Free SKILL.md scraped from GitHub. Clone the repo or copy the file directly into your Claude Code skills directory.
npx versuz@latest install m2ai-st-metro-skill-forge-drafts-prompt-rewritergit clone https://github.com/m2ai-st-metro/skill-forge.gitcp skill-forge/SKILL.MD ~/.claude/skills/m2ai-st-metro-skill-forge-drafts-prompt-rewriter/SKILL.md---
name: prompt-rewriter
description: Rewrite system prompts to strip compensating complexity and produce clean outcome-based prompts. Takes audit output (from compensating-complexity-auditor or manual analysis) and produces a four-component prompt — outcome spec, constraints, tools, coordination pattern. Use when modernizing prompts after a model upgrade, simplifying over-engineered system prompts, or converting procedural instructions to outcome-based ones. Trigger on "rewrite prompt", "simplify prompt", "strip scaffolding", "outcome-based prompt", "modernize prompt".
---
# Outcome-Based Prompt Rewriter
Transform scaffolding-heavy system prompts into clean, outcome-based prompts that work with capable models.
## Phase 1: Input
Accept ONE of:
- Raw audit output from the `compensating-complexity-auditor` skill (preferred)
- A system prompt the user wants rewritten (will do a quick classification pass first)
- A file path to a system prompt or CLAUDE.md
If no audit exists, do a fast classification pass (outcome/constraint/scaffolding/duct-tape) before rewriting.
## Phase 2: Extract Essential Intent
From the classified components, extract:
1. **Outcomes** — What must the system achieve? (strip all "how")
2. **Hard constraints** — Business rules, safety, compliance, quality thresholds
3. **Available tools** — What tools/APIs/resources does the system have access to?
4. **Coordination pattern** — If multi-agent: who talks to whom, what are handoff conditions?
Discard:
- Step-by-step procedures (let the model figure out "how")
- Format micromanagement (unless format IS the business requirement)
- Retry/fallback logic for known model weaknesses
- Few-shot examples that teach capabilities the model already has
## Phase 3: Rewrite
Produce a clean prompt with exactly four sections:
```markdown
## Outcome
[What this system must achieve — measurable, specific]
## Constraints
[Hard rules that cannot be violated — business, safety, quality]
## Tools
[Available tools and when to use them — not how to use them]
## Coordination
[Multi-agent handoffs, escalation conditions — if applicable]
```
Rules for the rewrite:
- No imperative procedures ("First do X, then do Y")
- No "you are a..." role-play preambles unless they genuinely change behavior
- Constraints only include things that are NOT obvious to a capable model
- Tool descriptions say WHAT the tool does, not step-by-step usage
- Total length should be 30-60% of the original (if it's longer, you added complexity)
## Phase 4: Diff + Risk Assessment
Show a before/after comparison:
- What was kept (and why)
- What was deleted (and why)
- What was reworded (and what changed)
- **Risk items**: anything deleted that MIGHT still be needed — flag these as "test before deploying"
Output a length comparison: original line count vs. rewritten line count, with percentage reduction.
## Verification
- Rewritten prompt must be shorter than the original
- All outcome logic from the original must be preserved
- All hard constraints must be preserved
- No procedural scaffolding in the output
- Risk items explicitly flagged for testing
## Source
Nate's Newsletter (2026-04-01): Outcome-based prompt rewriting as the second step of the compensating complexity removal pipeline. Pairs with `compensating-complexity-auditor`.