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when-using-sparc-methodology-use-sparc-workflow

DNYoussef
更新于 Yesterday
28 次查看
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其他automation

关于

This skill orchestrates structured SPARC (Scope, Plan, Act, Review, Consolidate) workflows for developers, enforcing gated checkpoints and explicit confidence ceilings throughout the process. Use it for stage-gated problem-solving and evidence-backed reviews, but not for ad-hoc, single-pass tasks. It ensures intent capture and confidence-aware delivery within a defined operational framework.

快速安装

Claude Code

推荐
插件命令推荐
/plugin add https://github.com/DNYoussef/context-cascade
Git 克隆备选方式
git clone https://github.com/DNYoussef/context-cascade.git ~/.claude/skills/when-using-sparc-methodology-use-sparc-workflow

在 Claude Code 中复制并粘贴此命令以安装该技能

技能文档

STANDARD OPERATING PROCEDURE

Purpose

Run SPARC methodology end-to-end with clear intent capture, stage gates, evidence-backed reviews, and confidence-aware delivery.

Trigger Conditions

  • Positive: structured problem solving using SPARC, stage-gated delivery, retrospectives, consolidation of learnings.
  • Negative: ad-hoc single-pass tasks, prompt-only edits (route to prompt-architect), or new skill weaving (route to skill-forge).

Guardrails

  • Skill-Forge structure-first: maintain SKILL.md, examples/, tests/; add resources//references/ or log remediation tasks.
  • Prompt-Architect hygiene: capture HARD/SOFT/INFERRED constraints per SPARC stage, keep English-only outputs, and declare ceilings.
  • Stage safety: set entry/exit criteria for Scope/Plan/Act/Review/Consolidate, enforce registry usage, and keep hook latency budgets.
  • Adversarial validation: challenge assumptions each stage, run COV, and document evidence and deltas.
  • MCP tagging: store SPARC runs with WHO=sparc-workflow-{session} and WHY=skill-execution.

Execution Playbook

  1. Scope: define objective, constraints, and success metrics; confirm inferred assumptions.
  2. Plan: design approach, assign owners, and set timelines plus rollback points.
  3. Act: execute tasks with monitoring, TodoWrite updates, and guardrails.
  4. Review: validate outcomes, run adversarial checks, and log evidence.
  5. Consolidate: capture learnings, decisions, and next actions.
  6. Delivery: summarize SPARC path, evidence, risks, and confidence ceiling.

Output Format

  • SPARC stage summary with constraints and decisions.
  • Evidence log, risks, and follow-ups.
  • Confidence: X.XX (ceiling: TYPE Y.YY) - rationale.

Validation Checklist

  • Structure-first assets present or ticketed; examples/tests reflect SPARC flow.
  • Stage gates and rollback points defined; registry and hooks validated.
  • Adversarial/COV runs stored with MCP tags; confidence ceiling declared; English-only output.

Completion Definition

Workflow is done when SPARC stages complete with evidence, risks are owned, learnings captured, and MCP logs tagged for reuse.

Confidence: 0.70 (ceiling: inference 0.70) - SPARC workflow doc rewritten with skill-forge scaffolding and prompt-architect constraint/confidence discipline.

GitHub 仓库

DNYoussef/context-cascade
路径: skills/orchestration/when-using-sparc-methodology-use-sparc-workflow

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