AI-agent readiness of business websites: scans, city indexes, assistants' answers, direct links.
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Where the assistants send people in a city: the league table of destinations (the businesses' own sites, each marketplace and directory by name, press and guides, other sites) with the share of answers that link each one, per assistant and overall, and the headline shares (direct, marketplace, the top marketplace). Pages: https://directindex.org/city/{slug}/assistants and https://directindex.org/assistants for every city.
City slug, for example lisbon; 'all' for every city together
Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
How many destinations
Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.
Where the assistants send people in a city: the league table of destinations (the businesses' own sites, each marketplace and directory by name, press and guides, other sites) with the share of answers that link each one, per assistant and overall, and the headline shares (direct, marketplace, the top marketplace). Pages: https://directindex.org/city/{slug}/assistants and https://directindex.org/assistants for every city.
| Argument | Type | Description |
|---|---|---|
| city* | string | City slug, for example lisbon; 'all' for every city together |
| limit | integer | How many destinations |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"city",
"context",
"llm_model"
],
"properties": {
"city": {
"type": "string",
"description": "City slug, for example lisbon; 'all' for every city together"
},
"limit": {
"type": "integer",
"default": 25,
"maximum": 200,
"minimum": 1,
"description": "How many destinations"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}The places ChatGPT, Claude and Gemini name in a city when asked the way people ask ('best pizza delivered right now', 'book me a table for Saturday'): per question, the places named, which assistant named each, whether with a link to the place's own site, and the direct booking or ordering link where the place has one. Pages: https://directindex.org/city/{slug}/recommended and /recommended/{question}.
| Argument | Type | Description |
|---|---|---|
| city* | string | City slug, for example lisbon; see list_cities |
| intent | string | A question key to narrow to one question, for example pizza-delivery, romantic, fado; empty for all |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
What changed in a city index over the last days: findings fixed or new, grades up or down, AI crawlers turned away or let in, direct booking or ordering channels and vendors gained or lost, and assistants that changed their answer about a business. Each change links the business's report. Also a page (https://directindex.org/city/{slug}/changes), an Atom feed (/changes.xml) and JSON (/api/city/{slug}/changes?days=30).
| Argument | Type | Description |
|---|---|---|
| city* | string | City slug, for example lisbon; see list_cities |
| days | integer | |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
What a city index's websites say, compared with every index of the same kind: the share of listed businesses with no web address, only a social profile or their own site; the share of sites that turn an AI crawler away, publish a readable menu, take bookings or orders directly or grade A or B; the share that declare an English version, show prices, link to WhatsApp, show an old copyright year or load a consent manager; the middle visible price and the page weight. Each with its base, rank and medians. Page: https://directindex.org/city/{slug}#sites and https://directindex.org/stats.
| Argument | Type | Description |
|---|---|---|
| city* | string | Index slug, for example lisbon or berlin-cafes-bars; see list_cities |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
Businesses in a city index ranked by Agent-Direct Score, with grade, menu format, direct channel and whether AI crawlers are blocked.
| Argument | Type | Description |
|---|---|---|
| city* | string | City slug, for example lisbon |
| limit | integer | |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
Two city indexes side by side: business websites scanned, the share that take a booking or an order on their own site, the share that turn an AI crawler away, the share scoring A or B, grades, menus, channels, builders, vendors, the assistants' direct share where probed, and the month-by-month numbers. Takes index slugs or city names (lisbon, Porto, berlin-cafes-bars). Page: https://directindex.org/compare/{a}/{b}.
| Argument | Type | Description |
|---|---|---|
| a* | string | First city or index slug, for example lisbon |
| b* | string | Second city or index slug, for example porto |
| kind | string | Which kind of index when a city name is given |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
A country's indexes added together (ISO code, for example PT or DE): sites scanned, direct share, crawler-blocked share, A-or-B share, the cities with their numbers, the kinds, the vendors common in the country. Without a code: every country with an index. Pages: https://directindex.org/country/{code} and /countries.
| Argument | Type | Description |
|---|---|---|
| code | string | Two-letter country code, for example PT; empty for the list of countries |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
The direct record of a business: the booking, ordering and menu links an agent should use instead of a marketplace, where each leads (the business's own site or a named vendor), whether and when a browser verified it, the hours (OpenStreetMap form and schema.org, with open_now), phone, address, the assistants' latest verdicts, how often agents read and followed it this month, the score, and the source and date of every fact. Corrected by the owner where the business is claimed. Also GET https://directindex.org/api/direct/{domain}.
