Standup Summary

Reviews skill libraries for structural, safety, linkage, size, and trigger-boundary issues. Useful for static analysis of skill metadata and structure without executing code.

Use when creating, updating, splitting, merging, or restructuring an agent skill or skill library. Defines scoping rules and authoring conventions for deterministic behavior.

Use when making a skill repository installable or public: manifests, README, artifacts, releases, publishing, or package checks.

Test and measure the activation, outcomes, and routing of agent skills in isolation. Ideal for verifying skill behavior and avoiding false activations.

Analyzes local AI skill library inventory, usage, and test status in the terminal, surfacing candidates for deletion or downgrading.

Export weekly or monthly business reports to CSV, PDF, or spreadsheet formats. Suitable for scheduled report packaging, multi-sheet exports, filtered dataset dumps, or download-ready report bundles.

Diagnoses new or existing AI project workspaces and defines an optimal technical roadmap in Spanish. Use at the start of a project for guidance on architecture and expert squad selection.

Designs, drafts, and deploys new AI skills following the Diamond Standard, generating documentation and registry integrations. Use when you need to create or extend agentic capabilities in a structured repository.

Analyzes a project's specific niche to inject domain knowledge, regulations, and industry standards. Use after the niche has been defined to ensure the product aligns with sector-specific expectations.