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 skills/justomsharma/github-resume-assistant/testnpx skills add justomsharma/github-resume-assistant --skill testgit clone --depth 1 https://github.com/justomsharma/github-resume-assistantWhat 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 | $0.00040 | $0.00437 |
| Opus 5 | $0.00020 | $0.00218 |
| Sonnet 5 | $0.00008 | $0.00087 |
| Haiku 4.5 | $0.00004 | $0.00044 |
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 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
test
Add tests for the code from /implement and make the suite green. Follow
docs/TESTING.md.
Write tests
- Mirror
src/structure undertests/. - Mock all external APIs (GitHub, Anthropic). Never hit the network. No real keys required to run the suite.
- Use / extend fixtures in
conftest.py(fake profile, fake repos, sample resume). - Cover, per TESTING.md:
- Happy path for the new code.
- At least one edge case.
- The empty / near-empty GitHub case if this touches analysis or suggestions — this is our real user and must degrade gracefully.
Run
pytest --cov=src
- If tests fail, fix the code or the test (whichever is wrong) and re-run.
- If a failure reveals the approach was flawed, STOP and return to
/plan-first.
Bar to pass
- New code has happy-path + edge-case tests
- All external calls mocked; suite runs offline with no keys
- Empty-GitHub path tested (if relevant)
-
pytestgreen
Handoff — STOP and wait for the user
Once tests pass, STOP. Do NOT automatically proceed to /self-review,
/commit-push, /open-pr, /review-pr, or merge.
- Report what changed and the local test results, then say the changes are ready to test locally and ask the user to verify.
- Only continue to commit, push, open the MR/PR, review it, or merge when the user explicitly tells you to (e.g. "commit and push", "raise the MR").
- Until that explicit go-ahead, keep all changes local and uncommitted.
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 · 49 lines · 40 tokens per session scan A 2f56d9d71c53
test is a skill published in the GitHub repository justomsharma/github-resume-assistant (0 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 437 once invoked, about $0.0002 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.
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