skillsaw: Skill for Claude Code

.agents/skills/skillsaw-onboard/SKILL.md

skillsaw-onboard is a skill for Claude Code from stbenjam/skillsaw. It costs 55 tokens per session (1,514 once invoked), scanned A, original, Apache-2.0.

A guided setup process for adding skillsaw, a linter that checks agent-related project files such as skills, plugins, agents, hooks, and CLAUDE.md.

In plain words
What is it for?
Onboarding a repository, applying automatic fixes, resolving remaining lint violations, creating a baseline, and setting up continuous integration checks.
Why use it?
It helps identify and fix setup problems when a project starts using skillsaw, including issues that need manual changes.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: mentions CLAUDE.md; installed under .agents/ (shared by several agents).

This is stbenjam/skillsaw's own configuration. It tells Claude Code how to work on skillsaw itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything skillsaw configures →

Part of the skillsaw plugin — 14 skills shipped together

Reuse

Borrowing it

Nothing to install: this file belongs to stbenjam/skillsaw. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/stbenjam/skillsaw/main/.agents/skills/skillsaw-onboard/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/stbenjam/skillsaw

Made for: Claude Code.

Or install skillsaw, the plugin that ships this one along with the rest of its 14 skills.

Wrote 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.

agentmods badge for skillsaw-onboard

README.md
[![agentmods](https://agentmods.dev/badge/skills/stbenjam/skillsaw/skillsaw-onboard/github.svg)](https://agentmods.dev/skills/stbenjam/skillsaw/skillsaw-onboard)
Your own site
<a href="https://agentmods.dev/skills/stbenjam/skillsaw/skillsaw-onboard"><img src="https://agentmods.dev/badge/skills/stbenjam/skillsaw/skillsaw-onboard/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.

agentmods 80×15 button for skillsaw-onboard

Your own site · 80×15
<a href="https://agentmods.dev/skills/stbenjam/skillsaw/skillsaw-onboard"><img src="https://agentmods.dev/badge/skills/stbenjam/skillsaw/skillsaw-onboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,514 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium MCP Rug Pull · line 4
    uvx/uv tool run commands without ==version create a rug-pull risk.
    Fix: Pin the version: uvx package-name==1.2.3
  • medium Excessive Agency · line 81
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium MCP Rug Pull · line 132
    uvx/uv tool run commands without ==version create a rug-pull risk.
    Fix: Pin the version: uvx package-name==1.2.3
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00055 $0.01514
Opus 5 $0.00028 $0.00757
Sonnet 5 $0.00011 $0.00303
Haiku 4.5 $0.00006 $0.00151

Measured 7d ago against content hash 2d1ade53428d, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

skillsaw-onboard 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 7d 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.

.agents/skills/skillsaw-onboard/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

skillsaw Onboard

Onboard this repository to skillsaw, a linter for agentic contextual building blocks (CLAUDE.md, skills, plugins, agents, hooks, etc.).

Workflow

Ask one routing question at a time and wait for the answer. An explicit choice in the user's request already counts as an answer. Read a reference only after its condition or a yes answer routes to it; do not read the reference to formulate the question. After completing it, return here. If the answer is no, continue to the next checkpoint without reading it. Carry forward the command prefix, counts, choices, and changed-file list.

Resolve every references/... path relative to the directory containing this SKILL.md, never relative to the target repository or the process's current working directory. If this file was fetched from the web, resolve each reference against the parent URL of this file and fetch it from that sibling location.

Replace brace-delimited fields below with facts from the repository or scan; never show placeholders to the user, and render singular or plural wording naturally.

1. Establish the current state

If no working skillsaw command is known, read install. Then read initial scan and report its violations before offering changes.

2. Triage findings by rule

Run skillsaw lint --format json -v to see all violations, including the info-level ones the first scan hid. Group the results by rule_id and sort them by count. Sample 3–5 examples from any large cluster (e.g. >10% of total findings or >20 issues) to understand the root cause before deciding on an action.

Follow triage to categorize each group into Fix now, Baseline, or Configure, and present a clear summary table to the user for confirmation before making changes. Carry the agreed buckets into the subsequent steps.

3. Apply autofixes

If the Fix now bucket holds autofixable findings, ask:

The plan includes autofixes for {count} violations: {safe count} safe and {suggest count} suggested. Applying them will edit the affected context files; I will show the changes and lint again afterward. Should I apply those fixes now?

Read the full file on GitHub · 151 lines

Changes

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.

  1. 7d ago Changed · +24 lines · +7 tokens per session 2d1ade53428d
  2. 13d ago First seen · 127 lines · 48 tokens per session scan A bd7f42f57249

Subscribe to this mod's changes

skillsaw-onboard is a skill published in the GitHub repository stbenjam/skillsaw (66 stars, last pushed today), licensed Apache-2.0. It adds 55 tokens to every session and 1,514 once invoked, about $0.0003 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.