Borrowing it
Nothing to install: this file belongs to rossoctl/examples. 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/rossoctl/examples/main/.claude/skills/orchestrate:precommit/SKILL.mdgit clone --depth 1 https://github.com/rossoctl/examplesWrote 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/rossoctl/examples/orchestrate-precommit)<a href="https://agentmods.dev/skills/rossoctl/examples/orchestrate-precommit"><img src="https://agentmods.dev/badge/skills/rossoctl/examples/orchestrate-precommit/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/rossoctl/examples/orchestrate-precommit"><img src="https://agentmods.dev/badge/skills/rossoctl/examples/orchestrate-precommit.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 | $0.00032 | $0.01364 |
| Opus 5.5 | $0.00013 | $0.00546 |
| Sonnet 5.5 | $0.00006 | $0.00273 |
| Haiku 4.5 | $0.00003 | $0.00136 |
Grade A, and why
orchestrate:precommit 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.
How it starts
The opening of the file, as written. The whole thing — 220 lines — stays where its author put it; the contents beside it link to each section on GitHub.
flowchart TD
START(["/orchestrate:precommit"]) --> DETECT["Detect language"]:::orch
DETECT --> PRECOMMIT["Generate .pre-commit-config.yaml"]:::orch
PRECOMMIT --> LINT["Generate lint config"]:::orch
LINT --> MAKEFILE["Add Makefile targets"]:::orch
MAKEFILE --> CLAUDE_MD["Create CLAUDE.md"]:::orch
CLAUDE_MD --> SETTINGS["Create .claude/settings.json"]:::orch
SETTINGS --> BRANCH["Create branch"]:::orch
BRANCH --> SIZE{Under 700 lines?}
SIZE -->|Yes| PR["Commit + open PR"]:::orch
SIZE -->|No| SPLIT["Split into sub-PRs"]:::orch
SPLIT --> PR
PR --> DONE([Phase complete])
classDef orch fill:#FF9800,stroke:#333,color:white
Follow this diagram as the workflow.
Orchestrate: Pre-commit
Establish the code quality baseline for a target repo. This is Phase 2 and produces PR #1 — the foundation that validates all subsequent PRs.
When to Use
- After
orchestrate:planidentifies precommit as a needed phase - Always the first PR-producing phase
Prerequisites
- Plan exists at
/tmp/rossoctl/orchestrate/<target>/plan.md - Target repo cloned in
.repos/<target>/
Step 1: Detect Language
Use the scan report or check directly:
ls .repos/<target>/go.mod .repos/<target>/pyproject.toml .repos/<target>/package.json .repos/<target>/requirements.yml 2>/dev/null
Step 2: Generate Pre-commit Config
Create .pre-commit-config.yaml with language-appropriate hooks.
Python hooks
ruff— lint + formattrailing-whitespace,end-of-file-fixer,check-yamlcheck-added-large-files
Go hooks
golangci-lintgofmt,govettrailing-whitespace,end-of-file-fixer
Node hooks
eslint,prettiertrailing-whitespace,end-of-file-fixer
Ansible hooks
ansible-lint,yamllinttrailing-whitespace,end-of-file-fixer
Step 3: Generate Lint Config
Python (pyproject.toml)
[tool.ruff]
line-length = 120
target-version = "py311"
[tool.ruff.lint]
select = ["E", "F", "I", "W"]
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 · 220 lines · 32 tokens per session scan A 8504a9d9f6f8
orchestrate:precommit is a skill published in the GitHub repository rossoctl/examples (11 stars, last pushed yesterday), licensed Apache-2.0. It adds 32 tokens to every session and 1,364 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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