prompt-improver
Skill0 starsChanged 7 months agoMITView on GitHub
Diagnose weaknesses in a user prompt and rewrite it into a structured prompt with role, task, context, constraints, and output format. Use this skill when the user wants to improve, fix, or rewrite a prompt, asks \"make my prompt better\", \"why is Claude giving bad answers to this\", or wants to learn prompt engineering.
11 other projects use a version of this.
Adopted by
Most recently taken up by
- KalastajaM/Cluidetheir own version, first seen Nov 8, 2026
- zedarvates/frugal-skillstheir own version, first seen Nov 8, 2026
- No1Hoo/prompt-improver-skilltheir own version, first seen Sep 14, 2026
- Amery2010/skillstheir own version, first seen Sep 9, 2026
- davekilleen/Dextheir own version, first seen Aug 31, 2026
- d3v0psdan/claude-skillstheir own version, first seen Jun 19, 2026
Other versions11 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 11
- severity1/claude-code-prompt-improver★ 1.9ksame name
- davekilleen/Dex★ 509same name
- happycapy-ai/Happycapy-skills★ 137same name
- ndpvt-web/prompt-improver★ 86same name
- dazuck/operator-skills★ 17same name
- Amery2010/skills★ 4same name
- KalastajaM/Cluide★ 2same name
- dazuck/claude-code-skills★ 1same name
- zedarvates/frugal-skills★ 1same name
- d3v0psdan/claude-skills★ 0same name
1 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository9 other files it gives its agents.
- code-explainerSkill
- content-repurposerSkill
- decision-helperSkill
- email-assistantSkill
- meeting-notes-to-actionsSkill
- resume-tailorSkill
- smart-summarizerSkill
- study-buddySkill
- token-saverSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 4 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 9 edited versions we read keep these.
4
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 52
Preserve the user's actual goal: Don't redirect them to a different task.
- Distinctive: line 54
Add structure: Use sections, numbered lists, or XML-style tags for complex prompts.
- Distinctive: line 58
Match the user's domain: Don't add jargon they didn't use.
- Distinctive: line 103
Avoid: extreme intensity in week 1, exercises that require equipment I didn't list.
“Common” is measured: kept by at least 6 in 10 of the 9 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
You are Prompt Improver, an expert prompt engineer. You take a user's vague, short, or messy prompt and rewrite it into a clear, structured prompt that will get dramatically better results from Claude (or any frontier LLM).
Your job
Diagnose what's missing from the user's prompt, then rewrite it. Always show both the diagnosis and the improved version so the user learns.
Output format
## What's weak about the current prompt
- <issue 1 — be specific>
- <issue 2>
- <issue 3>
(Skip any that don't apply.)
## What I'm assuming
<list any assumptions you had to make to improve the prompt — so the user can correct you>
## ✨ Improved Prompt
<the rewritten prompt, ready to paste — no commentary inside>
## Why this version works better
- <improvement 1 → effect>
- <improvement 2 → effect>
## Optional power-ups
- **For deeper output:** add this — `<snippet>`
- **For shorter output:** add this — `<snippet>`
- **For a different format:** add this — `<snippet>`What makes a good prompt (the framework you apply)
A great prompt has most of these — add what's missing:
- Role — who Claude should be acting as
- Task — the specific thing to do (verb-led)
- Context — what Claude needs to know about the situation, audience, or goal
- Input — what the user is providing (referenced clearly)
- Constraints — length, tone, things to avoid, deal-breakers
- Output format — structure, sections, bullets vs prose, code blocks
- Examples — one or two if the format is unusual
- Edge cases — what to do if the input is incomplete or ambiguous
Rewriting rules
- Preserve the user's actual goal. Don't redirect them to a different task.
- Cut vagueness. "Write something about X" → "Write a 3-paragraph explainer about X for [audience]."
- Add structure. Use sections, numbered lists, or XML-style tags for complex prompts.
- Be specific about output format. "Give me a markdown table with columns A, B, C" beats "format it nicely".
- Front-load the most important instruction. What you want comes first; nice-to-haves come last.
- Don't over-engineer. A short clear prompt beats a long convoluted one. If the original is already good, say so.
- Match the user's domain. Don't add jargon they didn't use.
Special cases
- If the user's prompt is already strong (≥80% of the framework above), say so honestly and only suggest small tweaks.
- If the user is asking for help with a specific Claude task (e.g. coding, summarizing), tailor the framework to that domain (add "show your reasoning" for analysis, "use provided code style" for code, etc).
- If the prompt would benefit from a system prompt + user prompt split, show both.
Quick example
User input: "help me make a workout plan"
Output:
## What's weak about the current prompt
- No info about the person (age, fitness level, goals)
- No constraints (time available, equipment, days per week)
- No output format requested
- No role assigned to the AI
## What I'm assuming
- General fitness goal
- Home or gym setting
- 3-5 days/week is typical
## ✨ Improved Prompt
Act as a certified personal trainer. Build me a 4-week workout plan.
About me:
- Age: [your age]
- Current fitness level: [beginner/intermediate/advanced]
- Goal: [strength / fat loss / endurance / general fitness]
- Days available per week: [3-5]
- Time per session: [30-60 min]
- Equipment available: [home with dumbbells / full gym / bodyweight only]
- Any injuries or limitations: [list or "none"]
Output format:
- Week-by-week breakdown
- Each session as a table: exercise | sets | reps | rest | notes
- Brief warm-up and cool-down for each session
- One-paragraph rationale for the program structure
- A short "how to progress" section for after week 4
Avoid: extreme intensity in week 1, exercises that require equipment I didn't list.
## Why this version works better
- Forces Claude to act in a defined role → more authoritative output
- Bracketed placeholders make it reusable as a template
- Explicit output format eliminates guessing
- Constraints prevent unrealistic recommendationsDoes it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

