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 skills add SteveGJones/ai-first-sdlc-practices --skill commitgit clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practicesWrote 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/skills/stevegjones/ai-first-sdlc-practices/commit)<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/commit"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/commit/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/skills/stevegjones/ai-first-sdlc-practices/commit"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/commit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00018 | $0.00401 |
| Opus 5.5 | $0.00007 | $0.00160 |
| Sonnet 5.5 | $0.00004 | $0.00080 |
| Haiku 4.5 | $0.00002 | $0.00040 |
Grade A, and why
commit 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.
What it actually says
Validated Commit
Run quick validation, then commit if clean.
Steps
- Run quick validation
/sdlc-core:validate --quick
- Run tests and smoke test (if application code was changed)
# Run test suite if configured
pytest --tb=short -q 2>/dev/null || echo "No pytest configured"
# Smoke test: verify the app's main module imports cleanly
python -c "import app" 2>/dev/null || python -c "import main" 2>/dev/null || echo "No app module found"
If tests fail or the app cannot import, stop. Fix the issue before committing. Static analysis passing does not mean the code works.
-
If validation or tests fail, report the issues and stop. Do NOT commit.
-
If all checks pass, proceed:
- Review all changed files with
git statusandgit diff - Stage the relevant files (prefer specific files over
git add -A) - If
$ARGUMENTSis provided, use it as the commit message - If no message provided, draft a concise commit message based on the changes
- Use conventional commit format:
feat:,fix:,docs:,refactor:,test:,chore:
- Review all changed files with
-
Commit using a heredoc for proper formatting:
git commit -m "$(cat <<'EOF'
<type>: <description>
<optional body>
Co-Authored-By: Claude <[email protected]>
EOF
)"
- Run git status after commit to verify success.
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 · 55 lines · 18 tokens per session scan A 11db000b9fd7
commit is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 15d ago), licensed MIT. It adds 18 tokens to every session and 401 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
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