Evaluate an AI workflow against representative cases and its permitted actions. Use for model, retrieval or agent evaluation; tests do not grant release authority.
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Use evaluate to define the pre-run evaluation contract for [AI workflow description], including the evaluated surface (judgment, inputs, outputs, and failure impact), a case matrix with provenance-labeled examples and critical-failure rules for risk/coverage, and proposed pass rules (thresholds and acceptable uncertainty) for agreement.
Required inputs
[AI workflow description]
User-approved starter prompt based on a pinned source version; check current skill requirements before running. Task evidence ↗
SKILL.md
name: evaluatedescription: Evaluate an AI workflow against representative cases and its permitted actions. Use for model, retrieval or agent evaluation; tests do not grant release authority.
evaluate
Purpose
Evaluation results, failure analysis and release evidence.
Load further references only when the task needs them. Everything linked is included in this skill; no other skill pack is required.
Principles
Work directly from the supplied permitted context. Standalone work does not require an engagement folder or initialization. Record filenames in the method are optional persistence destinations when no engagement is bound.
If called by @fde, reuse its current sanitized packet and scope. Do not restart setup, discovery or questions already answered.
The task context contract controls persistence and authority in both modes. Preserve unknowns and distinguish implementation, verification, deployment and acceptance.
Use the customer's repository instructions and available tools. Report a missing capability or unrun check honestly; do not claim that installing a skill provisions infrastructure.