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compress-promptlisted

Use when about to write a long prompt, include verbose text in context, or when any block of text needs to be made token-efficient before use. Delegates compression to a local model via the LiteLLM proxy (ollama-agent MCP).
slogsdon/skills-meta-utils · ★ 0 · AI & Automation · score 68
Install: claude install-skill slogsdon/skills-meta-utils
# Skill: compress-prompt Compress verbose text into a token-efficient version using a local model via the LiteLLM proxy (default alias `fast-general` → gemma4:e4b-mlx). Preserves meaning and intent; strips filler, redundancy, and padding. ## When to Use - Before writing a long prompt to the user - Before including verbose content in context (notes, docs, logs) - When a block of text is longer than it needs to be ## Steps 1. Identify the text to compress (from user message, clipboard, or current context) 2. Call `mcp__ollama-agent__qwen_start` (standalone) or `mcp__plugin_shane-config_ollama-agent__qwen_start` (plugin — use whichever is available) with: - `task`: `"Compress the following into a token-efficient version. Preserve all meaning, intent, and key details. Remove filler words, redundancy, and padding. Do not summarize — compress. Output only the compressed text, no commentary.\n\n[TEXT TO COMPRESS]"` - No `skill` or `context` fields needed 3. Loop: if `status` is `"running"`, call `mcp__ollama-agent__qwen_continue` (or `mcp__plugin_shane-config_ollama-agent__qwen_continue` in plugin) with `session_id`; repeat until `status` is `"done"` or `"error"` 4. Return the model's `result` as the compressed output ## Notes - **Compress ≠ summarize.** Summarizing loses detail. Compressing preserves it in fewer tokens. - If the input is already tight, say so rather than padding the output. - Works on prompts, notes, documentation, session logs, or any prose.