| Argument | Type | Description |
|---|---|---|
| domain* | string | Registered domain, for example belcanto.pt |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id |
Places in a city that take a booking or an order on their own website, best Agent-Direct Scores first, with the direct booking or ordering link for each (the owner's corrected link where the business is claimed), the vendor behind it, verified_at when a browser reached the step before confirming, the vendor's terms for agents when noted, the hours, and follow links (https://directindex.org/go/{domain}/book, /order, /menu) that count. Use it to recommend places a person can book or order from directly, without a marketplace. Optional query: a cuisine, a dish or a few words, for example pizza, sushi, vegan, francesinha. Optional filters: lat, lon and radius_m for places near a point; open_now for places open at this moment in the city's zone (unknown hours stay in, marked null); verified_only for links a browser verified; vendor for one booking or ordering vendor (slug as on https://directindex.org/vendors). The same lists exist as pages at https://directindex.org/city/{slug}/direct, /direct/book, /direct/order and /direct/{want}; the full record of one place is available by domain.
| Argument | Type | Description |
|---|---|---|
| lat | number | Latitude of the person; with lon, only places within radius_m |
| lon | number | Longitude of the person |
| city* | string | City slug, for example lisbon; see list_cities |
| want | string | book: a table; order: food to collect or deliver; any: either |
| limit | integer |
Status of a deep report order by its token, and the finished report itself as Markdown once it is done (every answer in full, the table of where answers sent people, the nearest similar places, the fix plan and the kit).
| Argument | Type | Description |
|---|---|---|
| order* | string | The 32-character order token from order_deep_report |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
Return the latest Agent-Direct report for a domain that has already been scanned, including findings, fixes and agent-discoverability checks.
| Argument | Type | Description |
|---|---|---|
| domain* | string | Registered domain, for example belcanto.pt |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
List the city indexes that exist, with counts and status.
| Argument | Type | Description |
|---|---|---|
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"context",
"llm_model"
],
"properties": {
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}What things cost on restaurant menus in a city: the middle price, and the middle half of prices, of an espresso, a cappuccino, a beer, a glass of wine, a margherita, a burger, a main course, a lunch offer, a cola and a bottle of still water, read from the menus on restaurants', cafes' and bars' own websites, with the number of menus behind each figure, the day they were read and how many prices a hand check found right. Covers 13 European cities so far (Paris, Madrid, Berlin, Milan, Lisbon, Vienna and others); without a city it lists them. Figures are menu prices, not what a bill comes to.
| Argument | Type | Description |
|---|---|---|
| city | string | City slug, for example paris or madrid; leave out for the list of cities with prices |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
Order the paid deep report (5 EUR, one-off) for a business in a city index: ChatGPT, Claude and Gemini are asked ten questions about it the way people ask, every answer is kept in full with where it sent people, plus the nearest similar places, the fix plan with the kit to paste, what an agent reads on the site, a page and a PDF. Returns the order token and a Stripe checkout link for the person to pay (nothing is charged until they do); the report is written in about fifteen minutes after payment and also emailed, and its status and text can be read by the token.
| Argument | Type | Description |
|---|---|---|
| lang | string | Language of the delivery mail: en, pt, es, fr, de, nl, it, da or cs |
| email* | string | Where the report and the receipt go |
| domain* | string | The business's registered domain, for example belcanto.pt; it must be in a city index (see city_leaderboard) |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* |
Every city index of a kind ranked on three measures with its sample size and date: direct share (a booking or ordering path on the business's own domain), crawler-open share (not turned away at the edge) and A-or-B share. Indexes with fewer than 100 scanned sites are listed unranked, and those with fewer than four in five of their own websites scanned are listed as partly scanned. Page: https://directindex.org/rankings?kind=.
| Argument | Type | Description |
|---|---|---|
| kind | string | restaurants, cafes, salons, clinics, tours, or all (whole cities, every kind added) |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
Scan a business website and return its Agent-Direct Score (0 to 100), grade, findings and fixes. Reuses a scan under 24 hours old; otherwise runs one, which takes 10 to 40 seconds.
