QC Gate - Parallel Quality Control

VerifiedSafe

Automated quality control system with 5 parallel agents reviewing code changes. All agents must pass to approve modifications.

Sby Skills Guide Bot
DevelopmentAdvanced
306/2/2026
Claude Code
#code-review#quality-gate#parallel-agents#automated-review

Recommended for

Our review

Runs a multi-agent quality gate that performs code review, simplification, consistency, robustness, and scope checks on a Git diff.

Strengths

  • Comprehensive multi-faceted review in parallel
  • Fast execution due to parallel spawning
  • Enforces consistency with existing codebase patterns
  • Automates quality checks before committing

Limitations

  • Requires a Git diff against the main branch
  • May produce false positives needing manual review
  • Costly due to multiple model calls (5 agents)
When to use it

Use before committing or merging to ensure changes meet code quality standards.

When not to use it

Do not use for exploratory code or early drafts where strict quality criteria are not yet appropriate.

Security analysis

Safe
Quality score90/100

The skill only uses read-only git commands (git diff, git diff --name-only) and read operations to gather context; it spawns AI agents for code review without any destructive, exfiltrating, or obfuscated actions.

No concerns found

Examples

Full quality gate on current diff
Run quality gate on the current changes against main branch.
With task description
Execute /qc with task description 'Add user authentication' and include pattern files from the same directory.
Re-run on failing gate
/qc - the last review failed on robustness, please run again after fixing the edge case.

name: qc description: Quality gate. 5 parallel agents review changes. All must pass. allowed-tools: Task, Bash, Read, Grep, Glob

QC Gate

Setup

DIFF=$(git diff main)
FILES=$(git diff main --name-only)
TASK="{task description or 'general changes'}"

Read 1-2 unmodified files from same directories for pattern context.

Agents

Spawn all 5 in parallel. All output raw JSON only, no markdown.

1: Code Review (sonnet)

DIFF: ${DIFF}

- Descriptive naming?
- Errors caught with useful messages?
- No hardcoded values, commented code, debug statements?
- No TODO without ticket ref?
- No obvious bugs?
- No useless comments?

{"pass": bool, "issues": [...]}

2: Simplification (sonnet)

DIFF: ${DIFF}

- Is this overcomplicated? Can I solve the same problem in a simpler manner?
- Can I reduce indirection?
- Can I reduce surface area?
- Premature abstraction? Premature Optimization? YAGNI violations?
- Dead code?
- Three similar lines > one abstraction

{"pass": bool, "issues": [...]}

3: Consistency (sonnet)

DIFF: ${DIFF}
PATTERNS: ${PATTERN_FILES}

- Matches existing codebase patterns?
- Proper types, no any, no unsafe casts?
- Idiomatic error handling?
- Changes internally consistent?
- Is logic isolated and composable?
- Are there existing tests if neccesary?

{"pass": bool, "issues": [...]}

4: Robustness (sonnet)

TASK: ${TASK}
DIFF: ${DIFF}

- Actually solves the problem?
- Edge cases: empty, null, zero, negative, boundaries, concurrency?
- Regression risk: changed signatures, shared state, removed exports?
- Maintains API contracts?

{"pass": bool, "issues": [...]}

5: Scope (haiku)

TASK: ${TASK}
FILES: ${FILES}
DIFF: ${DIFF}

- Solved the problem or just the symptom?
- Changes unrelated to task?
- Unnecessary refactoring?

{"pass": bool, "issues": [...]}

Results

| Check | Verdict | Issues | |-------|---------|--------| | Code Review | ✓/✗ | ... | | Simplification | ✓/✗ | ... | | Consistency | ✓/✗ | ... | | Robustness | ✓/✗ | ... | | Scope | ✓/✗ | ... |

ALL PASS: Ready to commit.

ANY FAIL: List issues, fix them, run /qc again.

Same issue 3x: Escalate to user.

Notes

  • Invalid JSON? Retry once. Still broken? Mark fail.
  • Large diffs (>500 lines): run simplification file-by-file.
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