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rea-ci-tests-audit

Audit REA’s automated checks and test suites to find missed failures, outdated test data, and unnecessary work. Use reproducible experiments and timing measurements to assess fixes or efficiency changes while preserving checks that catch real defects.

OriginalShow the original description

Audit REA CI and test suites for correctness, fixture drift, false passes, and measured performance; use for suite or workflow investigations and efficiency changes, rather than ordinary feature testing or a single test failure.

AI rating90/ 100See how to install

Good for

  • Investigating CI checks that pass despite defects
  • Checking whether test data matches current behavior
  • Measuring unnecessary work in slow test suites
  • Reviewing test reductions for lost failure detection

Overview

What it does

rea-ci-tests-audit examines REA’s CI, the system that automatically checks changes, and its test suites to determine whether they detect real defects. It checks for differences between test data and current requirements, missed test discovery, and checks that pass even when required reports are missing. To investigate slowness, it measures preparation, build, test execution, and waiting time separately, then uses those measurements to assess improvements.

When it helps

Use it when you need to investigate an entire test suite or workflow rather than address one failing test. It helps assess ways to reduce duplicate preparation and check whether removing tests would also remove important verification. Findings are organized into reproduced defects, costs supported by evidence, hypotheses, and insufficient evidence.

Example requests

  • “Investigate whether any CI checks pass even when there is a defect.”
  • “Measure this slow test suite and propose improvements that preserve its ability to detect defects.”

Notes

The work follows REA’s AGENTS.md, testing guide, contribution rules, and specified toolchain. An investigation request alone does not authorize edits. Fixes, pushes, merges, and other actions must stay within the authority granted by the request.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt distinguishes suite and workflow audits from single-test troubleshooting and identifies correctness, missed failures, and performance as audit targets.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodIt specifies baseline revision recording, minimal reproductions, controlled failure injection, timing categories, finding classifications, and report fields.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodIt restricts investigation-only work from editing, isolates changes, requires restoring experimental mutations, and explicitly limits publication, push, and merge authority.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingIt directs readers to referenced documents for the pinned toolchain and real-engine prerequisites, but includes no installation steps itself.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (3)

  • SKILL.md6.6 KB
  • agents/openai.yaml259 B
  • references/measurement-and-ci.md3.8 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

REA CI and tests audit

Establish which checks still catch real regressions and which costs can be removed without losing that protection. The outcome may be a verified fix, an evidence-backed recommendation, or an explicit decision to stop.

Follow the checkout's AGENTS.md, testing guide, and contribution rules. Use their current commands and pinned toolchain, rather than commands remembered from an earlier audit. Preserve the requested scope: investigation alone does not authorize edits; this skill does not grant permission to publish issues, push, or merge. Existing user authorization still applies. Keep audit notes and raw results outside the tracked tree, normally in a task-specific /tmp directory.

Establish the executed baseline

Fetch when the user asks for latest main. Pin the baseline SHA and inspected workflow revision; use an isolated worktree when changing or comparing code. Do not modify another task's checkout. Record dirty changes and the exact command, toolchain, host, selected tests, instrumentation, and prerequisites. An old run is evidence for its executed revision, even if main advances.

Trace workflow triggers, changed-path selection, job dependencies, reusable actions, package scripts, test discovery, artifact producers, and report gates through to the commands that actually execute. Include scripts, generated data, runtime registration, and subprocess boundaries missing from import graphs. Check positive and negative selection paths: required files must be discovered once per intended test configuration; deliberate platform/configuration repeats are separate coverage. A missing explicit test or missing required report must not turn green. Optional lanes may skip; preserve their stated prerequisites.

Use existing timing and failure artifacts to select suspicious families. Run relevant checks to establish a baseline; reserve a full local suite for broad CI diagnosis or uncertainty that focused checks cannot resolve. Do not rebuild or rerun an unchanged complete suite after every documentation edit.

Prove the failure or protection

For each candidate, state the expected observable behavior and its owner, then construct the smallest reproduction against production behavior. Follow the producer and affected consumers before deciding where to fix it.

  • For drift, compare fixtures with current admission requirements, protocol replies, named contracts, tool versions, and actual public entrypoints. A plausible-looking mock can fail before the behavior its test claims to cover. Search the whole affected fixture family, including other version strings. Preserve intentionally malformed fixtures and test their intended rejection.
  • For a suspicious green test, perturb the relevant behavior in an isolated copy or inject a controlled failure. Verify that the existing assertion or gate detects it. A test may merely repeat its mock, import abandoned code, or hide a subprocess/checker failure. Restore mutations after the experiment.
  • For shared setup or pruning, map distinct assertions to their retained scenarios. Preserve malformed inputs, cancellation, cleanup failure, permissions, capacity, identity, and meaningful concurrency interactions. A faster run that skips a case or weakens its oracle is not an improvement.
  • For provider coverage, separate fake-producer, boundary, and actual-engine evidence. Inspect named skips and prerequisites; fixtures do not establish real Ghidra, LLDB, browser, or other provider behavior.

Classify findings as reproduced defects, supported costs, hypotheses, or unavailable evidence. Record the baseline command, observed output/exit status, expected result, affected scope, and competing explanation. A failure on main may be pre-existing; that does not by itself make it irrelevant to a CI audit. Attribute PR failures using the executed revision and a clean baseline, not just their resemblance to a previous failure. Retry only to test a specific transient explanation; retain the original failure and stop when repetition adds no evidence. A passing retry does not establish a root cause or a fix.

Assess efficiency without losing the gate

Read measurement and CI checks when investigating slowness, caching, runner waits, shared artifacts, or log noise. Compare equivalent completed work before claiming a speedup. Distinguish setup/build time, test execution, coverage instrumentation, dependency waits, and runner scheduling; state which costs remain unmeasured.

Prefer removing proven duplicate preparation, reusing immutable setup, and reducing repeated subprocess work before shrinking correctness coverage. Preserve independent sessions where lifecycle or concurrency is the oracle. Keep live tests fresh; a cached previous pass cannot validate current host, installed provider contents, permissions, or external state.

Fix, verify, and hand off within scope

If implementation is authorized, make the smallest structural change at the owning boundary and add a regression that fails on the baseline for the right reason. Retest affected consumers and meaningful negative paths; verify cache invalidation or discovery when those mechanisms change. Read the installed Turbo documentation before changing its configuration or commands.

Run the repository's applicable checks and inspect complete current-head CI results before an authorized merge. Preserve required coverage and discovery gates. Do not suppress a failure, add blanket retries, raise timeouts, or delete distinct assertions solely to make CI green. Changes to these controls need their own demonstrated reason and retained failure detection.

Report each confirmed issue with exact revision, reproduction, consequence, proposed correction, and validation limits. Report performance with workload and measurements, not just a percentage. Use English issue/PR records when requested; follow the user's assignment, commit identity, review, and merge preferences without assuming them for other users. Open ready-for-review PRs only when that lifecycle is authorized. Resolve necessary review findings and check final main against the tested tree after merging.

Stop when the authorized work is verified, remaining benefits are unproven, or further changes would trade correctness for speculative speed. List genuine uncertainties without turning them into additional optimization rounds.

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