How do I install the Prompt Rewriter skill?

Run npx skillmds@latest add m2ai-portfolio/prompt-rewriter in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Prompt Rewriter safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Prompt Rewriter?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Prompt Rewriter free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Prompt Rewriter?

m2ai-portfolio (@m2ai-portfolio) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Prompt Rewriter by m2ai-portfolio — Agent Skill

Name: Prompt Rewriter
Author: m2ai-portfolio

Prompt Rewriter

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".

File contents

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:

Outcomes — What must the system achieve? (strip all "how")
Hard constraints — Business rules, safety, compliance, quality thresholds
Available tools — What tools/APIs/resources does the system have access to?
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:

## 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.

---name: prompt-rewriterdescription: 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 RewriterTransform scaffolding-heavy system prompts into clean, outcome-based prompts that work with capable models.## Phase 1: InputAccept 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.mdIf no audit exists, do a fast classification pass (outcome/constraint/scaffolding/duct-tape) before rewriting.## Phase 2: Extract Essential IntentFrom the classified components, extract:1. **Outcomes** — What must the system achieve? (strip all "how")2. **Hard constraints** — Business rules, safety, compliance, quality thresholds3. **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: RewriteProduce 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 AssessmentShow 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## SourceNate's Newsletter (2026-04-01): Outcome-based prompt rewriting as the second step of the compensating complexity removal pipeline. Pairs with `compensating-complexity-auditor`.

Frequently asked questions