mlsanityData to 14 Oct 2026

Skilldex: A Package Manager and Registry for Agent Skill Packages with Hierarchical Scope-Based Distribution

arXiv 2604.16911 ↗First posted 18 Apr 2026cs.AIcited by 5

On the map: LLM agents and tool use → Agent skill learning and evolution

Abstract (arXiv)

Large Language Model (LLM) agents are increasingly extended at runtime via skill packages, structured natural-language instruction bundles loaded from a well-known directory. Community install tooling and registries exist, but two gaps persist: no public tool scores skill packages against Anthropic's published format specification, and no mechanism bundles related skills with the shared context they need to remain mutually coherent. We present Skilldex, a package manager and registry for agent skill packages addressing both gaps. The two novel contributions are: (1) compiler-style format conformance scoring against Anthropic's skill specification, producing line-level diagnostics on description specificity, frontmatter validity, and structural adherence; and (2) the skillset abstraction, a bundled collection of related skills with shared assets (vocabulary files, templates, reference documents) that enforce cross-skill behavioral coherence. Skilldex also provides supporting infrastructure: a three-tier hierarchical scope system, a human-in-the-loop agent suggestion loop, a metadata-only community registry, and a Model Context Protocol (MCP) server. The system is implemented as a TypeScript CLI (skillpm / spm) with a Hono/Supabase registry backend, and is open-source.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Placed in Agent skill learning and evolution, one of 16 directions in LLM agents and tool use. Builds on 1 of its 13 references that are in the map. First posted on arXiv 18 Apr 2026.

Builds on

1 of 13 references.

References · 1

  1. 2016Towards Verified Artificial Intelligencecited by 36

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Skills Are Not Islands: Measuring Dependency and Risk in Agent Skill Supply Chains
  2. 2026SkillOps: Managing LLM Agent Skill Libraries as Self-Maintaining Software Ecosystems
  3. 2026SkillAxe: Sharpening LLM-Authored Agent Skills Through Evaluation-Guided Self-Refinement
  4. 2026Agent Skills for Large Language Models: Architecture, Acquisition, Security, and the Path Forward
  5. 2026SkillCorpus: Consolidating and Evaluating the Open Skill Ecosystem for Real-World LLM Agents
  6. 2026Agent Skills: A Data-Driven Analysis of Claude Skills for Extending Large Language Model Functionality
  7. 2026OpenSkillEval: Automatically Auditing the Open Skill Ecosystem for LLM Agents
  8. 2026SkillX: Automatically Constructing Skill Knowledge Bases for Agents