6 skills found
Apply a prompt-agnostic execution and verification loop to any substantial task while preserving the original request. Use when the user asks to fan out work, use subagents or independent reviewers, loop until done, benchmark against references, apply a harsh critic, compare candidates blind, improve an existing prompt with verification, or continue until explicit quality gates pass.
Canonical workflow for a task. Read and follow strictly end to end while working on the task.
RFC-driven multi-agent DAG execution pattern with quality gates, merge queues, and work unit orchestration.
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
Capture workflow usage data for spec-kit optimization. Auto-activates when:(1) completing a spec-kit workflow (/speckit.review, final commit),(2) encountering friction or confusion during workflows,(3) user mentions issues with prompts or templates,(4) workflow deviates from expected quality gates.Reminds to export chat logs and tracks patterns for feedback.
This skill should be used when the user asks to evaluate agent performance, build test framework, measure agent quality, create evaluation rubrics, or mentions LLM-as-judge, multi-dimensional evaluation, agent testing, or quality gates for agent pipelines.
