Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/cyperx84/claude-code-plugin-examples/coveragegit clone --depth 1 https://github.com/cyperx84/claude-code-plugin-examplesWhat 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 | $0.00006 | $0.00399 |
| Opus 5 | $0.00003 | $0.00199 |
| Sonnet 5 | $0.00001 | $0.00080 |
| Haiku 4.5 | $0.00001 | $0.00040 |
Grade A, and why
coverage 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 yesterday.
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.
What it actually says
Coverage Analysis
Analyze test coverage and identify gaps for: $ARGUMENTS (or entire project if not specified)
Process:
-
Run coverage analysis:
- Execute tests with coverage enabled
- Generate detailed coverage report
- Identify uncovered code paths
-
Coverage breakdown:
- Overall coverage percentage
- Per-file coverage
- Per-function coverage
- Branch coverage analysis
-
Identify gaps:
- List uncovered functions
- Show uncovered lines with context
- Highlight critical paths without tests
- Find edge cases not tested
-
Prioritize:
- Critical paths (authentication, payment, etc.)
- Complex functions (high cyclomatic complexity)
- Recently changed code
- Public API functions
-
Recommendations:
- Suggest which files/functions to test first
- Offer to generate tests using /agent test-generator
- Estimate effort to reach coverage goals
Example output:
Coverage Analysis for src/utils/
Overall: 78.4%
High Priority (Critical paths):
❗ src/utils/auth.ts: 45.2% - CRITICAL
├─ validateToken(): 0% coverage
└─ refreshToken(): 0% coverage
Medium Priority (Complex logic):
⚠️ src/utils/parser.ts: 67.8%
├─ parseComplexQuery(): 30% coverage
└─ handleEdgeCases(): 45% coverage
Low Priority:
✓ src/utils/format.ts: 92.1%
✓ src/utils/string.ts: 95.3%
Recommendation:
1. Test auth.ts functions (HIGH PRIORITY)
2. Add edge case tests for parser.ts
3. Target 85% overall coverage (+6.6%)
Generate tests? (y/n)
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.
- yesterday First seen · 67 lines · 6 tokens per session scan A c602c3960bb1
coverage is a command published in the GitHub repository cyperx84/claude-code-plugin-examples (2 stars, last pushed 10mo ago), licensed MIT. It adds 6 tokens to every session and 399 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.