Database:
- PostgreSQL + pgvector for semantic search over skills and documents
- OpenAI embeddings for semantic similarity
- CLI tools: index, search, reindex
- Supabase production deployment ready
- Docker Compose for local development
Docs:
- Added frontmatter to all documents (name, description, doc_type, source_url)
- Reorganized doc structure
.gitignore:
- Added Private/ and .cursor/ to prevent accidental commits
New skill based on Factory Research (Dec 2025) on context compression:
- Anchored iterative summarization preserves more information
- Tokens-per-task is the right metric, not tokens-per-request
- Probe-based evaluation measures functional compression quality
- Six evaluation dimensions: accuracy, context, artifact, completeness, continuity, instruction
- Artifact trail is universally weak (2.2-2.5) and needs specialized handling
Includes:
- SKILL.md with compression strategies and evaluation framework
- references/evaluation-framework.md with probe types and scoring rubrics
- scripts/compression_evaluator.py with evaluation utilities
muratcankoylan