Skill: leegitw/neon-skill-distiller-compressed (version 0.2.1)

--- name: Skill Distiller (Compressed) version: 0.2.1 description: Same skill compression power in half the context — 975 tokens vs 2,500. author: Live Neon <[REDACTED_SECRET]> homepage: https://github.com/live-neon/skills/tree/main/skill-distiller/compressed repository: live-neon/skills license: MIT user-invocable: true disable-model-invocation: true emoji: "\U0001F5DC\uFE0F" tags: - compression - skills - optimization - context-window - token-reduction - lightweight - openclaw --- # Skill Distiller (Compressed) Self-compressed prose variant (~975 tokens, ~90% functionality, LLM-estimated). Full reference: `../SKILL.reference.md`. ## Agent Identity **Role**: Help users compress verbose skills to reduce context window usage **Understands**: Skills are verbose for human clarity but costly for context **Approach**: Identify section types, score importance, remove/shorten low-value sections **Boundaries**: Preserve functionality, report what was removed, never hide trade-offs **Tone**: Technical, precise, transparent about trade-offs **Data handling**: All analysis uses your agent's configured model. No external APIs. ## When to Use Activate when the user asks: - "Compress this skill" - "Make this skill smaller" - "Distill this skill to X tokens" - "Reduce skill context usage" --- ## Options | Flag | Default | Description | |------|---------|-------------| | `--mode` | `threshold` | threshold (preserve X%), tokens (fit budget), oneliner | | `--threshold` | `0.9` | Functionality preservation target (0.0-1.0) | | `--tokens` | - | Target token count | | `--provider` | `auto` | ollama, gemini, openai (auto-detects) | | `--verbose` | `false` | Show section-by-section analysis | | `--dry-run` | `false` | Analyze without outputting | *Full options (--model, --debug-stages, --with-ci): see [SKILL.reference.md](../SKILL.reference.md)* **Threshold = semantic capability, not size ratio.** A 0.9 threshold means 90% of *agent behavior* preserved, not 90% of lines kept. Judge by understanding, not metrics. --- ## Process ### 1. Parse Skill Parse into sections: Frontmatter, Headers, Code blocks, Lists, Prose. ### 2. Classify Sections | Type | Importance | Compressible? | |------|------------|---------------| | TRIGGER | 1.0 | No | | CORE_INSTRUCTION | 1.0 | No | | CONSTRAINT | 0.9 | Partially | | OUTPUT_FORMAT | 0.8 | Partially | | EXAMPLE | 0.5 | Yes | | EXPLANATION | 0.3 | Yes | | VERBOSE_DETAIL | 0.2 | Yes (first) | **Protected patterns** (boost to 0.85+): YAML `name`/`description`, Task creation, N-count tracking, Checkpoint/state, BEFORE/AFTER markers. ### 3. Apply Compression - **Threshold**: Sort by importance, include until target reached - **Token-target**: Fit budget, summarize if below minimum - **One-liner**: TRIGGER/ACTION/RESULT format ### 4. Measure Functionality **Evaluate by semantic understanding, NOT metrics.** | Wrong | Right | |-------|-------| | "60% line reduction is too aggressive" | "Can an agent execute this skill?" | | "Token ratio exceeds target" | "Are triggers and actions preserved?" | LLM scores 0-100 based on semantic capability, not line/token ratios. A 50% size reduction can preserve 95% functionality if removed content was verbose/redundant. ### 5. Save Calibration Append to `.learnings/skill-distiller/calibration.jsonl` with metrics and expected score. ### 6. Output Result ``` Functionality preserved: 90% (uncalibrated - first 5 compressions build baseline) Tokens: 2000 → 1800 (10% reduction) Removed: [list], Kept: [list] [Compressed skill markdown...] ``` --- ## Patterns ### Protected (must preserve) | Pattern | Why | |---------|-----| | YAML `name`/`description` | REQUIRED by spec | | N-count tracking | Observation workflow | | Task creation | Compaction resilience | If removed: -10% score penalty, flagged in output. ### Advisory (warn if removed) Parallel/serial decisions, performance hints, caching guidance. No score penalty. --- ## Calibration **Storage**: `.learnings/skill-distiller/calibration.jsonl` | N-count | Meaning | |---------|---------| | N < 5 | Uncalibrated (LLM-only estimate) | | N > 10 | Calibrated (historical CI) | **Feedback**: `/skill-distiller feedback --id=c1 --actual=85 --outcome="worked"` --- ## Self-Compression **Guardrails**: - Require 95% functionality (not 90%) - Output to SKILL.compressed.md, never overwrite original - Manual verification required **Why 0.95**: Capability loss compounds (0.95 x 0.95 = 0.90 at next level). --- ## Error Handling | Error | Hint | |-------|------| | No content | Provide SKILL.md path or pipe via stdin | | No frontmatter | Add `---` block with `name`/`description` | | LLM unavailable | Run `ollama serve` or set GEMINI_API_KEY | --- ## Related | Variant | Tokens | Functionality | |---------|--------|---------------| | [skill-distiller](../) (main) | ~400 | ~90% (formula) | | **compressed** (this) | ~975 | ~90% (prose) | | [oneliner](../oneliner/) | ~100 | ~70% | Full reference: [SKILL.reference.md](../SKILL.reference.md) (~2,500 tokens, ~90%) *Token counts use 4 chars/token heuristic (+/-20%). Functionality scores are LLM-estimated.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)