Code Review

Code Review

Iron Law

FINDINGS FIRST. BLOCK ON CORRECTNESS, SAFETY, DATA LOSS, AND UNPROVEN CLAIMS.

When to Use

• Self-review of your own implementation diff in the workflow completion loop before invoking proof or claiming done. Default for any non-trivial agent-generated change; a second pass by the same agent reliably surfaces bugs, dead code, and missed edge cases the implementation pass overlooks.
• Diff review (local, branch, or GitHub PR via gh).
• Review-comment follow-up on the user's own PRs.
• Agent-generated code review before merge or handoff.

When NOT to Use

• Commit grouping or git history repair only; use git-workflow.
• A narrow domain-only review where a specialist skill is sufficient (security, database, api, accessibility).

Core Ideas

1. Review owns defect discovery, not proof execution. It should find behavioral bugs, regressions, unsafe edge cases, missing evidence, and merge blockers; proof owns turning claims into checks.
2. Findings first. Summaries, compliments, and change descriptions come after concrete issues ordered by severity.
3. Every review includes a security pass and a proof-evidence pass. If the review cannot verify a claim, report it as unproven.
4. Repository constraints beat generic advice. Check declared runtime, framework, dependency, CI, and support-policy constraints before using a language reference.
5. Maintainability findings need a concrete risk: hidden state, coupled effects, stale flags, duplicated rules, dead compatibility, unreachable paths, or behavior split across unrelated lifecycles.
6. Review protects the human's mental model. Generated code that is too large, vague, or disconnected from the stated intent is comprehension debt even when it appears to work.

Review Lenses

• Security: auth/authz, secrets, trust boundaries, input handling, dependencies, crypto, unsafe sinks, redaction, and error/log disclosure.
• Behavior: changed return values, effects, ordering, error shape, concurrency, persistence, migrations, UI states, and compatibility.
• Evidence: tests, CI, build output, root-cause evidence, proof contracts, and claims marked unproven.
• Dead surface: unused exports, old routes, stale flags, orphaned jobs, removed files still referenced, and duplicated rules with divergent meaning.
• Reuse & composition: duplicated logic with shared meaning and rules, inheritance where composition fits, deep inheritance chains, parallel implementations of existing behavior, and second wrappers for cross-cutting concerns already covered.
• Build-vs-adopt: hand-rolled HTTP clients, ORMs/query builders, parsers, retry/backoff loops, validators, serializers, format builders, date/time math, schedulers, templating, crypto, and migration runners.
• AI-generated risk: speculative abstraction, unnecessary compatibility shims, dead defensive code, test theater, fabricated APIs, scope creep, refactor drift, and comprehension debt.

Workflow

1. Resolve the target. Use local diffs or approved GitHub reads. For PR review threads, fetch thread state only when resolution or line context matters. Never run gh without explicit permission.
2. Pre-flight the review. Identify intent, impact, CI status, and changed surface. Missing PR intent on a non-trivial diff is a finding. Red or absent CI means the review is unproven, not blocked from inspection.
3. Bound the scope. For oversized generated or durable diffs, declare the partial review scope and make split/scope a finding when the human cannot review it in one sitting.
4. Load only needed references. Load language guides for languages in the diff and domain skills for touched risks. Use release only for concrete release artifacts, rollout obligations, or explicit release-readiness review.
5. Sweep by risk. Apply the Review Lenses, including the AI-generated risk pass for agent-written code. Sample generated, vendored, and lockfile churn only enough to detect obvious risk.
6. Write findings first. Report concrete issues in severity order with file/line or thread anchors. If no issues are found, name residual risk and unreviewed scope.

Addressing Review Feedback

• Modify a PR only when it belongs to the user or the user explicitly asks.
• Separate actionable requested changes from discussion, approvals, duplicates, resolved threads, and outdated threads.
• Cluster comments by behavior or file and fix the smallest coherent set.
• Draft a reply when the reviewer asks for explanation rather than code.
• Ask before GitHub writes: comments, reviews, thread resolution, pushes, and similar externally visible actions.
• Surface conflicting comments or behavior regressions before editing.

Finding Format

Each finding includes: file/line or PR thread anchor, issue, impact, concrete fix direction, and evidence or missing proof. Use questions only when ambiguity blocks the finding or fix.

Verification

• The review target, intent, CI/proof status, and scope of the review are explicit.
• Runtime/toolchain constraints and relevant language references informed the advice.
• Security, behavior, evidence, dead-surface, reuse-&-composition, build-vs-adopt, maintainability, and AI-generated risk lenses were applied where relevant.
• Findings are severity ordered, anchored, concrete, and focused on impact.
• Missing evidence, residual risk, and unreviewed scope are named.
• GitHub commands and writes had explicit permission.

Tripwires

Use these when the shortcut thought appears:

• Passing tests prove only what they assert; still review safety, data, and dead-surface risk.
• Style is not blocking unless it hides ambiguity, behavior risk, or unsafe control flow.
• Fewer files is simpler only when behavior, data, effects, and lifecycles stay uncoupled.
• Compatibility shims need owner, caller, removal condition, and proof.
• Trusting the author changes how you write findings, not how thoroughly you review.
• Test theater is a finding; load proof for the detailed taxonomy.
• Speculative abstraction waits for a real caller or requirement.
• Dead defensive code should become a boundary assertion or be removed.
• A refactor with observable behavior change is a feature change.
• Bundled reformatting or unrelated edits should be split before deep review.
• Oversized durable generated code is comprehension debt.

Handoffs

• specify: plan-to-code divergence from an agreed design artifact.
• security: auth, trust boundaries, secrets, crypto, dependencies, injection.
• database: migrations, locking, transactions, schema, indexes, data access.
• release: version, changelog, package, publish, rollout, or migration release-readiness review.
• proof: missing behavior coverage, test quality, mocks, flakes, and proof obligations.
• git-workflow: branch mechanics and packaging accepted fixes.

References

• Language-specific reviewer guides: references/rust.md, references/fsharp.md, references/csharp.md, references/python.md, references/typescript.md, references/ruby.md, references/java.md, references/kotlin.md, references/bash.md, references/sql.md.

Source: kreek/agent-booster-pack — distributed by TomeVault.