slm-compress
SolidCompress large text, tool output, or transcripts to reduce context-window usage while keeping the full 1M window intact — call slm_compress(content, mode, reversible, ttl_seconds) to shrink content; if the result is lossy a ccr_id is returned so you can call slm_retrieve(ccr_id) later to recover the exact original; always fail-open (ok:false → continue with the original).
Install
Quality Score: 88/100
Skill Content
Details
- Author
- qualixar
- Repository
- qualixar/superlocalmemory
- Created
- 5 months ago
- Last Updated
- today
- Language
- Python
- License
- AGPL-3.0
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
slm-status
Health and optimization stats for SuperLocalMemory — call slm_optimize_stats() for live compression and cache counters (compress_runs, tokens_saved_compress, cache_proxy_hits, cache_proxy_misses, cache_kv_hits, cache_kv_misses); run slm status [--json] for system state (mode, profile, DB size, fact/entity/edge counts) and slm doctor [--json] for preflight including the "Optimize (Surface B)" health line; use together to confirm optimization is actually saving tokens.
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.
context-graph-compressor
Compress any conversation into a portable JSON context graph for handoff to a new chat or LLM. Trigger on: "compress this chat", "save context", "new chat", "hand off", "transfer context", "too many tokens", "start fresh", "export conversation", "context graph", "continue in new session". Also trigger proactively when the user mentions starting over in a long session.