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Found 20 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.
Iteratively improve any output until measurable criteria are met. Use when the user wants to refine existing work against specific standards — whether it's code, prose, data, config, or any other artifact. Triggers on phrases like "improve this", "make it better", "iterate", "refine", "keep improving", "not good enough yet", "optimize this", "polish this", "tighten this up", or when the user provides criteria and wants repeated improvement until they're satisfied. Also use when the user gives feedback on output and expects you to keep refining, even if they don't say "improve" explicitly.
Trigger: Call this skill when you need to collect opinions from multiple parties, integrate fragmented feedback into an actionable plan, or bring the plan back to real users/executors for validation. Common trigger signals include stakeholder input, user feedback, opinion summarization, alignment and verification. English: Trigger when input must be gathered from many people, synthesized into a clearer plan, and returned to the affected users or executors for validation. Use this skill for a collect-synthesize-validate loop.
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification
Reflect on previus response and output, based on Self-refinement framework for iterative improvement with complexity triage and verification