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- Agent Capability Discovery
agent-capability-discovery_skill
0
GitHub Stars
2
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill jorgealves/agent_skills --skill agent-capability-discovery- SKILL.md2.0 KB
- skill.yaml1.4 KB
Overview
This skill scans a repository of agent skill directories to build a comprehensive global map of available agent capabilities, inputs, and outputs. It indexes skill definition files to produce a searchable catalog that a master agent or developer can use to route requests or generate documentation. The result is a single source of truth describing what each sub-agent can do.
How this skill works
The skill locates and parses skill definition files (e.g., skill.yaml) under a specified base directory, extracting metadata such as name, description, inputs, outputs, and tags. It validates and skips malformed files while reporting warnings, then aggregates findings into a structured output (JSON, Markdown, or table) suitable for programmatic consumption or human review. The tool never executes skills or read arbitrary source code; it only reads declared metadata within the repository scope.
When to use it
- On system startup to populate an agent’s internal tool registry and available capabilities.
- When a master agent must choose the best specialized skill to handle a complex user request.
- To generate or update a Global Skills Map for developer documentation or audits.
- Before routing tasks to ensure required inputs and outputs match a sub-agent’s contract.
- When onboarding new skills so the catalog stays current and discoverable.
Best practices
- Keep skill definition files consistent and well-structured to improve discovery accuracy.
- Run discovery automatically on CI or at startup to ensure the registry reflects the latest skills.
- Treat discovery results as read-only metadata; use separate runtime processes for execution.
- Limit the base directory to intended repo paths to avoid accidental indexing of unrelated files.
- Log and review warnings for malformed definitions to maintain a healthy skill ecosystem.
Example use cases
- A master agent examines the catalog to pick between a privacy sanitizer and a compliance checker for a data-handling task.
- Generate a Markdown table of all skills for internal documentation and developer onboarding.
- Verify which skills declare a required input type before composing a multi-step workflow.
- Detect missing or duplicate capability declarations during a code review or CI run.
- Produce a JSON payload of capabilities for another service that performs routing or scheduling.
FAQ
No. It only discovers and indexes metadata from skill definition files; execution is handled by other runtime components.
What happens if a skill definition is malformed?
Malformed files are skipped and a warning is reported so maintainers can fix the definition without disrupting the entire discovery run.