agent-qa-authoring

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Create, edit, validate, and run Agent QA tests, suites, and hooks through MCP or CLI while preserving canonical IDs and schema contracts.

AI & Automation 45,362 stars 6648 forks Updated today MIT

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Skill Content

# Agent QA Authoring ## Overview Author Agent QA tests, suites, and hooks without inventing schema fields or identifiers. Prefer Agent QA's MCP tools, use the bundled contract reference for exact fields, and validate every definition before saving or running it. ## When to Use - Creating or editing an Agent QA test, suite, or hook. - Validating Agent QA YAML or canonical IDs. - Running a newly authored Agent QA definition through MCP or CLI. - Investigating which Agent QA configuration fields or workspace patterns apply. ## Preconditions and Approval Boundary - Work only in a configured Agent QA workspace that the user has authorized. - Inspect the requested scope before any create, update, delete, or test-run operation. - Obtain explicit confirmation before deleting a definition or running a test that can change external application state. - Keep credentials out of definitions and output; use the workspace's configured secret handling. ## Workflow 1. Discover the local surface with `agent_qa_discover`. 2. Inspect active config with `agent_qa_get_config`, especially targets, devices, providers, and `services.mcp`. 3. Load `references/agent-qa-contracts.json` when exact schema fields or ID contracts are needed. 4. Generate every new ID with Agent QA tooling: - MCP: `agent_qa_generate_id` - CLI fallback: `agent-qa ids generate <test|suite|hook|run|observation>` - Package fallback: `npx --yes agent-qa ids generate <type>` 5. Never hand-write IDs. Validate existi...

Details

Author
sickn33
Repository
sickn33/agentic-awesome-skills
Created
7 months ago
Last Updated
today
Language
Python
License
MIT

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