| Argument | Type | Description |
|---|---|---|
| url* | string | Website address, for example yourbusiness.com |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
Find businesses in the city indexes by name or domain, filtered by city, kind, grade, builder, booking or ordering vendor and finding (for example menu_pdf, edge_blocks, no_structured, booking_marketplace). Fifty results a page, best Agent-Direct Scores first, each with its report link. Free, no contacts. Page: https://directindex.org/search.
| Argument | Type | Description |
|---|---|---|
| q | string | A name, part of a name, or a domain |
| city | string | City or index slug, for example berlin or berlin-cafes-bars |
| kind | string | |
| page | integer | |
| grade | string | |
| vendor | string | Vendor slug, for example thefork, zenchef, toast |
| builder | string | Builder slug, for example wordpress, wix, squarespace |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
A booking or ordering vendor across the index: software on the vendor's domain or a marketplace, booking or ordering, how many sites use it, their average score and A or B share, how the browser action test went on them, the cities, example sites, and the vendor's terms for agents when a note exists. Vendor slugs as on https://directindex.org/vendors (zenchef, sevenrooms, thefork, toast ...).
| Argument | Type | Description |
|---|---|---|
| slug* | string | Vendor slug, for example zenchef |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
Whether a booking or ordering vendor's terms let an AI agent book or order through it: allowed, partners only, banned, or not stated; with the vendor's own page and the date the terms were read. Without a vendor: every researched vendor. Use it before sending a person to book or order through a vendor on an agent's behalf.
| Argument | Type | Description |
|---|---|---|
| vendor | string | Vendor slug as it appears in reports, for example thefork, opentable, square |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
What ChatGPT, Claude and Gemini answer about one business: the latest verdict per question (official website, where to book, where to order: own site, vendor, marketplace, directory, no link), the answers quoted, the questions people ask for which the business was named, and one sentence on why an assistant sent people elsewhere. For businesses in a city index that have been asked about; see the report at https://directindex.org/r/{domain}.
| Argument | Type | Description |
|---|---|---|
| domain* | string | Registered domain, for example belcanto.pt |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"city",
"context",
"llm_model"
],
"properties": {
"city": {
"type": "string",
"description": "City slug, for example lisbon; see list_cities"
},
"intent": {
"type": "string",
"description": "A question key to narrow to one question, for example pizza-delivery, romantic, fado; empty for all"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| conversation_id |
| string |
| Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"city",
"context",
"llm_model"
],
"properties": {
"city": {
"type": "string",
"description": "City slug, for example lisbon; see list_cities"
},
"days": {
"type": "integer",
"default": 30,
"maximum": 365,
"minimum": 1
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| conversation_id |
| string |
| Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"city",
"context",
"llm_model"
],
"properties": {
"city": {
"type": "string",
"description": "Index slug, for example lisbon or berlin-cafes-bars; see list_cities"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"city",
"context",
"llm_model"
],
"properties": {
"city": {
"type": "string",
"description": "City slug, for example lisbon"
},
"limit": {
"type": "integer",
"default": 50,
"maximum": 500,
"minimum": 1
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"a",
"b",
"context",
"llm_model"
],
"properties": {
"a": {
"type": "string",
"description": "First city or index slug, for example lisbon"
},
"b": {
"type": "string",
"description": "Second city or index slug, for example porto"
},
"kind": {
"enum": [
"restaurants",
"cafes",
"salons",
"clinics",
"tours"
],
"type": "string",
"default": "restaurants",
"description": "Which kind of index when a city name is given"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"context",
"llm_model"
],
"properties": {
"code": {
"type": "string",
"description": "Two-letter country code, for example PT; empty for the list of countries"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| string |
| Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"domain",
"context",
"llm_model"
],
"properties": {
"domain": {
"type": "string",
"description": "Registered domain, for example belcanto.pt"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| query | string | What the person wants: a cuisine, a dish or a few words. Empty for any. |
| vendor | string | Only places on this booking or ordering vendor, by slug: zenchef, sevenrooms, toast ... |
| context* | string | Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution." |
| open_now | boolean | Only places open right now by their OpenStreetMap hours, in the city's zone; places with unreadable hours stay in with open_now null |
| radius_m | integer | Metres around lat, lon |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| verified_only | boolean | Only links a browser verified: an agent reached the step before confirming |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"city",
"context",
"llm_model"
],
"properties": {
"lat": {
"type": "number",
"description": "Latitude of the person; with lon, only places within radius_m"
},
"lon": {
"type": "number",
"description": "Longitude of the person"
},
"city": {
"type": "string",
"description": "City slug, for example lisbon; see list_cities"
},
"want": {
"enum": [
"book",
"order",
"any"
],
"type": "string",
"default": "any",
"description": "book: a table; order: food to collect or deliver; any: either"
},
"limit": {
"type": "integer",
"default": 10,
"maximum": 25,
"minimum": 1
},
"query": {
"type": "string",
"description": "What the person wants: a cuisine, a dish or a few words. Empty for any."
