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.
git clone --depth 1 https://github.com/Sagargupta16/claude-skillsWrote 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/sagargupta16/claude-skills/test)<a href="https://agentmods.dev/commands/sagargupta16/claude-skills/test"><img src="https://agentmods.dev/badge/commands/sagargupta16/claude-skills/test.svg" alt="Measured on agentmods" 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 | $0.00010 | $0.00318 |
| Opus 5 | $0.00005 | $0.00159 |
| Sonnet 5 | $0.00002 | $0.00064 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
test 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 2d 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.
What it actually says
Live state
- Detection: !
ls -1 package.json pyproject.toml pytest.ini setup.cfg Cargo.toml go.mod Makefile 2>/dev/null - package.json scripts: !
jq -r '.scripts // {} | to_entries | map("\(.key): \(.value)") | .[]' package.json 2>/dev/null | head -10 || echo "no package.json"
Task
Using the detection above, run the project's test suite.
Framework mapping:
package.jsonwithscripts.test->pnpm test(preferred), elsenpm testoryarn testpytest.ini/pyproject.toml [tool.pytest]/setup.cfg->pytest -v(oruv run pytest -vifuv.lockexists)Cargo.toml->cargo testgo.mod->go test ./...Makefilewithtest:target ->make test
If tests fail:
- Parse the failing test name and root-cause line.
- Show the specific assertion or error message.
- Classify: is the failure in code we just changed, or pre-existing?
- Suggest a minimal fix. Do not auto-fix unless the user asked.
Report: X passed, Y failed, Z skipped and whether failures are new or pre-existing.
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.
- 2d ago Changed aaeaaee0f49d
- 8d ago First seen · 29 lines · 10 tokens per session scan A def6c1662ef5
test is a command published in the GitHub repository Sagargupta16/claude-skills (5 stars, last pushed 2d ago), licensed MIT. It adds 10 tokens to every session and 318 once invoked, about $0.0001 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
verify
Run the repo's verification loop on the current change and report real output - stage 4A of the SDLC loop.
commit
Create a git commit with intelligent message drafting (-f for fast, -v for verbose).
review-arch
Review app architecture: components, data flows, risks, and prioritized improvements.
ijfw-audit
Run the IJFW audit gate for the current workflow phase. Usage: /ijfw-audit [phase name].
complete
Complete a partially implemented feature by filling gaps and ensuring production readiness.
ng-red-team
Portable command prompt generated from skills/stress-testing-agent-changes/SKILL.md. Edit the skill, then run python tools/ng.py gen-commands; do not edit this file by hand.