Review Hog Validation Criteria

作者 PostHog469d1773e9cb無授權條款收錄於 2026年10月8日更新於 2026年10月8日

The validation criteria for PostHog Review, the bar for deciding whether a flagged PR issue is worth keeping. Keeps real, user-affecting correctness / security / data-loss / contract / performance problems; drops overengineering, speculation, paranoia, never-gonna-happen edge cases, and style.

AI 產生的概覽

定義用來判斷被標記的 PR 審查問題是否值得保留的驗證標準。

功能
這個技能為 PR 審查的最終判定環節提供判斷標準。它要求代理針對先前被標記的候選問題,對照實際的程式碼庫進行調查,並回傳保留或捨棄的結論(is_valid),同時給出類別與聚焦的論證。它列出哪些屬於真實問題(正確性、安全性、資料遺失、契約破壞、效能、可靠性),哪些屬於雜訊(過度設計、臆測、防禦性偏執、風格、已處理、判斷錯誤)。其指導原則是精確優先於召回,因此不確定的問題會被捨棄。
適用情境
適用於作為最終驗證關卡,對先前審查視角在某個拉取請求上提出的候選問題進行判定。它適合用來決定哪些被標記的發現值得呈現給作者,而不是重新審查 PR 或提出新問題。
執行需求
不需要指令碼或特殊工具,僅為說明性指示。它假定代理能夠讀取被標記的檔案以及實際程式碼庫中的相關程式碼。

Review validation criteria

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.

來源與署名

來源:PostHog/ai-plugin位於skills/review-hog-validation-criteria提交469d177

授權條款: 無授權條款

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