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Prompt evals over MCP: run a prompt on your dataset, score each output 1-5 with an LLM judge.
Machine-readable taxonomy of 100+ AI system failure modes spanning factuality, alignment, planning, code generation, and instruction following.
Checks the structural integrity of translated resource dictionaries against a source dictionary y...
Resolve whether an uncertain side-effecting action completed before software retries it.
Workflow planning, recovery checkpoints, coordination, fixtures, and compatibility tools for agents.
## Skill Catalog The library contains 42 public skills organized by Rails development concern. | Category | Examples | |----------|----------| | Planning | `create-prd`, `generate-tasks`, `plan-tickets` | | Testing | `plan-tests`, `write-tests`, `test-service`, `triage-bug` | | Code quality | `code-review`, `respond-to-review`, `security-check`, `refactor-code` | | Architecture and DDD | `define-domain-language`, `review-domain-boundaries`, `model-domain`, `review-architecture` | | Rails imple
Free enterprise-grade due diligence for your app, run by your coding agent. Then the full SDLC.
Review connected software projects, submit local findings and read reports with explicit approval.
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Browser-based QA for AI-built software. Test pages with real browsers via agents.