Compress and restructure any text using MECE grouping and the Pyramid Principle, scoring candidates on size reduction and meaning fidelity. Preserves template tags verbatim and can fill a user-supplied output template. Supports dense (LLM-oriented) and readable (human-oriented) output modes.
An Agent Skill that compresses and restructures any text using MECE grouping and the Pyramid Principle. It generates multiple candidate groupings, scores each on size reduction and meaning-fidelity, and ships the best one — preserving every instruction, key point, reference, and example.
Supports two output modes:
It also preserves template tags verbatim — auto-detected engine tags
(Handlebars/Mustache/Jinja/Liquid/shell/ERB) and explicit <!-- keep --> / <!-- drop -->
markers — and can emit the result into a user-supplied output template with named
<!-- slot:NAME --> slots.
compress-text-skill/
├── .claude-plugin/
│ ├── plugin.json # Claude Code plugin manifest
│ └── marketplace.json # Claude Code marketplace catalog (this repo)
├── .github/
│ └── workflows/ci.yml # CI: validate + run evals + build bundle
├── skills/
│ └── compress-text/
│ └── SKILL.md # The skill
├── evals/ # Evaluation suite (see evals/README.md)
├── scripts/
│ ├── build-skill-bundle.sh
│ └── validate.sh
├── CHANGELOG.md
├── LICENSE
└── README.md
This repo is both a Claude Code plugin (root contains skills/) and a
marketplace that lists that plugin.
# Add this repo as a marketplace
/plugin marketplace add MartinForReal/compress-text-skill
# Install the plugin
/plugin install compress-text@martinforreal-skills
Once installed, ask Claude to "compress this text" (or invoke the skill directly) and it will apply the MECE + Pyramid workflow.
To validate the manifests locally before publishing:
claude plugin validate . --strict
Build a distributable .zip bundle:
./scripts/build-skill-bundle.sh
# -> dist/compress-text-skill.zip (contains compress-text/SKILL.md)
Then upload the zip wherever Agent Skills are accepted:
POST the bundle to the Skills endpoint{{ tags }} untouched"Validate everything (manifests, skill structure, eval datasets) before publishing:
./scripts/validate.sh
Run just the evaluation suite (offline static checks, no model required):
python3 evals/run_evals.py
The suite also includes a labelled triggering dataset and functional rubric cases for model-judged evaluation — see evals/README.md. CI runs the validator and builds the bundle on every push and pull request.
See CHANGELOG.md.
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