Claude-night-market bug-review

Bug hunting with evidence trails: find defects, document them, and verify fixes

install
source · Clone the upstream repo
git clone https://github.com/athola/claude-night-market
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/athola/claude-night-market "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/pensive/skills/bug-review" ~/.claude/skills/athola-claude-night-market-bug-review && rm -rf "$T"
manifest: plugins/pensive/skills/bug-review/SKILL.md
source content

Table of Contents

Bug Review Workflow

Systematic bug identification and fixing with language-specific expertise.

Quick Start

/bug-review

Verification: Run the command with

--help
flag to verify availability.

When To Use

  • Reviewing code for potential bugs
  • After receiving bug reports
  • Before major releases
  • During security audits
  • Investigating production issues

When NOT To Use

  • Test coverage audit - use test-review instead

Required TodoWrite Items

  1. bug-review:language-detected
  2. bug-review:repro-plan
  3. bug-review:defects-documented
  4. bug-review:fixes-prepared
  5. bug-review:verification-plan

Progressive Loading

Load additional context as needed:

  • Language Detection:
    @include modules/language-detection.md
    - Manifest heuristics, expertise framing, version constraints
  • Defect Documentation:
    @include modules/defect-documentation.md
    - Severity classification, root cause analysis, static analyzers
  • Fix Preparation:
    @include modules/fix-preparation.md
    - Minimal patches, idiomatic patterns, test coverage

Workflow

Step 1: Detect Languages (
bug-review:language-detected
)

Identify dominant languages using manifest files (Cargo.toml → Rust, package.json → Node, etc.).

State expertise persona appropriate for the language ecosystem.

Note version constraints (MSRV, Python versions, Node engines).

Progressive: Load

modules/language-detection.md
for detailed manifest heuristics.

Step 2: Plan Reproduction (
bug-review:repro-plan
)

Identify reproduction methods:

  • Unit/integration test suites
  • Fuzzing tools
  • Manual reproduction commands

Document exact commands:

cargo test -p core
pytest tests/test_api.py
npm test -- pkg

Verification: Run

pytest -v tests/test_api.py
to verify.

Capture blockers and propose mocks when dependencies unavailable.

Step 3: Document Defects (
bug-review:defects-documented
)

Review code line-by-line, logging each bug with:

  • File:line reference: Precise location
  • Severity: Critical, High, Medium, Low
  • Root cause: Logic error, API misuse, concurrency, resource leak
  • Impact: What breaks and how

Run static analyzers (

cargo clippy
,
ruff check
,
golangci-lint
,
eslint
).

Use

imbue:proof-of-work
for reproducible capture.

Progressive: Load

modules/defect-documentation.md
for classification details and analyzer commands.

Step 4: Prepare Fixes (
bug-review:fixes-prepared
)

Draft minimal, idiomatic patches using language best practices:

  • Guard clauses (Rust: pattern matching, Python: early returns)
  • Resource cleanup (Go: defer, Python: context managers)
  • Error propagation (Rust: ?, Go: wrapped errors)

Create tests following Red → Green pattern:

  1. Write failing test
  2. Apply minimal fix
  3. Verify test passes

Progressive: Load

modules/fix-preparation.md
for language-specific patterns and test strategies.

Step 5: Verification Plan (
bug-review:verification-plan
)

Execute reproduction steps with fixes applied.

Capture evidence:

  • Test output logs
  • Benchmark comparisons
  • Coverage reports

Document remaining risks using

imbue:diff-analysis/modules/risk-assessment-framework
.

Assign owners and deadlines for follow-up items.

Defect Classification (Condensed)

Severity: Critical (crash/data loss) → High (broken features) → Medium (degraded UX) → Low (edge cases)

Root Causes: Logic errors | API misuse | Concurrency issues | Resource leaks | Validation gaps

Output Format

## Summary
[Brief scope description]

## Defects Found
### [D1] file.rs:142 - Title
- Severity: High
- Root Cause: Logic error
- Impact: Data corruption possible
- Fix: [description]

## Proposed Fixes
### Fix for D1
[code diff with explanation]

## Test Updates
[new/updated tests with Red → Green verification]

## Evidence
- Commands executed
- Logs and outputs
- External references

Verification: Run

pytest -v
to verify tests pass.

Best Practices

  1. Evidence-based: Every finding has file:line reference
  2. Reproducible: Clear steps to reproduce each bug
  3. Minimal fixes: Smallest change that fixes the issue
  4. Test coverage: Every fix has corresponding test
  5. Risk awareness: Document remaining risks with severity scoring

Exit Criteria

  • All defects documented with precise references
  • Fixes prepared with test coverage verified
  • Verification plan includes commands and expected outputs
  • Remaining risks assessed and owners assigned