# Agent Skill Registry > Agents should execute whenever possible — open registry of reusable AI agent skills and capability definitions - **Type:** MCP server - **Install:** `agentstack add mcp-gfernandf-agent-skill-registry` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [gfernandf](https://agentstack.voostack.com/s/gfernandf) - **Installs:** 0 - **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml) - **Latest version:** 0.1.0 - **License:** Apache-2.0 - **Upstream author:** [gfernandf](https://github.com/gfernandf) - **Source:** https://github.com/gfernandf/agent-skill-registry ## Install ```sh agentstack add mcp-gfernandf-agent-skill-registry ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Agent Skill Registry An open registry of reusable **AI agent skills** and **capability definitions**. ## Terminology Note For cognitive runtime terminology, we use: - COGIT = capability - SYLLOG = skill In this repository implementation, we keep the canonical technical terms `capability/capabilities` and `skill/skills` (directory structure, schemas, tooling, catalogs, and validation contracts) to preserve architecture and compatibility. ## Quick Start ```bash pip install -r requirements.txt python tools/validate_registry.py python tools/generate_catalog.py ``` See the companion runtime at [agent-skills](https://github.com/gfernandf/agent-skills) for execution. ## License Apache 2.0 — see [LICENSE](LICENSE). --- The registry provides a standardized, declarative way to define: - primitive **capabilities** - composable **skills (workflows)** - shared **vocabulary** - machine-readable **catalogs** It acts as the **source of truth for agent workflows** that can be executed by compatible runtimes. ------------------------------------------------------------------------ # Why this exists AI agents increasingly rely on structured tools and workflows. However, most implementations today are: - tightly coupled to a specific framework - implemented imperatively in code - difficult to reuse across systems - inconsistent in naming and structure The **Agent Skill Registry** addresses this by providing: - a **common vocabulary** - a **declarative workflow model** - a **shared registry of reusable skills** - a **machine-readable catalog for runtimes** The goal is to make agent capabilities **discoverable, composable, and reusable**. ------------------------------------------------------------------------ # Core Concepts The registry defines two fundamental building blocks. ## Capabilities Capabilities represent **primitive operations**. They define a **contract** describing what an operation does, including: - inputs - outputs - execution properties - optional metadata Examples: reasoning.content.summarize\ web.page.fetch\ pdf.document.read\ audio.speech.transcribe\ code.diff.extract Capabilities are **not implementations**. They define **what a runtime must implement**, not how. ------------------------------------------------------------------------ ## Skills Skills are **composable workflows** built from capabilities. A skill defines: - inputs - outputs - steps - capability usage - optional nested skill usage Example skill: web.fetch-summary Workflow: web.page.fetch → web.page.extract → reasoning.content.summarize Skills allow building reusable agent behavior without writing imperative code. ------------------------------------------------------------------------ # Registry Structure agent-skill-registry\ │\ ├─ capabilities/\ │ Capability definitions\ │\ ├─ skills/\ │ Reusable workflows\ │\ ├─ catalog/\ │ Generated machine-readable catalogs\ │\ ├─ tools/\ │ Registry tooling\ │\ └─ docs/\ Specifications and language documentation ------------------------------------------------------------------------ # Vocabulary The registry enforces a **controlled vocabulary** to maintain consistency. Capability identifiers follow the pattern: domain.noun.verb Examples: perception.keyword.extract\ image.caption.generate\ data.schema.validate\ code.diff.extract The vocabulary is defined in: vocabulary.json This ensures: - consistent naming - predictable semantics - long-term maintainability ------------------------------------------------------------------------ # Skills as Dataflow Skills are **declarative workflows**. Each step references a capability or another skill. Example: steps: - id: fetch uses: web.page.fetch input: url: inputs.url output: content: vars.page - id: extract uses: web.page.extract input: content: vars.page output: text: vars.text - id: summarize uses: reasoning.content.summarize input: text: vars.text output: summary: outputs.summary Execution semantics: inputs → steps → outputs No imperative logic is embedded in the skill definition. ------------------------------------------------------------------------ # Generated Catalog The registry generates machine-readable catalogs used by runtimes. catalog/capabilities.json\ catalog/skills.json\ catalog/graph.json\ catalog/stats.json These provide: - skill discovery - dependency graphs - usage statistics - capability relationships Catalogs are generated using: tools/generate_catalog.py ------------------------------------------------------------------------ # Validation All registry content is validated using: tools/validate_registry.py Validation checks: - schema correctness - vocabulary compliance - capability references - skill dependency cycles - identifier correctness Run validation: python tools/validate_registry.py ------------------------------------------------------------------------ # Statistics Registry statistics are generated automatically. python tools/registry_stats.py This produces: catalog/stats.json Including: - capability usage - unused primitives - skill counts by domain - metadata coverage ------------------------------------------------------------------------ # Contributing Contributions are welcome. You may contribute: - new capabilities - new skills - improvements to metadata - documentation updates Typical workflow: 1. Add capability or skill\ 2. Run validator\ 3. Regenerate catalog\ 4. Submit pull request Commands: python tools/validate_registry.py\ python tools/generate_catalog.py\ python tools/registry_stats.py\ python tools/governance_guardrails.py\ python tools/capability_governance_guardrails.py\ python tools/enforce_capability_sunset.py ------------------------------------------------------------------------ # Design Principles The registry follows several core principles. ### Declarative Skills describe **what happens**, not how. ### Runtime-agnostic The registry does not define execution engines. Different runtimes may implement capabilities differently. ### Composable Skills can reuse capabilities and other skills. ### Vocabulary-controlled Naming follows a strict vocabulary to avoid fragmentation. ### Open and extensible The registry is designed to grow through community contributions. ------------------------------------------------------------------------ # Relationship with Runtimes This repository **does not execute skills**. It defines the language and registry. Execution is handled by compatible runtimes. A runtime typically performs: skill → step resolution → capability provider → execution ------------------------------------------------------------------------ # Current Registry Scope Current registry includes: - 159 capabilities - 37 skills - validation tooling - dependency graph generation - registry statistics This represents the first usable registry version. ------------------------------------------------------------------------ # Documentation Additional documentation: docs/LANGUAGE.md\ docs/CAPABILITIES.md\ docs/SKILL_FORMAT.md\ docs/GOVERNANCE.md\ docs/SKILL_ADMISSION_POLICY.md\ docs/SEMANTIC_FAMILY_MAP.md\ docs/CAPABILITY_ADMISSION_POLICY.md\ docs/CAPABILITY_COMPATIBILITY_POLICY.md\ docs/CAPABILITY_SUNSET_POLICY.md\ docs/VOCABULARY_BUSINESS_WORKFLOW_COVERAGE.md docs/CANONICAL_METRICS.md Governance artifact: catalog/governance_guardrails.json\ catalog/capability_governance_guardrails.json ------------------------------------------------------------------------ # Vision The long-term goal is to create a **shared ecosystem of agent skills** that can be: - discovered - reused - composed - executed across runtimes A common language for AI agent workflows. ## Source & license This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [gfernandf](https://github.com/gfernandf) - **Source:** [gfernandf/agent-skill-registry](https://github.com/gfernandf/agent-skill-registry) - **License:** Apache-2.0 Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/mcp-gfernandf-agent-skill-registry - Seller: https://agentstack.voostack.com/s/gfernandf - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.