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Build evaluation datasets, harnesses, baselines, and release gates for multi-agent systems. Use when testing topology choice, routing, interaction contracts, coordination, durability, dynamic membership, adversarial propagation, end-to-end quality, or system cost and latency.
build-multi-agent-evals is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # Build Multi-Agent Evals Evaluate the composition, not only its members. ## Workflow 1. Read the System Spec, risk scenarios, topology decision, member evals,. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding build-multi-agent-evals to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install X-McKay/playbooksReview the upstream source before running this command.
Scan coverage: Install metadata and the indexed document body.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
# Build Multi-Agent Evals Evaluate the composition, not only its members. ## Workflow 1. Read the System Spec, risk scenarios, topology decision, member evals, and release policy.