Historical ES Book Pressure data, matched evidence, and evaluation guidance for $5 USDC via x402.
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BRING YOUR OWN ES STRATEGY. TEST WHETHER AUCTIONTRACE HELPS MANAGE ITS TRADES BETTER. WHAT IT IS For $5.00 USDC on Base mainnet, AuctionTrace delivers 751,598 validated, timestamped ES Book Pressure observations, a seven-category application map, matched historical evidence, rejected-use guidance, and an accompanying public toolkit for package verification, strict as-of alignment, and matched result comparison. Join the observations strict as-of after entries your strategy already makes; keep entries and baseline behavior fixed. WHAT THE EVIDENCE SUPPORTS Across seven category-specific historical applications, relative profit-factor improvement versus matched price-only management ranged from 2.40% to 26.26%. All seven published AuctionTrace treatment profit factors remained below 1.0, ranging from 0.5130 to 0.9246. The evidence therefore supports better post-entry management versus each matched baseline; it does not establish a profitable standalone system, guarantee profitability, or predict future performance. Six high-sample studies covered 63,350 identical entries and improved all 18 of 18 study windows and all 36 of 36 chronological halves. WHERE IT WAS TESTED 1. Mean reversion — Use adverse pressure when it contradicts the mean-reversion thesis. PF 0.7882 -> 0.8835 (+12.09%). 2. Range rotation — De-risk when pressure contradicts the return-to-center thesis. PF 0.6645 -> 0.8390 (+26.26%). 3. Trend and momentum — Detect early post-entry failure while preserving the original entry. PF 0.8034 -> 0.9246 (+15.09%). 4. Pullback and retracement — Distinguish pressure consistent with resumption from a failed reclaim. PF 0.7038 -> 0.8054 (+14.44%). 5. Breakout and continuation — Cut risk when pressure contradicts the breakout while preserving runner logic. PF 0.7195 -> 0.7946 (+10.44%). 6. Scalping and microstructure — Use immediate adverse pressure to de-risk short-horizon trades. PF 0.5010 -> 0.5130 (+2.40%). 7. Reversal and exhaustion — Select which stopped trades merit an opposite-side child instead of reversing every stop. PF 0.6043 -> 0.7321 (+21.15%). Each application is category-specific. AuctionTrace is a finished signal family with documented applications, not one immutable trading rule reused across every strategy. WHAT $5 DELIVERS The private ZIP is the immutable Release 008 six-file package: data.csv, the complete machine-readable AgentOffer, the seven-category playbook, a strict-as-of quickstart scaffold, a README, and a hash manifest. Public companion tools at /buyer-kit/README.md add package verification and matched baseline-versus-treatment comparison without exposing AuctionTrace construction logic or private treatment rules. The data is bar agnostic for consumption and covers 2025-07-29T22:00:00.1320000Z through 2026-07-01T00:00:00.0000000Z exclusive. NEXT DECISION If your task, ES market, strategy category, coverage, evidence, payment constraints, and budget fit, purchase the $5 package and run the matched evaluation under your own risk policy. Read the complete evidence, category statuses, host scopes, limitations, rejected uses, package contract, and evaluation steps at /agent-offer.json. Purchase at /api/v1/datasets/auctiontrace-es-book-pressure-20250729-20260630-v1/access.
This tool takes no arguments.
