Borrowing it
Nothing to install: this file belongs to SylphxAI/coderag. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SylphxAI/coderag/main/.claude/commands/quality.mdgit clone --depth 1 https://github.com/SylphxAI/coderagWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/sylphxai/coderag/quality)<a href="https://agentmods.dev/commands/sylphxai/coderag/quality"><img src="https://agentmods.dev/badge/commands/sylphxai/coderag/quality/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/sylphxai/coderag/quality"><img src="https://agentmods.dev/badge/commands/sylphxai/coderag/quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00015 | $0.00869 |
| Opus 5.5 | $0.00006 | $0.00348 |
| Sonnet 5.5 | $0.00003 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
quality scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to quality — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quality Assurance
Maximize quality metrics: tests, coverage, performance, bundle size.
Scope
Testing:
- Fix failing tests
- Add missing tests (.test.ts for all modules)
- Improve coverage (critical paths 100%, business logic 80%+)
- Test edge cases
- Test error paths
- Integration tests
- E2E tests (if applicable)
Benchmarking:
- Add benchmarks (.bench.ts for critical functions)
- Measure performance
- Identify regressions
- Optimize slow operations
Performance:
- Profile hot paths
- Optimize algorithms (reduce complexity)
- Fix memory leaks
- Reduce allocations
- Cache expensive operations
- Lazy load where possible
Bundle Size:
- Analyze bundle composition
- Remove unused dependencies
- Tree-shake effectively
- Code split strategically
- Compress assets
- Use dynamic imports
Code Quality:
- Fix lint errors/warnings
- Improve type safety (no
any) - Reduce complexity
- Improve maintainability
- Follow code standards
Security:
- Fix vulnerabilities
- Update dependencies
- Validate inputs
- Sanitize outputs
- Secure defaults
Execution
1. Test Coverage
# Run tests with coverage
npm run test:coverage
# Identify gaps
# Add tests for uncovered code
# Focus on critical paths first
Priority:
- Critical business logic (100%)
- Error handling (100%)
- Edge cases (90%)
- Happy paths (100%)
- Integration points (80%)
2. Benchmarking
# Run benchmarks
npm run bench
# Compare against baseline
# Identify regressions
# Optimize bottlenecks
Add benchmarks for:
- Algorithm complexity (O(n) vs O(n²))
- Database queries
- API calls
- Data processing
- Rendering (if UI)
3. Performance Profiling
# Profile application
node --inspect ...
# Or use Clinic.js, 0x, etc.
# Identify bottlenecks
# Optimize hot paths
# Measure improvements
Check:
- CPU usage
- Memory usage
- I/O operations
- Network calls
- Rendering time
4. Bundle Analysis
# Analyze bundle
npm run build -- --analyze
# Check size
ls -lh dist/
# Identify large dependencies
# Remove unnecessary code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 183 lines · 15 tokens per session scan A ab8ea52deee4
quality is a command published in the GitHub repository SylphxAI/coderag (12 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 869 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to quality, differing in 0 lines, and is treated as a copy.
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