SkillZip: Contract-Preserving Graph Compression for Agent Skill Libraries
Xingyu Tan · hf · 2026-08-13
SkillZip is a compression method designed for AI agent skill libraries. It compresses reusable procedural skills into contract-preserving, executable graph units.
The core objective is to address the retrieval and expansion challenges under limited context budgets. By utilizing efficient graph compression, it enhances the invocation performance of large-scale skill libraries.
Related event: SkillZip: Evaluation-Free Graph Compression for Agent Skills(2 posts)→
More from coding & agent
- Devs say LLM coding mistakes are a different class: overcomplication, inferred limits, worse at higher reasoning — Mu5_ · 2026-10-16
- How do you debug bad agent runs when you already have tracing? — Sensitive-Parsnip-12 · 2026-10-16
- Where does pre-task context live for agents? Devs debate workflows beyond handoff — shishen2026 · 2026-10-16
- No-instruction autonomous agent wakes up, sets own goals, and tries hacking by default — sethlazar · 2026-10-16
- CODESTRUCT reframes codebases as AST action spaces to fix brittle LLM code agents — burkov · 2026-10-16
- Would you install another SDK for agent debugging on top of your tracing stack? — Sensitive-Parsnip-12 · 2026-10-16