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Minutes Lint

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silverstein
minutes-lint

Health-check your meeting knowledge for contradictions, stale commitments, and decision conflicts. Use when the user asks "any conflicts in my meetings", "check for stale action items", "lint my meetings", "consistency check", "are there contradictions", or wants to audit their decision history.

Overview

Publishersilverstein
Repositoryminutes
Skill nameminutes-lint
Stars
1.5K
Forks
163
Bundled files
Instructions only
LicenseMIT
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 silverstein on GitHub. Read the source before you install it.

Installation

Install the Minutes Lint 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.
  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/silverstein/minutes.git /tmp/minutes
mkdir -p .claude/skills
cp -r /tmp/minutes/tooling/skills/goldens/claude/minutes-lint .claude/skills/minutes-lint
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Minutes Lint 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 Minutes Lint 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 Minutes Lint 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.

/minutes-lint

Run a consistency check across policy-authorized normal meetings to find decision conflicts and stale commitments. Restricted meetings are excluded from this agent workflow by default and must never be described as absent evidence.

How to run the lint

  1. Run the consistency check:

    bash
    minutes consistency --stale-after-days 14

    Optional filters:

    • --owner <name> — limit to commitments assigned to a specific person
    • --stale-after-days <N> — change the staleness threshold (default: 7)
  2. Parse the JSON output and present it as readable markdown.

Formatting the report

Decision Conflicts

For each conflict, show:

**Topic: {topic}**
- Latest: "{latest decision text}" — *{meeting title}* ({date})
- Prior: "{prior decision text}" — *{meeting title}* ({date})
- **Status**: These decisions may contradict each other.

Frontmatter v2: resolved supersessions. When the resolution field is present on a conflict, the newer decision has a supersedes: entry in its frontmatter. Treat this as informational, not a red flag. Format as:

**Topic: {topic}** ✓ Resolved
- Current: "{latest decision text}" — *{meeting title}* ({date})
- Superseded: "{prior decision text}" — *{meeting title}* ({date})
- **Status**: {resolution text}

If the latest decision also carries an authority field (high/medium/low), surface it next to the title. Authority is optional — when absent, omit the tag.

Stale Commitments

For each stale item, show:

- [ ] **@{who}**: {task} (due {due_date}, {age_days} days overdue)
  - Last discussed: *{meeting title}* ({date})

Clean bill of health

If no conflicts and no stale commitments, say: "No decision conflicts or stale commitments found across your meetings. Everything looks consistent."

When to suggest next steps

  • If there are decision conflicts: suggest running /minutes-debrief on the most recent conflicting meeting, or /minutes-search "{topic}" to review the full decision history
  • If there are stale commitments: suggest the user update the action item status in the meeting file, or bring it up in the next meeting with that person
  • Relationship-graph commitments come from minutes commitments --json; treat a nonzero exit as unavailable, never empty

Gotchas

  • The consistency check reads live Markdown — it uses stable source snapshots, not a durable graph cache. If a result looks wrong, inspect and correct the referenced meeting source; do not suggest deleting or rebuilding graph.db (it does not exist)
  • Stale != forgotten — some action items are intentionally deferred. Don't alarm the user; present the data and let them decide
  • Decision conflicts are topic-based — two meetings discussing "pricing" with different conclusions will flag, even if the later decision intentionally superseded the earlier one. Context matters.

Frequently asked questions

What does the Minutes Lint AI skill do?

Health-check your meeting knowledge for contradictions, stale commitments, and decision conflicts. Use when the user asks "any conflicts in my meetings", "check for stale action items", "lint my meetings", "consistency check", "are there contradictions", or wants to audit their decision history.

Why use Minutes Lint on TypingMind?

Because you install it once and use it with any model. Minutes Lint 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 Minutes Lint in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/silverstein/minutes/tree/main/tooling/skills/goldens/claude/minutes-lint. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Minutes Lint?

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 Minutes Lint?

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

Is the Minutes Lint AI skill free?

Yes. It is published on GitHub by silverstein under the MIT 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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