semantic-compression
SolidAggressively remove grammatical scaffolding LLMs reconstruct while preserving meaning-carrying content. Output may be fragments. Use when compressing text for prompts, reducing token count, preparing context for LLM input, or making documentation more token-efficient. Applies LLM-aware compression rules that delete predictable grammar while preserving semantics.
Install
Quality Score: 86/100
Skill Content
Details
- Author
- dmae97
- Repository
- dmae97/omk
- Created
- 3 months ago
- Last Updated
- yesterday
- Language
- TypeScript
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
semantic-compress
Make an LLM-directed document smaller while preserving what it does. Two modes: a local span-level core->pointer pass, and an A/B-validated distill loop that produces the smallest document that behaves the same as the original. Point at core knowledge the model already holds (a concept name activates it); keep project-specific detail explicit and verbatim. TRIGGER when asked to compress, tighten, shorten, or strip a prompt / instruction / system message meant for an LLM; to distill a skill; to compress a whole document; to make this smaller while preserving behaviour; to A/B test a compression or produce a behaviourally-equivalent compression; when an instruction set explains concepts the model already knows from training; or when reducing token cost of an LLM-directed prompt without losing meaning. Not for human-facing prose - that is /deslop.
technical-gist
Compresses technical English into compact expert notes. Sentence fragments, dropped articles, and omitted scaffolding are allowed; meaning, numbers, scope, uncertainty, negation, and technical terms are not. For methods summaries, model descriptions, implementation notes, issue and bug summaries, analytical findings, internal updates, and technical documentation. Levels: lite, full (default), ultra.
compress-context
Compress a given file (CLAUDE.md, skill file, prompt file) into token-efficient symbolic notation. Rewrites the file in-place and maintains a symbols.md legend. Use when asked to compress, reduce tokens, shorten prompts, or make context more efficient.