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prompt-optimizer

prompt-optimizer

github.com/chujianyunAgent workflows749210 installsUpdated 2w ago
Repository

About prompt-optimizer

A prompt-writing skill for people turning task descriptions into usable prompts. It evaluates the request, selects a framework suited to its complexity and domain, asks about essential gaps, and generates a prompt for iteration.

Key features

  1. 01Analyze existing prompts and requests
  2. 02Select frameworks by domain and complexity
  3. 03Ask focused clarifying questions
  4. 04Generate and refine structured prompts
  5. 05Explain framework selection

Use cases

  1. 01Turning a vague idea into a task prompt
  2. 02Improving a prompt for a specific domain
  3. 03Quickly polishing a simple prompt without overbuilding

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/chujianyun/skills --skill prompt-optimizer

After installing, type/prompt-optimizerin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

LICENSE.txt
references/
Frameworks_Summary.md
references/frameworks/
01_RACEF_Framework.md
02_CRISPE_Framework.md
03_BAB_Framework.md
04_Tree_of_Thought_Framework.md
05_RICE_Framework.md
06_RELIC_Framework.md
07_SCAMPER_Framework.md
08_BLOG_Framework.md
09_Six_Thinking_Hats_Framework.md
10_CIDI_Framework.md
11_SPEAR_Framework.md
12_Few_shot_Framework.md
13_Zero_shot_Framework.md
14_FOCUS_Framework.md
15_RACE_Framework.md
16_Blooms_Taxonomy_Framework.md
17_Pros_and_Cons_Framework.md
18_3Cs_Model_Framework.md
19_4S_Method_Framework.md
20_APE_Framework.md
21_CAR_PAR_STAR_Framework.md
22_CARE_Framework.md
23_ELI5_Framework.md
24_Challenge_Solution_Benefit_Framework.md
25_COAST_Framework.md
26_Elicitation_Framework.md
27_ERA_Framework.md
28_Five_Ws_and_One_H_Framework.md

Details

From the project README

Prompt Optimizer

帮助用户基于具体任务场景,选择合适的提示词框架,并生成更清晰、更可执行的 prompt。

设计模式

本 skill 主要采用:

  • Reviewer:先判断用户现有 prompt 或任务描述的问题
  • Inversion:信息不足时,先追问目标、受众、约束和格式
  • Generator:基于选定框架生成优化后的 prompt

Gotchas

  • 不要一上来就套框架,先判断任务是否真的需要复杂框架
  • 不要为了显得专业而过度设计简单 prompt
  • 如果用户只想快速润色一句 prompt,不要强行输出一整套长模板
  • 如果目标、受众、输出格式不清楚,先补最小必要问题
  • 说明为什么选这个框架,比堆很多框架名更重要

Workflow

Copy this checklist and track your progress:

  • Step 1: Analyze User Input
  • Step 2: Match Scenario and Select Framework
  • Step 3: Load Framework Details
  • Step 4: Clarify Ambiguities
  • Step 5: Generate Optimized Prompt
  • Step 6: Present and Iterate

When a user requests create or prompt optimization, follow these steps:

Step 1: Analyze User Input

Receive the user's request, which may be:

  • A raw prompt that needs optimization
  • A task description or requirement
  • A vague idea that needs to be turned into a prompt
Step 2: Match Scenario and Select Framework

Read the references/Frameworks_Summary.md file to:

  1. Identify the user's scenario from the application scenarios listed
  2. Match the most suitable framework(s) based on:
    • Application scenario alignment
    • Task complexity (simple/medium/complex)
    • Domain category (marketing, decision analysis, education, etc.)

Framework Selection Guide by Complexity:

ComplexityRecommended Frameworks
Simple (≤3 elements)APE, ERA, TAG, RTF, BAB, PEE, ELI5
Medium (4-5 elements)RACE, CIDI, SPEAR, SPAR, FOCUS, SMART, GOPA, ORID, CARE, ROSE, PAUSE, TRACE, GRADE, TRACI, RODES
Complex (6+ elements)RACEF, CRISPE, SCAMPER, Six Thinking Hats, ROSES, PROMPT, RISEN, RASCEF, Atomic Prompting

Framework Selection Guide by Domain:

DomainRecommended Frameworks
Marketing ContentBAB, SPEAR, Challenge-Solution-Benefit, BLOG, PROMPT, RHODES
Decision AnalysisRICE, Pros and Cons, Six Thinking Hats, Tree of Thought, PAUSE, What If
Education & TrainingBloom's Taxonomy, ELI5, Socratic Method, PEE, Hamburger Model
Product DevelopmentSCAMPER, HMW, CIDI, RELIC, 3Cs Model
AI Dialogue/AssistantCOAST, ROSES, TRACE, RACE, RASCEF
Writing & CreationBLOG, 4S Method, Hamburger Model, Few-shot, RHODES, Chain of Destiny
Image GenerationAtomic Prompting
Quick Simple TasksZero-shot, ERA, TAG, APE, RTF
Complex ReasoningChain of Thought, Tree of Thought
Step 3: Load Framework Details

Once the best framework is identified, read the corresponding framework file from the references/frameworks/ directory:

  • File naming pattern: XX_FrameworkName_Framework.md
  • Example: For RACEF framework, read references/frameworks/01_RACEF_Framework.md

The framework file contains:

  • Framework overview and components
  • Detailed explanation of each element
  • Pros and cons
  • Best practice examples
Step 4: Clarify Ambiguities

Before generating the final prompt, verify with the user:

  1. Goal Clarity: Is the intended outcome clear?
  2. Target Audience: Who will receive the AI's response?
  3. Context Completeness: Is sufficient background information provided?
  4. Format Requirements: Are there specific output format needs?
  5. Constraints: Are there any limitations or restrictions?

Ask clarifying questions if any information is:

  • Missing
  • Ambiguous
  • Incomplete
  • Contradictory

Example clarifying questions:

  • "What specific outcome are you hoping to achieve?"
  • "Who is the target audience for this content?"
  • "Are there any format or length requirements?"
  • "What context should the AI consider?"
Step 5: Generate Optimized Prompt

Apply the selected framework to create the final prompt:

  1. Structure the prompt according to framework components
  2. Incorporate all clarified information
  3. Ensure clarity and specificity
  4. Include relevant examples if the framework requires
  5. Add any necessary constraints or guidelines
Step 6: Present and Iterate

Present the optimized prompt to the user with:

  1. The selected framework name and why it was chosen
  2. The complete optimized prompt
  3. Explanation of how each framework element was applied
  4. Suggestions for potential variations or improvements

If the user requests changes, iterate on the prompt while maintaining framework structure.

Framework Reference Files

All framework details are stored in the references/frameworks/ directory. Each file contains:

  • Application scenarios
  • Framework components with explanations
  • Advantages and disadvantages
  • Multiple practical examples

Quick Framework Selection

For users unsure which framework to use:

User SaysRecommended Framework
"I need a simple prompt"APE, ERA, TAG
"I want to persuade/sell"BAB, SPEAR, Challenge-Solution-Benefit
"I need to analyze/decide"RICE, Pros and Cons, Chain of Thought
"I want to teach/explain"ELI5, Bloom's Taxonomy, Socratic Method
"I need creative ideas"SCAMPER, HMW, SPARK, Imagine
"I want structured writing"BLOG, 4S Method, Hamburger Model
"I need step-by-step reasoning"Chain of Thought, Tree of Thought
"I'm generating images"Atomic Prompting
"I need a detailed plan"RISEN, RASCEF, CRISPE

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