},
"vendor": {
"type": "string",
"description": "Only places on this booking or ordering vendor, by slug: zenchef, sevenrooms, toast ..."
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"open_now": {
"type": "boolean",
"default": false,
"description": "Only places open right now by their OpenStreetMap hours, in the city's zone; places with unreadable hours stay in with open_now null"
},
"radius_m": {
"type": "integer",
"default": 1000,
"maximum": 50000,
"minimum": 50,
"description": "Metres around lat, lon"
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"verified_only": {
"type": "boolean",
"default": false,
"description": "Only links a browser verified: an agent reached the step before confirming"
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"order",
"context",
"llm_model"
],
"properties": {
"order": {
"type": "string",
"description": "The 32-character order token from order_deep_report"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"domain",
"context",
"llm_model"
],
"properties": {
"domain": {
"type": "string",
"description": "Registered domain, for example belcanto.pt"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| conversation_id |
| string |
| Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"context",
"llm_model"
],
"properties": {
"city": {
"type": "string",
"description": "City slug, for example paris or madrid; leave out for the list of cities with prices"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| string |
| The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"domain",
"email",
"context",
"llm_model"
],
"properties": {
"lang": {
"type": "string",
"default": "en",
"description": "Language of the delivery mail: en, pt, es, fr, de, nl, it, da or cs"
},
"email": {
"type": "string",
"description": "Where the report and the receipt go"
},
"domain": {
"type": "string",
"description": "The business's registered domain, for example belcanto.pt; it must be in a city index (see city_leaderboard)"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"context",
"llm_model"
],
"properties": {
"kind": {
"enum": [
"restaurants",
"cafes",
"salons",
"clinics",
"tours",
"all"
],
"type": "string",
"default": "restaurants",
"description": "restaurants, cafes, salons, clinics, tours, or all (whole cities, every kind added)"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"url",
"context",
"llm_model"
],
"properties": {
"url": {
"type": "string",
"description": "Website address, for example yourbusiness.com"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}| finding | string | Finding id, for example menu_pdf, edge_blocks, robots_blocks, no_structured, no_text_nojs, no_channel, booking_marketplace, ordering_marketplace, no_llms_txt |
| llm_model* | string | The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess. |
| conversation_id | string | Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request. |
{
"type": "object",
"required": [
"context",
"llm_model"
],
"properties": {
"q": {
"type": "string",
"description": "A name, part of a name, or a domain"
},
"city": {
"type": "string",
"description": "City or index slug, for example berlin or berlin-cafes-bars"
},
"kind": {
"enum": [
"restaurants",
"cafes",
"salons",
"clinics",
"tours"
],
"type": "string"
},
"page": {
"type": "integer",
"default": 1,
"minimum": 1
},
"grade": {
"enum": [
"A",
"B",
"C",
"D",
"F"
],
"type": "string"
},
"vendor": {
"type": "string",
"description": "Vendor slug, for example thefork, zenchef, toast"
},
"builder": {
"type": "string",
"description": "Builder slug, for example wordpress, wix, squarespace"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"finding": {
"type": "string",
"description": "Finding id, for example menu_pdf, edge_blocks, robots_blocks, no_structured, no_text_nojs, no_channel, booking_marketplace, ordering_marketplace, no_llms_txt"
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"slug",
"context",
"llm_model"
],
"properties": {
"slug": {
"type": "string",
"description": "Vendor slug, for example zenchef"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"context",
"llm_model"
],
"properties": {
"vendor": {
"type": "string",
"description": "Vendor slug as it appears in reports, for example thefork, opentable, square"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}{
"type": "object",
"required": [
"domain",
"context",
"llm_model"
],
"properties": {
"domain": {
"type": "string",
"description": "Registered domain, for example belcanto.pt"
},
"context": {
"type": "string",
"description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\""
},
"llm_model": {
"type": "string",
"description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess."
},
"conversation_id": {
"type": "string",
"description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request."
}
}
}