Agentic code review, no signup to try: reality gates + frontier-model review, with veto.
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Advisory deep-dive on existing code — scores and findings, deliberately NO pass/fail verdict, so it never blocks an agent. Surfaces performance hot paths, scalability cliffs, reliability gaps and tech debt with concrete latency/throughput arithmetic (e.g. 'O(n²) dedup: ~4s at 10k items'). Read-only: the code is analyzed, never executed. Use it to understand a validate_ai_output rejection or review inherited code; use validate_ai_output when you need an accept/reject decision.
The source code to analyze — a function, file or pasted excerpt.
Source language, e.g. 'python', 'typescript', 'cpp', 'sql', 'swift'. Inferred if omitted; stating it sharpens findings.
Lens for the review: 'quality' (default, broad ISO/IEC 25010 pass) or a focused pass on one dimension.
Advisory deep-dive on existing code — scores and findings, deliberately NO pass/fail verdict, so it never blocks an agent. Surfaces performance hot paths, scalability cliffs, reliability gaps and tech debt with concrete latency/throughput arithmetic (e.g. 'O(n²) dedup: ~4s at 10k items'). Read-only: the code is analyzed, never executed. Use it to understand a validate_ai_output rejection or review inherited code; use validate_ai_output when you need an accept/reject decision.
| Argument | Type | Description |
|---|---|---|
| code* | string | The source code to analyze — a function, file or pasted excerpt. |
| language | string | Source language, e.g. 'python', 'typescript', 'cpp', 'sql', 'swift'. Inferred if omitted; stating it sharpens findings. |
| analysis_type | string | Lens for the review: 'quality' (default, broad ISO/IEC 25010 pass) or a focused pass on one dimension. |
{
"type": "object",
"required": [
"code"
],
"properties": {
"code": {
"type": "string",
"description": "The source code to analyze — a function, file or pasted excerpt."
},
"language": {
"type": "string",
"description": "Source language, e.g. 'python', 'typescript', 'cpp', 'sql', 'swift'. Inferred if omitted; stating it sharpens findings."
},
"analysis_type": {
"enum": [
"quality",
"performance",
"scalability",
"security",
"tech_debt"
],
"type": "string",
"default": "quality",
"description": "Lens for the review: 'quality' (default, broad ISO/IEC 25010 pass) or a focused pass on one dimension."
}
}
}Generate code and gate it in one step: an LLM writes the implementation, then the same protection engine as validate_ai_output vets it — retrying generation when the gate rejects. If every attempt is vetoed you still receive the last attempt, clearly marked validated:false with the gate findings — rejected code is never presented as clean. Generation runs on our infrastructure; nothing executes in your environment.
| Argument | Type | Description |
|---|---|---|
| prompt* | string | What to build, with any constraints worth enforcing — e.g. 'a rate-limited retry decorator with exponential backoff, stdlib only'. |
| language | string | Target language for the generated code, e.g. 'python' (default), 'typescript', 'go', 'sql'. |
| max_tokens | integer | Generation budget. The default 4000 fits most functions/classes; raise it for multi-file scaffolds. |
{
"type": "object",
"required": [
"prompt"
],
"properties": {
"prompt": {
"type": "string",
"description": "What to build, with any constraints worth enforcing — e.g. 'a rate-limited retry decorator with exponential backoff, stdlib only'."
},
"language": {
"type": "string",
"default": "python",
"description": "Target language for the generated code, e.g. 'python' (default), 'typescript', 'go', 'sql'."
},
"max_tokens": {
"type": "integer",
"default": 4000,
"maximum": 32768,
"minimum": 256,
"description": "Generation budget. The default 4000 fits most functions/classes; raise it for multi-file scaffolds."
}
}
}The merge gate for ANY AI-written output — code, documentation, reports, emails, configs: returns a binary approve/reject verdict with veto power — e.g. it rejects code calling the nonexistent stripe.Inventory API, an N+1 loop with the latency arithmetic to prove it, or a doc claiming success with no evidence. Deterministic reality gates (mock/placeholder veto, gaming and bypass detection, invented-API checks) run first and cannot be overridden; a frontier-model review (ISO/IEC 25010) then scores quality, accuracy, reliability and tech debt. In a benchmark, a frontier model reviewing alone caught reward-gaming and hallucinated APIs 0/6 times in a natural review workflow; these gates catch them deterministically on every call. Read-only: nothing is executed. Call it on every AI-generated deliverable before accepting it; use validate_plan for plans, analyze_code for an advisory report without a verdict.
