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Skillsaw Issue

Community
stbenjam
skillsaw-issue

Use when skillsaw reports a likely false positive, misses an edge case, behaves incorrectly, or needs an RFE. Gather a safe report and, only with explicit user permission, create a feedback bundle or open a GitHub issue.

Overview

Publisherstbenjam
Repositoryskillsaw
Skill nameskillsaw-issue
Stars
69
Forks
15
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by stbenjam on GitHub. Read the source before you install it.

Installation

Install the Skillsaw Issue AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/stbenjam/skillsaw/tree/main/.agents/skills/skillsaw-issue
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/stbenjam/skillsaw.git /tmp/skillsaw
mkdir -p .claude/skills
cp -r /tmp/skillsaw/.agents/skills/skillsaw-issue .claude/skills/skillsaw-issue
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skillsaw Issue in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Skillsaw Issue on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Skillsaw Issue is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

skillsaw Issue

Use this skill when skillsaw itself needs a GitHub issue: a false positive, a missed violation, a crash, incorrect autofix, an edge case in rule detection, or a request for enhancement (RFE). Do not use it to report a problem in the repository being linted unless that problem demonstrates incorrect skillsaw behavior or a useful feature gap.

Gather safe evidence first

Collect the minimum evidence needed to explain the issue without sending anything externally:

  • skillsaw version and the exact command
  • affected rule ID, file type, and relevant configuration
  • expected behavior and actual behavior for a bug
  • user goal and proposed outcome for an RFE
  • a minimal reproducer or a short sanitized excerpt

Never copy credentials, private repository content, or complete diagnostic output into an issue draft. Prefer a minimal synthetic reproducer.

Require separate permission for each external action

Ask the user two explicit questions before taking either action:

  1. "May I run skillsaw feedback to create a local diagnostic ZIP?"
  2. "May I open an issue in stbenjam/skillsaw?"

Do not run skillsaw feedback without permission for the first action. Do not create a GitHub issue without permission for the second action. Permission for one action does not authorize the other. If permission is absent, present a sanitized draft and ask for the missing approval.

Create a feedback bundle only when approved

Run skillsaw feedback <repository-path> with a concise --message that describes the observed behavior. The command creates a local ZIP; it does not submit anything. Do not add --include unless the user explicitly identifies the file to share.

Review the ZIP before sharing it. skillsaw does not scan file contents for secrets: anything --include or --config names is copied in verbatim, so read those files yourself and remove or replace anything sensitive. Keep the bundle local if the user does not also approve opening an issue.

Open an issue only when approved

Search existing issues first to avoid duplicates. Then open an issue in stbenjam/skillsaw with:

  • a specific title naming the affected rule, behavior, or requested capability
  • the minimal reproducer and exact command for a bug
  • expected and actual results for a bug, or the user goal and proposed outcome for an RFE
  • skillsaw version and relevant configuration when applicable
  • the reviewed feedback ZIP only when the user approves attaching it

State which sensitive details were omitted. Link the issue back to the user and summarize what was shared. Do not change labels, milestones, assignees, or project state unless the user specifically requests it.

Frequently asked questions

What does the Skillsaw Issue AI skill do?

Use when skillsaw reports a likely false positive, misses an edge case, behaves incorrectly, or needs an RFE. Gather a safe report and, only with explicit user permission, create a feedback bundle or open a GitHub issue.

Why use Skillsaw Issue on TypingMind?

Because you install it once and use it with any model. Skillsaw Issue is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Skillsaw Issue in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/stbenjam/skillsaw/tree/main/.agents/skills/skillsaw-issue. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Skillsaw Issue?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Skillsaw Issue?

As many as you like. As long as a model supports skills, you can use Skillsaw Issue with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Skillsaw Issue AI skill free?

Yes. It is published on GitHub by stbenjam under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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