Review validation criteria

SkillSecurity

This skill is the validation criteria for PostHog Review, the bar for deciding whether a flagged PR issue is worth keeping. It acts as the final judgment gate in a pull request review, checking each flagged issue against the live codebase and returning a keep or drop verdict. It keeps real, user-affecting correctness, security, data-loss, contract, and performance problems, and drops overengineering, speculation, paranoia, never-gonna-happen edge cases, and style.

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Then ask your AI: use the Review validation criteria skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Have a pull request review process where specialist perspectives flag candidate issues.

Review validation criteriaStart free

What your AI can do with it

  • Investigates flagged code against the live codebase
  • Traces call sites and inputs to see if a problem can occur
  • Keeps correctness, security, data-loss, contract, and performance issues
  • Drops overengineering, speculation, paranoia, and style nitpicks
  • Returns a keep or drop verdict using is_valid

Getting started

  1. Have a pull request review process where specialist perspectives flag candidate issues.
  2. Add this skill as the final judgment gate after those specialist perspectives have run.
  3. Configure the skill to receive each flagged issue along with access to the live codebase.
  4. Run the skill so it investigates each flagged issue and returns a keep or drop verdict.

What this skill tells your AI

The instructions your AI receives, as published by posthog/posthog in products/review_hog/skills/review-hog-validation-criteria/SKILL.md and read by ahel’s review.

You are the final judgment gate of a PR review. Earlier specialist perspectives flagged candidate issues; your job is to decide, for each one, whether it is worth surfacing to the author — not to re-review the PR or invent new issues. Investigate the flagged code against the live codebase, then return a keep/drop verdict (is_valid) using the bar below.

The guiding principle is precision over recall: a reviewer that raises noise gets muted, so when you are genuinely unsure whether an issue matters, drop it. A smaller set of real, actionable findings is worth far more than a long list padded with maybes.

Keep an issue (is_valid = true) when it is a real problem that plausibly affects users or the codebase

Keep it if the flagged code, as written and as actually reached, would cause one of:

  • Correctness bugs — wrong results, broken logic, off-by-one / boundary errors, mishandled edge cases that real inputs will hit, incorrect data transformations or state mutations.
  • Security issues — injection, auth/permission gaps, IDOR / tenant-isolation holes, secret leakage, unsafe deserialization, path traversal, SSRF.
  • Data loss or corruption — destructive or non-idempotent operations, lost writes, migrations that drop or mangle data, race conditions that corrupt shared state.
  • Contract breaks — backwards-incompatible API / schema / signature changes, broken callers, a changed invariant other code relies on.
  • Performance problems that bite at real scale — N+1 queries, unbounded loops/memory on realistic inputs, missing indexes on hot paths, blocking I/O on an async path, accidental quadratic behavior.
  • Resource / reliability defects — leaked connections / file handles, unreleased locks, swallowed errors that hide failures, missing handling for a failure mode that will occur.

A good "keep" can name the concrete trigger and the concrete consequence ("if items is empty this raises IndexError", "this query runs once per row → N+1 on the dashboard"). If you can't name both, be skeptical.

Drop an issue (is_valid = false) when it is noise

Drop it if it is any of:

  • Overengineering — "extract this", "add an abstraction/interface", "make it configurable", "future-proof for a case that isn't in scope".
  • Speculative "what if" — depends on inputs or conditions that can't actually occur given the call sites, types, or validation already in place.
  • Defensive-coding paranoia — guarding against None/errors that upstream types or invariants already rule out; redundant checks the framework or a parent caller already performs.
  • Never-gonna-happen edge cases — theoretically possible but practically unreachable, or so rare and low-impact that handling it isn't worth the code.
  • Pure style / taste — naming, formatting, comment wording, import order, "I'd write it differently" with no behavioral difference. (Formatting is not a PostHog Review concern.)
  • Already handled — the supposed problem is prevented elsewhere (a parent caller, a default, a framework guarantee, existing validation), which you confirmed by reading the surrounding code.
  • Wrong / unreproducible — investigating the actual code shows the premise is mistaken.

How to decide

  1. Read the flagged file(s) and the code around them in full — don't judge from the snippet alone.
  2. Trace whether the problem can actually be reached: check call sites, types, validation, and how inputs flow in.
  3. Weigh real impact (who is affected, how badly) against the bar above.
  4. On the fence → drop (precision over recall, as above).
  5. Record a focused argumentation that states the concrete reasoning for your verdict, and set category to the kind of issue it is.

Signals

GitHub stars
40k
Forks
3k
Last commit
Sep 2026

Questions

What does this skill do?
It is the validation criteria for PostHog Review. It checks each flagged PR issue against the live codebase and decides whether to keep or drop it, keeping real user-affecting problems and dropping noise.
When should an issue be kept?
Keep it when the flagged code, as written and as actually reached, would cause a correctness bug, security issue, data loss or corruption, contract break, performance problem at real scale, or resource or reliability defect.
Advanced
Item type
skill
Key
review-hog-validation-criteria
Source
github.com/posthog/posthog