| Argument | Type | Description |
|---|---|---|
| context | object | string | Optional review context — an object like {"language": "cpp", "scale": "10k req/s"} ('language' sharpens SDK-reality checks) or a free-text sentence describing intent. |
| ai_output* | string | The AI-generated output to gate — source code (a diff, function or whole file, any mainstream language) or prose (documentation, a report, an email, release notes). For reliable latency keep one submission under ~15,000 characters; split larger artifacts at natural boundaries (functions, SQL statements, sections) and validate the units separately. Reviews are wall-clock bounded: an over-budget model review returns an explicit timed-out result (deterministic gates still run) rather than hanging. |
| validation_type | string | What the output is: 'code_generation' (default) for source code; 'documentation', 'report', 'email', 'text', ... for prose (code-marker gates are skipped, integrity gates and the frontier review still run). Use 'report' (or 'status_report' / 'handover') for anything that CLAIMS work is done or passing: there, a completion claim with no evidence in the text is a veto. 'plan' for designs/specs. |
Deterministic production-readiness gate for AI-built systems. Verifies the invariants that stop a system silently shipping broken: every critical component is PRESENT and LOADS, the import closure resolves (nothing assumed 'already on the box'), all runtime dependencies are declared, and health is a REAL fail-closed check. Returns approve/reject with a fix plan and ISO 27001 / ISO 5055 control evidence. Facts are gathered by the Verificate collector in your CI; the gate is the authority. Non-bypassable, fails closed. This is the control-plane sibling of validate_ai_output — code quality is one invariant; this gates the whole deployable.
| Argument | Type | Description |
|---|---|---|
| artifact* | object | Collected artifact facts: {critical_components:[{name,loads:bool}], import_closure_ok:bool, undeclared_deps:[str], health_truthful:bool}. |
{
"type": "object",
"required": [
"artifact"
],
"properties": {
"artifact": {
"type": "object",
"description": "Collected artifact facts: {critical_components:[{name,loads:bool}], import_closure_ok:bool, undeclared_deps:[str], health_truthful:bool}."
}
}
}The gate for PLANS, designs and specs — run BEFORE any code is written, the cheapest place to catch a bad design. Returns the same binary verdict shape as validate_ai_output, with findings on completeness, feasibility, performance and scalability implications, security risks and missing considerations (e.g. it rejects a plan that polls an API every 100ms per client, with the request-volume math). Read-only: nothing is executed or stored beyond the verdict. Use validate_ai_output for the code that follows.
| Argument | Type | Description |
|---|---|---|
| plan* | string | The implementation plan, design or spec to validate, as plain text or markdown — e.g. a numbered migration plan or an architecture sketch. |
| context | object | Optional constraints the review should weigh, e.g. {"system": "payments API", "scale": "1M users", "constraints": "PostgreSQL only"}. |
{
"type": "object",
"required": [
"plan"
],
"properties": {
"plan": {
"type": "string",
"description": "The implementation plan, design or spec to validate, as plain text or markdown — e.g. a numbered migration plan or an architecture sketch."
},
"context": {
"type": "object",
"description": "Optional constraints the review should weigh, e.g. {\"system\": \"payments API\", \"scale\": \"1M users\", \"constraints\": \"PostgreSQL only\"}."
}
}
}{
"type": "object",
"required": [
"ai_output"
],
"properties": {
"context": {
"type": [
"object",
"string"
],
"description": "Optional review context — an object like {\"language\": \"cpp\", \"scale\": \"10k req/s\"} ('language' sharpens SDK-reality checks) or a free-text sentence describing intent."
},
"ai_output": {
"type": "string",
"description": "The AI-generated output to gate — source code (a diff, function or whole file, any mainstream language) or prose (documentation, a report, an email, release notes). For reliable latency keep one submission under ~15,000 characters; split larger artifacts at natural boundaries (functions, SQL statements, sections) and validate the units separately. Reviews are wall-clock bounded: an over-budget model review returns an explicit timed-out result (deterministic gates still run) rather than hanging."
},
"validation_type": {
"type": "string",
"default": "code_generation",
"description": "What the output is: 'code_generation' (default) for source code; 'documentation', 'report', 'email', 'text', ... for prose (code-marker gates are skipped, integrity gates and the frontier review still run). Use 'report' (or 'status_report' / 'handover') for anything that CLAIMS work is done or passing: there, a completion claim with no evidence in the text is a veto. 'plan' for designs/specs."
}
}
}