BRING YOUR OWN ES STRATEGY. TEST WHETHER AUCTIONTRACE HELPS MANAGE ITS TRADES BETTER. WHAT IT IS For $5.00 USDC on Base mainnet, AuctionTrace delivers 751,598 validated, timestamped ES Book Pressure observations, a seven-category application map, matched historical evidence, rejected-use guidance, and an accompanying public toolkit for package verification, strict as-of alignment, and matched result comparison. Join the observations strict as-of after entries your strategy already makes; keep entries and baseline behavior fixed. WHAT THE EVIDENCE SUPPORTS Across seven category-specific historical applications, relative profit-factor improvement versus matched price-only management ranged from 2.40% to 26.26%. All seven published AuctionTrace treatment profit factors remained below 1.0, ranging from 0.5130 to 0.9246. The evidence therefore supports better post-entry management versus each matched baseline; it does not establish a profitable standalone system, guarantee profitability, or predict future performance. Six high-sample studies covered 63,350 identical entries and improved all 18 of 18 study windows and all 36 of 36 chronological halves. WHERE IT WAS TESTED 1. Mean reversion — Use adverse pressure when it contradicts the mean-reversion thesis. PF 0.7882 -> 0.8835 (+12.09%). 2. Range rotation — De-risk when pressure contradicts the return-to-center thesis. PF 0.6645 -> 0.8390 (+26.26%). 3. Trend and momentum — Detect early post-entry failure while preserving the original entry. PF 0.8034 -> 0.9246 (+15.09%). 4. Pullback and retracement — Distinguish pressure consistent with resumption from a failed reclaim. PF 0.7038 -> 0.8054 (+14.44%). 5. Breakout and continuation — Cut risk when pressure contradicts the breakout while preserving runner logic. PF 0.7195 -> 0.7946 (+10.44%). 6. Scalping and microstructure — Use immediate adverse pressure to de-risk short-horizon trades. PF 0.5010 -> 0.5130 (+2.40%). 7. Reversal and exhaustion — Select which stopped trades merit an opposite-side child instead of reversing every stop. PF 0.6043 -> 0.7321 (+21.15%). Each application is category-specific. AuctionTrace is a finished signal family with documented applications, not one immutable trading rule reused across every strategy. WHAT $5 DELIVERS The private ZIP is the immutable Release 008 six-file package: data.csv, the complete machine-readable AgentOffer, the seven-category playbook, a strict-as-of quickstart scaffold, a README, and a hash manifest. Public companion tools at /buyer-kit/README.md add package verification and matched baseline-versus-treatment comparison without exposing AuctionTrace construction logic or private treatment rules. The data is bar agnostic for consumption and covers 2025-07-29T22:00:00.1320000Z through 2026-07-01T00:00:00.0000000Z exclusive. NEXT DECISION If your task, ES market, strategy category, coverage, evidence, payment constraints, and budget fit, purchase the $5 package and run the matched evaluation under your own risk policy. Read the complete evidence, category statuses, host scopes, limitations, rejected uses, package contract, and evaluation steps at /agent-offer.json. Purchase at /api/v1/datasets/auctiontrace-es-book-pressure-20250729-20260630-v1/access.
No arguments.
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"properties": {}
}Submit private, optional feedback about the current AuctionTrace offer. Discovery --------- Call get_auctiontrace_product and read agent_offer.questionnaire before submitting. The HTTP equivalent and complete contract are at /api/v1/offer-feedback/schema. When to use ----------- - Tell the owner what task you are performing and what you were looking for. - Explain what is useful, unclear, undesirable, missing, or blocking purchase. - Request owner follow-up without purchasing. Do / Don't ---------- Do provide a stable submission_id so retries are idempotent. Do select the closest enumerated values and use free text only for additional context. Don't include credentials, payment signatures, private keys, proprietary strategy formulas, private addresses, local paths, or sensitive personal data. Idempotency ----------- Retrying the same submission_id from the same anonymous client returns the existing receipt.
