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/sneg55/agent-starter/commitnpx skills add sneg55/agent-starter --skill commitgit clone --depth 1 https://github.com/sneg55/agent-starterWhat 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 | $0.00035 | $0.00479 |
| Opus 5 | $0.00017 | $0.00239 |
| Sonnet 5 | $0.00007 | $0.00096 |
| Haiku 4.5 | $0.00003 | $0.00048 |
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 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
Git Commit
Context
Gather this context before committing:
- Current git status:
git status - Current git diff (staged and unstaged):
git diff HEAD - Current branch:
git branch --show-current - Recent commits:
git log --oneline -10
Git Safety Protocol
- NEVER update the git config
- NEVER skip hooks (--no-verify, --no-gpg-sign, etc) unless the user explicitly requests it
- CRITICAL: ALWAYS create NEW commits. NEVER use git commit --amend, unless the user explicitly requests it
- Do not commit files that likely contain secrets (.env, credentials.json, etc). Warn the user if they specifically request to commit those files
- If there are no changes to commit (i.e., no untracked files and no modifications), do not create an empty commit
- Never use git commands with the -i flag (like git rebase -i or git add -i) since they require interactive input which is not supported
Task
Based on the changes, create a single git commit:
-
Analyze all staged changes and draft a commit message:
- Look at the recent commits to follow this repository's commit message style
- Summarize the nature of the changes (new feature, enhancement, bug fix, refactoring, test, docs, etc.)
- Ensure the message accurately reflects the changes and their purpose (i.e. "add" means a wholly new feature, "update" means an enhancement to an existing feature, "fix" means a bug fix, etc.)
- Draft a concise (1-2 sentences) commit message that focuses on the "why" rather than the "what"
-
Stage relevant files and create the commit using HEREDOC syntax:
git commit -m "$(cat <<'EOF'
Commit message here.
EOF
)"
Stage and create the commit in a single message. Do not do anything else.
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 · 35 tokens per session scan A 55cb2073d47b
commit is a skill published in the GitHub repository sneg55/agent-starter (76 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 479 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 2026-08-30.
Other skills, from other repositories
dummy-dataset
Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data for development and demos.
outcome-roadmap
Transform an output-focused roadmap into an outcome-focused one that communicates strategic intent. Rewrites initiatives as outcome statements reflecting user and business impacts. Use when shifting to outcome roadmaps, making a roadmap more strategic, or rewriting feature lists as outcomes.
release-notes
Generate user-facing release notes from tickets, PRDs, or changelogs. Creates clear, engaging summaries organized by category (new features, improvements, fixes). Use when writing release notes, creating changelogs, announcing product updates, or summarizing what shipped.
retro
Facilitate a structured sprint retrospective — what went well, what didn't, and prioritized action items with owners and deadlines. Use when running a retrospective, reflecting on a sprint, creating action items from team feedback, or learning how to run effective retros.
shipping-artifacts
The durable documentation set that makes an AI-built (vibe-coded) app reviewable before shipping. A small core every app needs — architecture, user/permission flows, permissions, variables/secrets, and a test-coverage map — plus conditional docs added only when they apply: emails, scheduled work, SEO, and embedded…
ideal-customer-profile
Identify the Ideal Customer Profile (ICP) from research data with demographics, behaviors, JTBD, and needs. Use when defining your ICP, analyzing PMF survey data, or understanding who your best customers are.