dev-workflows/skills/recipe-task/SKILL.md
Execute tasks following appropriate rules with rule-advisor metacognition
npx skillsauth add shinpr/claude-code-workflows recipe-taskInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts.
Task: $ARGUMENTS
Step 1: Rule Selection via rule-advisor (REQUIRED)
Invoke rule-advisor using Agent tool:
subagent_type: "dev-workflows:rule-advisor"description: "Rule selection"prompt: "Task: $ARGUMENTS. Select appropriate rules and perform metacognitive analysis."Step 2: Utilize rule-advisor Output
After receiving rule-advisor's JSON response, proceed with:
Understand Task Essence (from taskAnalysis.essence)
Follow Selected Rules (from selectedRules)
Recognize Past Failures (from metaCognitiveGuidance.pastFailures)
Execute First Action (from metaCognitiveGuidance.firstStep)
Step 3: Create Task List with TaskCreate
Register work steps using TaskCreate. Use "Select and map applicable rules" as the first task and "Verify selected rules and report completion" as the final task.
Break down the task based on rule-advisor's guidance:
taskAnalysis.essence in task descriptionsmetaCognitiveGuidance.firstStep to first taskwarningPatternsStep 4: Execute Implementation
Proceed with task execution following:
metaCognitiveGuidance.firstStep action from rule-advisortesting
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
testing
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
testing
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.
testing
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing. Use when writing or revising LLM-facing prompts, handoffs, planning artifacts, reviews, reports, or generated instructions.