Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Compress verbose SKILL.md files using Chain-of-Density with skill-aware formatting. Use when a skill exceeds 200 lines or needs terse refactoring.
Compress verbose SKILL.md files using Chain-of-Density with skill-aware formatting. Use when a skill exceeds 200 lines or needs terse refactoring.
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Compress SKILL.md files using CoD with skill-format awareness. Optimized for 2-3 passes (not 5) since skills are structured, not prose.
SKILL.md exceeds 200 lines Skill contains prose paragraphs instead of bullets Refactoring verbose documentation to terse style
Read the skill to condense Run 2-3 iterations of cod-iteration with skill-format context Each iteration: extract key entities, compress to bullets/tables Output: condensed skill maintaining structure
Pass to cod-iteration: iteration: 1 target_words: [current_words * 0.6] format_context: | OUTPUT FORMAT: Agent Skills SKILL.md - Use ## headers for sections - Bullet lists, not prose paragraphs - Tables for comparisons/options - Code blocks for commands - No filler phrases ("this skill helps you...") text: [FULL SKILL.MD CONTENT]
iteration: 2 target_words: [iteration_1_words] format_context: | SKILL.md TERSE RULES: - Each bullet = one fact - Combine related bullets with semicolons - Remove redundant examples (keep 1 best) - Tables compress better than lists for options text: [ITERATION 1 OUTPUT] source: [ORIGINAL SKILL.MD]
Only if still >150 lines: iteration: 3 target_words: [iteration_2_words] format_context: | FINAL PASS: - Move detailed content to references/ links - Keep only: Quick Start, Core Pattern, Troubleshooting - Each section <20 lines text: [ITERATION 2 OUTPUT] source: [ORIGINAL SKILL.MD]
Each iteration returns: Missing_Entities: "entity1"; "entity2"; "entity3" Denser_Summary: --- name: skill-name description: ... --- # Skill Name [Condensed content in proper SKILL.md format]
When condensing skills, prioritize these entity types: Entity TypeKeepRemoveCommandsdeploy.py --env prodVerbose explanationsOptionsTable rowParagraph per optionErrorsError β FixLong troubleshooting proseExamples1 best exampleMultiple similar examplesPrerequisitesBullet listExplanation of why needed
OriginalTargetIterations200-300 lines100-1502300-500 lines150-2002-3500+ lines200 + refs3 + refactor
Before (45 words): ## Configuration The configuration system allows you to customize various aspects of the deployment. You can set environment variables, adjust timeouts, and configure retry behavior. Each setting has sensible defaults but can be overridden as needed. After (18 words): ## Configuration | Setting | Default | Override | |---------|---------|----------| | `ENV` | prod | `--env dev` | | `TIMEOUT` | 30s | `--timeout 60` | | `RETRIES` | 3 | `--retries 5` |
If skill is too large after 3 iterations: Keep in SKILL.md: Overview, Quick Start, Common Errors Move to references/: API details, advanced config, examples Update SKILL.md with links: See [advanced config](references/config.md)
Preserve frontmatter exactly (don't condense metadata) Keep all ## section headers (structure matters) Don't remove code blocks (commands are entities) Maintain one concrete example per workflow
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Largest current source with strong distribution and engagement signals.