Borrowing it
Nothing to install: this file belongs to hlalljie/agent-workflow-presets. 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/hlalljie/agent-workflow-presets/main/.cursor/skills/commit/SKILL.mdgit clone --depth 1 https://github.com/hlalljie/agent-workflow-presetsWrote 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/hlalljie/agent-workflow-presets/commit)<a href="https://agentmods.dev/skills/hlalljie/agent-workflow-presets/commit"><img src="https://agentmods.dev/badge/skills/hlalljie/agent-workflow-presets/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/hlalljie/agent-workflow-presets/commit"><img src="https://agentmods.dev/badge/skills/hlalljie/agent-workflow-presets/commit.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00029 | $0.01838 |
| Opus 5.5 | $0.00012 | $0.00735 |
| Sonnet 5.5 | $0.00006 | $0.00368 |
| Haiku 4.5 | $0.00003 | $0.00184 |
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 19d 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Commit
Process
- Run
git diff --stagedandgit status(if nothing staged, note unstaged changes). - Security review — no secrets, credentials, or env files staged; sensitive paths ignored.
- Loose ends — only if something needs a follow-up. If there are none, omit this (do not write "none", do not explain what you are not doing).
3b. Upgrade notes — only if
UPGRADING.mdexists at the repo root and the change touches harness files it names: follow its "How this file works" section. Most changes need no entry: say "no entry needed" and nothing more. Include a proposed entry, and the file, only when a project must act by hand. Skip silently in any other repo. - Propose — commit message, files to stage,
Ready to commit (y/n):, stop. Before printing, check the subject matchestype(scope)?!?: subject(see "Commit message format"); fix it if not. Do not rungit addorgit commit. - Wait for explicit approval.
- Only then run
git addandgit commit.
Starting vs approving
/commit, "prepare a commit", "go ahead and /commit", "run the commit skill" mean: run steps 1–4 (including the full proposed commit message and files to stage), printReady to commit (y/n):, then stop. That is not permission to rungit commityet.- Approval is a separate message after that proposal: e.g.
y, "yes", "approved", or a short edit ("use that message" / tweak subject only). Never treat "go ahead" in the same message as/commitas approval to commit unseen. - The user must be able to read the proposed subject and body before approving.
Proposal output: short and scannable. If this commit finishes the last open task for a plan phase: state that clearly in the proposal to the user and in the commit message (subject or bullet); mark that phase complete in plan.md (heading and Completed: date, per workflow.mdc) in the same commit as the task checkboxes. Make this edit before printing the proposal, so the user approves what will be committed. If it does not complete a phase, say nothing about phases — do not list non-events.
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.
- 19d ago Changed · +15 lines 6b2cb2265ee7
- 22d ago Changed · +2 lines 73b6835f4c00
- 1mo ago First seen · 70 lines · 29 tokens per session scan A 76205f88016a
commit is a skill published in the GitHub repository hlalljie/agent-workflow-presets (2 stars, last pushed 20d ago), licensed MIT. It adds 29 tokens to every session and 1,838 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 2026-08-31.
Other skills, from other repositories
cast-ship
Take finished work through to merge. Commits in topical pieces, opens the pull request with a description that links the session, then binds this session to the pull request so review comments, failing checks and a stale branch wake it until the merge lands. Use when asked to ship, open a PR, or handle review…
to-stack
Split a large branch or PR into a stack of small PRs, verified layer by layer, and open them as linked drafts.
commit-changes-main
Commit directly on main/master when explicitly allowed.
commit-same-branch
Commit on the current branch with conventional message.
commit
Commit on a new branch with conventional message.
llm-gate
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.