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 opendatahub-io/ai-helpers --skill aipcc-commit-suggestgit clone --depth 1 https://github.com/opendatahub-io/ai-helpersWrote 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/opendatahub-io/ai-helpers/aipcc-commit-suggest)<a href="https://agentmods.dev/skills/opendatahub-io/ai-helpers/aipcc-commit-suggest"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/aipcc-commit-suggest/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/opendatahub-io/ai-helpers/aipcc-commit-suggest"><img src="https://agentmods.dev/badge/skills/opendatahub-io/ai-helpers/aipcc-commit-suggest.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 | $0.00021 | $0.01495 |
| Opus 5 | $0.00010 | $0.00747 |
| Sonnet 5 | $0.00004 | $0.00299 |
| Haiku 4.5 | $0.00002 | $0.00150 |
Grade A, and why
aipcc-commit-suggest 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 10d 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Name
odh-ai-helpers:aipcc-commit-suggest
Synopsis
/aipcc:commit-suggest # Analyze staged changes
/aipcc:commit-suggest [N] # Analyze last N commits (1-100)
Description
AI-powered command that analyzes code changes and generates commit messages following the project's AIPCC format requirements.
Modes:
- Mode 1 (no argument) – Analyze staged changes (
git addrequired) - Mode 2 (with N) – Analyze last N commits to rewrite (N=1) or summarize for squash (N≥2)
Use cases:
- Create AIPCC-formatted commit messages
- Improve or rewrite existing commits to meet project standards
- Generate squash messages for MR merges
Difference from /git:summary – That command is read-only, while aipcc:commit-suggest generates actionable commit message suggestions for user review and manual use.
Implementation
The command operates in two modes based on input:
Mode 1 (no argument):
- Collect staged changes via
git diff --cached - Analyze file paths and code content to determine appropriate AIPCC ticket reference
- Generate 3 AIPCC-formatted commit message suggestions (Recommended, Standard, Minimal)
- Display formatted suggestions and prompt user for selection
- Ask: "Which suggestion would you like to use? (1/2/3 or skip)"
- Support responses:
1,use option 2,commit with option 3,skip - Execute
git commit -swith selected message if user requests (includes sign-off)
Mode 2 (with N):
- Retrieve last N commits using
git log - Parse commit messages and analyze changes to maintain AIPCC format consistency
- For N=1: Suggest improved rewrite following AIPCC format For N≥2: Merge commits into unified AIPCC-formatted squash message
- Generate 3 AIPCC-formatted commit message suggestions (Recommended, Standard, Minimal)
- Display formatted suggestions and prompt user for selection
- Ask: "Which suggestion would you like to use? (1/2/3 or skip)"
- Support responses:
1,use option 2,amend with option 3,skip - Execute
git commit --amend -s(N=1) or squash operation (N≥2) if user requests
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.
- 10d ago First seen · 173 lines · 21 tokens per session scan A 2e4e08bed527
aipcc-commit-suggest is a skill published in the GitHub repository opendatahub-io/ai-helpers (37 stars, last pushed 3d ago), licensed Apache-2.0. It adds 21 tokens to every session and 1,495 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 2026-08-30.
Other skills, from other repositories
git-advanced-workflows
Master advanced Git workflows including rebasing, cherry-picking, bisect, worktrees, and reflog to maintain clean history and recover from any situation. Use when managing complex Git histories, collaborating on feature branches, or troubleshooting repository issues.
workflow-patterns
Use this skill when implementing tasks according to Conductor's TDD workflow, handling phase checkpoints, managing git commits for tasks, or understanding the verification protocol.
block-no-verify-hook
Configure a PreToolUse hook to prevent AI agents from skipping git pre-commit hooks with --no-verify and other bypass flags. Use when setting up Claude Code projects that enforce commit quality gates.
chinese-commit-conventions
A Chinese-language guide to Conventional Commits, a format for writing consistent Git commit messages, plus related changelog, commit-checking, and commit-helper configuration.
work-unit-commits
Plan commits as reviewable work units. Trigger: implementation, commit splitting, chained PRs, or keeping tests and docs with code.
mcore-split-pr
Split a PR into multiple PRs to reduce the number of required CODEOWNERS reviewer groups.