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Summarize

OrganizationPopular
amd
summarize

Summarize a document, meeting transcript, or email — pick a style that matches what the content actually is, and fold long input forward in sections instead of losing the back half. Use when the user pastes or points at a transcript, email, PDF, or long document and asks for a summary, action items, or key decisions.

Overview

Publisheramd
Repositorygaia
Skill namesummarize
Stars
1.6K
Forks
176
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 amd on GitHub. Read the source before you install it.

Installation

Install the Summarize 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/amd/gaia/tree/main/hub/skills/summarize
  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/amd/gaia.git /tmp/gaia
mkdir -p .claude/skills
cp -r /tmp/gaia/hub/skills/summarize .claude/skills/summarize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Summarize 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 Summarize 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 Summarize 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.

Summarize

A summary that drops the back half of a long document is worse than no summary — it looks complete and isn't. Everything here exists to stop that: pick the right style for what the content is, and never lose earlier material when the input is too long to read in one pass.

Procedure

  1. Identify what you're summarizing before you pick a style. Read the first portion and classify it:

    • Transcript — speaker labels, timestamps, back-and-forth dialogue.
    • Email — From:/To:/Subject: headers, a greeting/sign-off, one author's voice.
    • Document / PDF / business content — reports, decks, specs; prose without dialogue structure. When it's genuinely ambiguous, say which you picked and why in one clause rather than silently guessing — the style below changes with it.
  2. Get the full text. For an indexed document, index_document it first if it isn't already (list_indexed_documents to check), then either call summarize_document(file_path, summary_type) or dump_document first if you need the raw extracted text. For pasted text or a plain text file, read_file is enough.

    summary_type accepts only brief, detailed, or bullets — anything else comes back as an error, not a summary. The named styles below are how you shape the output: pick the closest of those three, then write to the style the user actually asked for. For "what were the action items", that means detailed (so nothing is dropped) and then writing the list yourself from the text.

  3. Decide if it fits in one pass. If the content is short enough for you to read and reason over directly, write the summary yourself using the style instructions below — don't reach for the section-by-section tool path for a two-page memo. For anything long, use summarize_document (which already sections and folds internally) or the manual fold-forward procedure below when the tool isn't available for the content you have.

  4. Write to the style, not a generic summary. Match the length and structure rules exactly — a "brief" that runs to eight sentences failed the request even if every sentence is accurate.

Styles

Transcripts and emails — conversational, outcome-focused:

Only brief, detailed and bullets are real summary_type values; the rest name a shape you write yourself.

StyleWhat to produce
brief / executive2–3 sentences on the key outcomes and decisions.
detailedFull paragraph coverage of every major topic and outcome.
participantsSimple list of who was involved, with role/title if known.
action_itemsSimple list of what was assigned, and to whom if stated.
key_decisionsSimple list of concrete decisions and outcomes — not discussion.
topics_discussedSimple list of the subjects covered.

Documents, PDFs, and business content — numbers before narrative:

StyleWhat to produce
briefAt most 3 sentences, no bullets, only the 2–3 essential takeaways. No filler ("Overall", "In summary").
detailed250+ words. Extract every number, percentage, dollar amount, date, and metric. Name competitors, partners, customers, technologies. Full paragraphs, no bullets.
bulletsAt most 3 bullets total, each under 20 words, one idea per bullet.
executiveAt most 5 sentences. Priority order: (1) quantitative metrics, (2) financial data, (3) strategic outcomes, (4) competitive differentiators. Always keep the specific numbers. Board-ready tone, no bullets.

The rule underneath the table: for business documents, a metric always outranks the marketing language around it. "Revenue grew 40% YoY to $12M" is the sentence that survives a brief; "the company is scaling rapidly" is not.

Folding a long document forward (map-reduce)

summarize_document already does this internally when it's available — call it and you're done. Reach for the manual version only when you're working from pasted text or a file too large to read in one pass and the tool isn't an option:

  1. Split the text into ordered chunks, breaking on paragraph boundaries where possible rather than mid-sentence.
  2. Summarize the first chunk normally, in the target style.
  3. For every chunk after that, summarize it against the running summary: given the summary so far and the new chunk, output only the facts in the new chunk that are not already captured — no restating, no rephrasing what came before, no transition filler like "Additionally". This is the whole point of folding forward instead of summarizing each chunk in isolation: isolated per-chunk summaries repeat themselves and drift from the style once concatenated; folding keeps one coherent summary that only grows by what's actually new.
  4. Append each chunk's new-facts output to the running summary in order. The final running summary is the answer — do not re-summarize it again at the end, that just re-introduces the drift step 3 was avoiding.

Fork this

Swap the document table's priority order for a different domain (legal: obligations and deadlines before financial terms; incident review: root cause and impact before remediation steps) and the same fold-forward procedure carries a completely different kind of long input.

Frequently asked questions

What does the Summarize AI skill do?

Summarize a document, meeting transcript, or email — pick a style that matches what the content actually is, and fold long input forward in sections instead of losing the back half. Use when the user pastes or points at a transcript, email, PDF, or long document and asks for a summary, action items, or key decisions.

Why use Summarize on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/amd/gaia/tree/main/hub/skills/summarize. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Summarize?

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 Summarize?

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

Is the Summarize AI skill free?

Yes. It is published on GitHub by amd 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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