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Ieee Summarize

Community
CloudWave818
ieee-summarize

Summarize, organize, and normalize messy research materials into an IEEE-ready writing brief before manuscript drafting. Use when Codex needs to process a folder or collection of experiment logs, code files, AI chat exports, idea notes, literature summaries, related-work notes, copied introduction excerpts, Zotero-derived paper summaries, tables, figures, or scattered Markdown/text records and convert them into structured inputs for ieee-writing, ieee-experiment, ieee-citation, ieee-reviewer, or ieee-response.

Overview

PublisherCloudWave818
Repositoryieee-skills
Skill nameieee-summarize
Stars
405
Forks
22
Bundled files
5
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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by CloudWave818 on GitHub. Read the source before you install it.

Installation

Install the Ieee 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/CloudWave818/ieee-skills/tree/main/skills/ieee-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/CloudWave818/ieee-skills.git /tmp/ieee-skills
mkdir -p .claude/skills
cp -r /tmp/ieee-skills/skills/ieee-summarize .claude/skills/ieee-summarize
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ieee 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 Ieee 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 Ieee 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.

IEEE Summarize Router

Use this skill before ieee-writing when the user's research materials are scattered, chronological, duplicated, or not yet in manuscript structure. The output is not final prose; it is an evidence-grounded research brief that later writing skills can use.

Do not turn messy notes into polished claims by guessing. Preserve uncertainty, source paths, missing evidence, and contradictions.

Routing Protocol

  1. Read manifest.yaml.
  2. Read every file listed under always_load.
  3. Detect the request axes:
    • material_scope: folder / pasted-notes / code-and-logs / literature-pack / mixed.
    • output_target: research-brief / writing-input / experiment-summary / related-work-seed / claim-evidence-seed.
    • cleanup_level: inventory / standard / deep.
  4. State the detected axes in one short line.
  5. If a folder path is provided, inventory first:
    • Prefer scripts/inventory_research_folder.py <folder>.
    • If the script is unsuitable, use rg --files <folder>.
    • Do not read every large file blindly. Select representative and high-signal files by category.
  6. Map raw material into IEEE evidence slots:
    • problem object and operating condition,
    • engineering harm or practical motivation,
    • method idea and implementation clues from notes/code,
    • datasets, baselines, metrics, ablations, robustness, complexity, and reproducibility,
    • related-work families and closest-prior-work candidates,
    • contribution candidates and conclusion candidates.
  7. Preserve provenance. Every important extracted point should include a file path, heading, filename, or note source when available.
  8. Mark solid, partial, unclear, or missing for each evidence block.
  9. Hand off to the next skill explicitly: ieee-writing, ieee-experiment, ieee-citation, ieee-reviewer, or ieee-polishing.

Output Contract

Default output:

text
Detected axes: material_scope=..., output_target=..., cleanup_level=...

Material inventory
- Notes:
- Code:
- Experiments:
- Literature:
- Figures/tables:
- Unknown / skipped:

IEEE Research Brief
- Working title:
- Research object:
- Operating condition / constraints:
- Engineering harm:
- Core method:
- Implementation clues:
- Experiment evidence:
- Related-work seed:
- Contribution candidates:
- Conclusion candidates:
- Missing evidence:
- Contradictions / risks:

Next skill handoff
- Recommended next skill:
- Prompt-ready brief:

For folder-level work, create or update a Markdown file only when the user asks for a file. Suggested filename: ieee-research-brief.md.

Red Lines

Do not invent paper titles, citations, datasets, numerical results, code behavior, reviewer comments, or experiment outcomes.

Do not treat AI chat exports as verified evidence. Label them as ideation unless confirmed by code, logs, data, or papers.

Do not summarize copied paper introductions into plagiarism-ready text. Extract reusable background logic, domain motivation, and citation roles instead.

Do not remove negative results or failed experiments; classify them as limitation, ablation clue, or future-work evidence.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ieee Summarize AI skill do?

Summarize, organize, and normalize messy research materials into an IEEE-ready writing brief before manuscript drafting. Use when Codex needs to process a folder or collection of experiment logs, code files, AI chat exports, idea notes, literature summaries, related-work notes, copied introduction excerpts, Zotero-derived paper summaries, tables, figures, or scattered Markdown/text records and convert them into structured inputs for ieee-writing, ieee-experiment, ieee-citation, ieee-reviewer, or ieee-response.

Why use Ieee Summarize on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CloudWave818/ieee-skills/tree/main/skills/ieee-summarize. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ieee 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 Ieee Summarize?

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

Is the Ieee Summarize AI skill free?

Yes. It is published on GitHub by CloudWave818 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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