| Argument | Type | Description |
|---|---|---|
| stage | string | |
| responses* | object | |
| submission_id | string | |
| schema_version* | string |
{
"type": "object",
"$schema": "http://json-schema.org/draft-07/schema#",
"required": [
"schema_version",
"responses"
],
"properties": {
"stage": {
"enum": [
"pre_purchase",
"post_purchase"
],
"type": "string",
"default": "pre_purchase"
},
"responses": {
"type": "object",
"required": [
"objective",
"principal_mandate",
"purchase_intent"
],
"properties": {
"likes": {
"type": "string",
"maxLength": 2000,
"minLength": 1
},
"missing": {
"type": "string",
"maxLength": 2000,
"minLength": 1
},
"dislikes": {
"type": "string",
"maxLength": 2000,
"minLength": 1
},
"es_status": {
"enum": [
"trades_es_now",
"researching_es",
"does_not_trade_es",
"not_applicable"
],
"type": "string"
},
"objective": {
"type": "string",
"maxLength": 1000,
"minLength": 1
},
"attracted_by": {
"type": "array",
"items": {
"enum": [
"finished_data",
"mathematical_evidence",
"category_specific_heuristics",
"integration_code",
"bar_agnostic_contract",
"supported_and_rejected_uses",
"low_acquisition_cost",
"es_income_opportunity",
"other"
],
"type": "string"
},
"default": [],
"maxItems": 9
},
"workflow_roles": {
"type": "array",
"items": {
"enum": [
"develop",
"test",
"deploy",
"manage",
"risk_control",
"evaluate_purchase",
"other"
],
"type": "string"
},
"default": [],
"maxItems": 7
},
"purchase_intent": {
"enum": [
"purchased",
"likely_to_purchase",
"considering",
"unlikely_to_purchase",
"will_not_purchase",
"not_applicable"
],
"type": "string"
},
"follow_up_contact": {
"type": "object",
"required": [
"method",
"value"
],
"properties": {
"value": {
"type": "string",
"maxLength": 500,
"minLength": 1
},
"method": {
"enum": [
"email",
"https_url",
"agent_identifier"
],
"type": "string"
}
},
"additionalProperties": false
},
"principal_mandate": {
"enum": [
"develop_trading_strategies",
"test_trading_strategies",
"deploy_trading_strategies",
"manage_trading_strategies",
"manage_trading_risk",
"evaluate_income_opportunities",
"research_market_data",
"other"
],
"type": "string"
},
"purchase_blockers": {
"type": "array",
"items": {
"enum": [
"no_payment_capability",
"unclear_value",
"insufficient_evidence",
"data_format",
"coverage",
"integration_effort",
"does_not_trade_es",
"needs_live_data",
"price",
"licensing",
"security_or_compliance",
"principal_policy",
"trust",
"other",
"none"
],
"type": "string"
},
"default": [],
"maxItems": 15
},
"information_needed": {
"type": "array",
"items": {
"enum": [
"sample_rows",
"full_schema",
"methodology",
"additional_evidence",
"integration_example",
"licensing_terms",
"payment_instructions",
"delivery_security",
"support_response",
"other",
"none"
],
"type": "string"
},
"default": [],
"maxItems": 11
},
"question_for_owner": {
"type": "string",
"maxLength": 2000,
"minLength": 1
},
"follow_up_requested": {
"type": "boolean",
"default": false
},
"strategy_categories": {
"type": "array",
"items": {
"enum": [
"mean_reversion",
"range_rotation",
"trend_momentum",
"pullback_retracement",
"breakout_continuation",
"scalping_microstructure",
"reversal_exhaustion",
"other",
"not_applicable"
],
"type": "string"
},
"default": [],
"maxItems": 9
},
"valuable_components": {
"type": "array",
"items": {
"enum": [
"finished_data",
"category_specific_applications",
"matched_evidence",
"rejected_use_map",
"quickstart_code",
"evaluation_procedure",
"integrity_manifest",
"human_support",
"other"
],
"type": "string"
},
"default": [],
"maxItems": 10
}
},
"additionalProperties": false
},
"submission_id": {
"type": "string",
"pattern": "^[A-Za-z0-9][A-Za-z0-9._:-]*$",
"maxLength": 128,
"minLength": 8
},
"schema_version": {
"type": "string",
"const": "auctiontrace_offer_feedback_submission_v1"
}
},
"additionalProperties": false
}