Borrowing it
Nothing to install: this file belongs to strikersam/autonomous-ai-agency. 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/strikersam/autonomous-ai-agency/master/.agents/skills/smart-commit/SKILL.mdgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote 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/strikersam/autonomous-ai-agency/smart-commit)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/smart-commit"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/smart-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/strikersam/autonomous-ai-agency/smart-commit"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/smart-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 | $0.00034 | $0.00787 |
| Opus 5 | $0.00017 | $0.00394 |
| Sonnet 5 | $0.00007 | $0.00157 |
| Haiku 4.5 | $0.00003 | $0.00079 |
Grade A, and why
smart-commit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: smart-commit
When to Use
Use this skill every time you are ready to commit code. It replaces ad-hoc
git add && git commit with a structured quality gate sequence.
Instructions
Step 1 — Confirm changelog is updated
git diff docs/changelog.md
If the diff is empty and this is a code change (not chore/test/docs), update
docs/changelog.md under ## [Unreleased] before continuing.
Step 2 — Run tests
pytest -x
Block on failure. Do not commit with failing tests. Fix the failure first.
Step 3 — Check for obvious issues
# Syntax check staged Python files
git diff --staged --name-only | grep '\.py$' | xargs python -m py_compile
# Confirm no secrets in staged files
git diff --staged | grep -iE '(SECRET_KEY\s*=\s*["\x27][^"\x27]{8}|password\s*=\s*["\x27][^"\x27]{4}|api_key\s*=\s*["\x27]sk-)'
If any secrets are detected: stop immediately, do not commit.
Step 4 — Stage your changes
git status # review what changed
git diff --staged # confirm what's staged
git add <specific files> # stage by name, not -A
Step 5 — Write a conventional commit message
Format: <type>(<scope>): <short description>
| Type | When to Use |
|---|---|
feat |
New feature visible to users |
fix |
Bug fix |
refactor |
Code change with no behaviour change |
test |
Adding or updating tests |
docs |
Documentation only |
chore |
Tooling, config, dependencies |
ci |
CI/CD changes |
style |
Formatting, whitespace (no logic change) |
perf |
Performance improvement |
security |
Security fix or hardening |
Examples:
feat(router): add task classification for long-context requests
fix(auth): reject tokens with empty bearer string
refactor(agent): extract planner prompt into prompts.py
security(key_store): hash keys before comparison
Step 6 — Commit
git commit -m "$(cat <<'EOF'
feat(scope): description here
- Additional context if needed
- Reference issue if applicable
https://claude.ai/code/session_<id>
EOF
)"
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.
- 9d ago First seen · 122 lines · 34 tokens per session scan A ac0502d8ab74
smart-commit is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 787 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.
Other skills, from other repositories
git-integration
Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.
audit-trail
Full traceability from PRD to code commit through the CCPM spec-driven pipeline.
strict-tdd
Strict RED->GREEN->REFACTOR test-driven development with enforcement. Never write production code before a failing test. Atomic commits per TDD cycle.
checkpoint-management
Git-backed state management for safe rollback. Create and restore checkpoints with tagged commits and metadata tracking.
issue-tracking
Track beads as git-backed issues with persistent attribution, supporting Gas Town's bead lifecycle and convoy progress monitoring.
merge-queue
Process the Refinery merge queue - collect agent work, detect and resolve conflicts, merge in dependency order, and verify integration.