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Contextual code review
Traces a change through callers, guards and data transformations to distinguish real regressions from unrelated existing issues.
contextual-code-review
Team members using this skill
When is it useful?
Use when a small diff affects shared contracts, state transitions or high-risk data.
What does it help you do?
- Checks existing upstream validation before reporting a supposedly missing guard.
- Follows input through domain rules, persistence and serialization.
- Focuses findings on introduced or worsened defects with concrete consequences.
Try asking this
Review this response-shape change through all callers and serializers, identifying only actionable compatibility failures caused by the change. Trace a nullable field into an older client's renderer. Report a failure only when the changed response can reach that consumer without an existing guard.
Detailed documentation
Read the skill’s original instructions, examples and checks in their authored language.
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Contextual Code Review
Reading only the green and red lines of a diff misses the most dangerous bugs. A change is safe only in the context of its callers, dependencies, data contracts, and runtime environment (Michael Feathers & Michael Fagan).
Thinking Sequence for Every Review
- What must this change achieve?
- What is the accepted scope and expected behavior?
- Where does the code implement it?
- What happens on the main path, error paths, and boundary cases?
- What does it alter in existing system behavior?
- Which claims are backed by real checks?
- Is there a concrete, actionable defect that requires a fix?
Workflow
- Expand context beyond the modified lines:
- Inspect all callers of any modified function, hook, component, or endpoint to verify their assumptions about arguments, return values, nullability, and thrown errors still hold.
- Inspect all callees and existing guards (upstream middleware, schema validators, database constraints, transactions) before claiming a check is missing.
- Trace control flow and data transformations end to end:
- Follow data from entry point (HTTP request, CLI arg, UI event, queue payload) through validation, domain logic, persistence, and response serialization.
- Check for off-by-one errors, inverted boolean conditions, unhandled
null/undefined, mutated shared references, unawaited promises, and resource leaks.
- Separate new regressions from pre-existing technical debt:
- Introduced or worsened by this change: In scope for blocking or targeted review findings.
- Pre-existing issue in untouched code: Only flag if the current change directly triggers or amplifies it, and explicitly label it as pre-existing rather than blaming the diff.
- Calibrate review depth to risk:
- Spend deep analytical effort on state transitions, permissions, financial/usage math, migrations, and public contracts; never pad a review with subjective naming or formatting nitpicks.
Included files 1
SKILL.md