القائمة
Skill compression reminder in 100 tokens — just trigger, action, result.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Same skill compression power in half the context — 975 tokens vs 2,500.
Complete skill compression documentation — all options, modes, and calibration details (~2,500 tokens).
Fit more skills in your context window — compress without losing what matters.
Full creative synthesis — combine song, visual concept, and TED talk from a single technical insight
Transform technical insights into full 40-50 minute TED-style talks with concrete examples and Q&A
Transform technical insights into Suno-ready songs with lyrics, style tags, and emotional arc
| name | Skill Distiller (One-Liner) |
| version | 0.2.1 |
| description | Skill compression reminder in 100 tokens — just trigger, action, result. |
| author | Live Neon <lee@liveneon.ai> |
| homepage | https://github.com/live-neon/skills/tree/main/skill-distiller/oneliner |
| repository | live-neon/skills |
| license | MIT |
| user-invocable | true |
| disable-model-invocation | true |
| emoji | 🗜️ |
| tags | ["compression","skills","optimization","context-window","token-reduction","quick-reference","minimal","openclaw"] |
Minimal reference variant (~100 tokens, ~70% functionality, LLM-estimated). Full reference: ../SKILL.reference.md.
TRIGGER: User asks to compress, distill, or reduce a skill's context usage
ACTION: Parse skill into sections (TRIGGER/INSTRUCTION/EXAMPLE/etc), score importance via LLM, remove low-value sections while preserving protected patterns (YAML name/description, N-count tracking, task creation)
RESULT: Compressed skill markdown with functionality score (0-100%), token reduction stats, and list of removed/kept sections
| Variant | Tokens | Functionality |
|---|---|---|
| skill-distiller (main) | ~400 | ~90% (formula) |
| compressed | ~975 | ~90% (prose) |
| oneliner (this) | ~100 | ~70% |
Full reference: SKILL.reference.md (~2,500 tokens, ~90%)
Functionality scores are LLM-estimated.
