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Writing · Version 1.2.0 · Reviewed 2026-08-02

API Documentation Reviewer

Make the reader act on completeness and example accuracy with evidence, explicit trade-offs, and a verification plan.

4 method steps 6 documented failure modes 5 diagnostic checks 7 quality gates

Reviews API documentation for completeness, accuracy, and whether a new integrator can succeed.

₹99 one-time

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What this skill helps you do

  • Completeness
  • Example accuracy
  • Error documentation

How API Documentation Reviewer works

You provide

Suite structure, failure history, and the risk to cover

It inspects

Nondeterminism sources affecting completeness

It decides

A example accuracy plan at the cheapest useful level

You verify

The test fails when the behavior is broken, not only passes

What it checks first

API Documentation Reviewer reviews API documentation for completeness, accuracy, and whether a new integrator can succeed. Use it when the work involves Completeness, Example accuracy, Error documentation.

  1. Whether the test asserts behavior or implementation, because implementation-coupled tests break on safe refactors.
  2. Sources of nondeterminism: time, randomness, ordering, concurrency, network, and shared state.
  3. Whether tests share mutable state, which makes failures depend on execution order.
  4. The test pyramid balance, since a suite dominated by end-to-end tests is slow and flaky by construction.
  5. Whether a failing test failed for the intended reason, verified by making it fail deliberately.

Failure modes it recognizes

  • A flaky test caused by a fixed sleep instead of waiting for the actual condition.
  • Tests passing in isolation and failing in suite because of leaked global or database state.
  • Time-dependent assertions failing at month or year boundaries or across daylight-saving transitions.
  • Over-mocking that verifies the mock rather than the integration, so the suite passes while production breaks.
  • A test asserting on unordered collection order, which passes until the implementation changes hashing.
  • Coverage measured but assertions absent, so lines execute without being verified.

Answers it will reject

  • Retrying a flaky test to make CI green, which converts a real intermittent bug into an invisible one.
  • Chasing a coverage percentage, which produces tests that execute code without asserting behavior.
  • Writing an end-to-end test for logic that a unit test could cover deterministically and instantly.
  • Deleting a failing test to unblock a release without recording the risk that was accepted.

Decision rules it applies

  • Choose the cheapest test level that can actually observe the failure mode.
  • A flaky test is a defect in the test or the system; quarantine with an owner and a deadline, never ignore.
  • Assert on observable behavior and public contracts so refactors stay free.
  • Every bug fix gets a test that fails before the fix and passes after it.

Evidence it asks for

  • Run the suite in randomized order to expose inter-test dependencies.
  • Track flake rate per test over time rather than treating each failure as isolated.
  • Verify a new test fails when the behavior is broken, not only that it passes when correct.

The method inside

  1. Identify the reader decision before drafting
  2. Lead with the conclusion and strongest evidence
  3. Remove unsupported claims and background that does not change action
  4. Check traceability, ambiguity, and the explicit ask

Deliverables

  • Completeness revised draft
  • Example accuracy source and logic check
  • Error documentation approval-ready version

Evidence requirements

  • Source analysis, facts, decisions, and approved claims
  • Named audience, decision, and desired action
  • Format, length, tone, and review constraints

Quality gates

  • Every material claim traces to supplied evidence or is labeled as a hypothesis.
  • The response follows the declared deliverable contract.
  • No execution, access, measurement, or verification is invented.
  • Secrets and personal data are redacted rather than repeated.
  • The user receives a concrete independent verification step.
  • The relevant failure modes in this domain were considered rather than only the reported symptom.
  • No listed anti-pattern was recommended as a solution.

Example task

Input

Review our API docs. Integrators keep opening support tickets for things we believe are documented.

Expected output

Tickets are the measurement: each one names a place the documentation failed. The usual gaps are authentication setup, error responses, and pagination behavior, which are documented as reference but never as a working end-to-end first request...

Boundaries and compatibility

Ideal for

  • Completeness: produce a decision or artifact grounded in supplied evidence.
  • Example accuracy: produce a decision or artifact grounded in supplied evidence.
  • Error documentation: produce a decision or artifact grounded in supplied evidence.

Out of scope

  • Inventing facts, quotations, or approvals
  • Hiding uncertainty or material bad news

Agent compatibility

  • GitHub Copilot custom agents
  • Claude Agent Skills / SKILL.md
  • Any instruction-following chat model

Tool policy: Advisory by default. No tools are assumed. If the host provides tools, use read-only evidence gathering unless the user explicitly approves a scoped write or execution action.