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Found 17 Skills
A methodology for iteratively improving agent-facing text instructions (skills / slash commands / task prompts / CLAUDE.md sections / code-generation prompts) by having a bias-free executor actually run them and evaluating two-sidedly (executor self-report + instruction-side metrics). Keep iterating until improvements plateau. Use it right after creating or substantially revising a prompt or skill, or when you want to attribute an agent's unexpected behavior to ambiguity on the instruction side.
Orchestrate copy exploration. Brief, generate 5 distinct approaches, adversarial review, iterate to 90+ composite, present catalog, user selects, execute.
Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification
Iteratively auto-optimize a prompt until no issues remain. Uses prompt-reviewer in a loop, asks user for ambiguities, applies fixes via prompt-engineering skill. Runs until converged.
· Batch-improve skill collections with evaluation loops, lint checks, behavioral tests, peer review. Triggers: 'skill refiner', 'improve skills', 'quality sweep', 'batch improve', 'skill loop'. Not for one skill.