Automatically compress large natural text or log files before processing. Triggers when the user pastes massive text blobs, asks to analyze a large file (logs, docs, transcripts), or provides a prompt too large for the context window. Do not trigger on source code files or structural data (JSON, XML).
/plugin marketplace add g-akshay/ClaudeShrink
The exact command may vary by repository. Check the README on GitHub.
For the skill author
Shows your skill is listed on Skillteca, generates a backlink and trackable traffic.
[](https://www.skillteca.com.br/skills/claudeshrink?utm_source=badge&utm_medium=readme&utm_campaign=badge)
Use this skill for any task involving spreadsheet files as primary input or output, such as opening, reading, editing, fixing, creating, or converting .xlsx, .xlsm, .csv, or .tsv files.
Searches claude-mem's persistent cross-session memory database. Use this to answer questions about previous solutions or retrieve work from past sessions.
Generates a week-by-week narrative digest of a project's Claude-mem timeline, splitting it into ISO-week files and using subagents to produce weekly chapters. Ideal for "weekly digests" or "narrative chapters" of a project's history.
This skill explains how claude-mem captures observations, when memory injection occurs, and where its data is stored.
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ClaudeShrink compresses large inputs using LLMLingua (gpt2) before you reason over them. This preserves semantic content while dramatically reducing token usage.
The compressor lives at: ~/.claude/skills/ClaudeShrink/scripts/compressor.py
It runs inside an isolated venv at: ~/.claude/skills/ClaudeShrink/.venv
[Description truncada. Veja o README completo no GitHub.]
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