القائمة
Mastra Evaluation and Testing guide - built-in scorers, custom scorers, datasets, experiments, and CI integration
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | mastra-evals |
| description | Mastra Evaluation and Testing guide - built-in scorers, custom scorers, datasets, experiments, and CI integration |
Comprehensive guide for evaluating AI agent quality with Mastra. Covers 17 built-in scorer factories, custom scorer creation with createScorer(), datasets for reproducible benchmarks, experiments for comparison, and CI pipeline integration.
/mastra-evals
Provides context for:
createAnswerRelevancyScorer())@mastra/evals/scorers/llm and @mastra/evals/scorers/codecreateScorer() from @mastra/core/scoresrunEvals({ target, scorers, data })samplingStructured task execution with quality gates, parallel waves, and pm-db tracking — solo or with multi-agent teams (--team). Use this skill when the user wants to execute a task list, run implementation tasks, start building a feature from a plan, run tasks in parallel with a team of agents, or says things like 'execute these tasks', 'start building', 'run the implementation', 'execute the plan', 'execute with a team', or 'start phase execute'. Also triggers on '/start-phase execute' and '/start-phase-execute-team' commands.
Assess and score codebase architecture health — layer separation, SOLID compliance, module coupling (FAN-IN/FAN-OUT), circular dependencies, drift from documented patterns. Use whenever the user asks to assess/review/grade architecture quality, wants an architecture score, or asks how healthy the codebase's architecture is. Analysis-only report + refactoring tasks; for docs-vs-code drift use document-hub-analyze.
Deep analysis of codebase for code duplication. Detects exact, structural, and pattern-level duplicates, generates comprehensive reports with refactoring suggestions and metrics.
Use when Mark reports a bug by pasting a raw artifact with little or no prose — a stack trace, an HTTP request/response trace (URL + method + status like 500/403/404/502), a console/React/Prisma error, a ChunkLoadError, a shell error, or a screenshot of a visual defect — or when he says things like 'still failing', 'clicking X does nothing', 'no inline editor on the rendered page', 'do we have local postgres/pgvector?', or 'identify the true error'. This is the front-to-back debugging procedure — extract the trigger and reproduction from terse input, probe whether the underlying plumbing even exists, localize by contrasting known-good vs broken, and drive to a durable root cause rather than a workaround. Reach for this BEFORE proposing any fix.
Deep analysis of codebase vs documentation alignment (cline-docs/). Detects drift, identifies undocumented code, extracts missing glossary terms, and provides actionable recommendations without making changes. Use this skill when the user asks "are the docs up to date", "check documentation quality", "what's missing from the docs", or wants a read-only audit before deciding what to update. For actually making changes, use document-hub-update instead.
Bootstrap a new project's documentation hub by creating the four core documentation files (systemArchitecture.md, keyPairResponsibility.md, glossary.md, techStack.md) with initial content based on codebase analysis.