ClawHub

prompt-polisher

v1.0.0

Rewrite rough goals, scattered notes, or vague requests into clear, actionable prompts with explicit objective, constraints, output format, and missing assum...

⭐ 0· 81·0 current·0 all-time
byXiaojian Chen@chenxiaojian985

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for chenxiaojian985/prompt-polisher1.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "prompt-polisher" (chenxiaojian985/prompt-polisher1) from ClawHub.
Skill page: https://clawhub.ai/chenxiaojian985/prompt-polisher1
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install prompt-polisher1

ClawHub CLI

Package manager switcher

npx clawhub@latest install prompt-polisher1
Security Scan
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Benign
high confidence
✓
Purpose & Capability
The skill's name and description match the SKILL.md: it only describes transforming rough requests into clearer prompts. It does not request unrelated credentials, binaries, or system access that would be disproportionate to rewriting prompts.
✓
Instruction Scope
The SKILL.md gives clear, bounded instructions for rewriting prompts (identify goal, extract constraints, list assumptions, produce a structured prompt). It does not instruct the agent to read files, environment variables, system state, or to send data to external endpoints. Note: the skill will echo user-provided text, so avoid submitting secrets.
✓
Install Mechanism
No install spec and no code files are present — the skill is instruction-only, so nothing is written to disk or downloaded during install.
✓
Credentials
No environment variables, credentials, or config paths are required. The agent instructions do not reference any secrets or unrelated services.
✓
Persistence & Privilege
always:false and user-invocable:true (defaults). The skill can be invoked autonomously by the agent (normal platform behavior) but does not request permanent presence, nor does it modify other skills or system configuration. agents/openai.yaml only defines a small interface/default prompt.
Assessment
This skill appears internally consistent and low-risk: it only contains instructions for rewriting prompts and requires no installs or credentials. Before using, avoid pasting any sensitive information (API keys, passwords, or private data) because the skill will rewrite and return whatever you provide. If you plan to let an autonomous agent use this skill, remember the agent could include user-supplied content in downstream requests — do not feed secrets. If you want extra assurance, test with non-sensitive example prompts first.

Like a lobster shell, security has layers — review code before you run it.

latestvk9703mv2x82xtswz8r0deqaxd584zkxe
81downloads
0stars
1versions
Updated 1w ago
v1.0.0
MIT-0
Xiaojian Chen@chenxiaojian985
latest
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Prompt Polisher

Overview

Turn an incomplete request into a prompt that is easier for another agent or model to execute well. Keep the user's intent intact while removing ambiguity, adding structure, and stating assumptions clearly.

Workflow

  1. Identify the core goal in the user's rough request.
  2. Extract any concrete constraints that are already present: audience, tone, format, length, platform, deadline, tools, or exclusions.
  3. Detect what is missing but necessary for reliable execution.
  4. Fill only low-risk gaps with brief assumptions. Label assumptions explicitly instead of presenting them as facts.
  5. Rewrite the request into a compact prompt with clear sections.
  6. If the request is still under-specified, provide a best-effort prompt plus a short list of the most important follow-up questions.

Output Shape

Prefer this structure when rewriting:

  • Goal
  • Context
  • Constraints
  • Desired Output
  • Assumptions
  • Final Prompt

Omit empty sections. Keep the final prompt concise and ready to paste.

Prompting Rules

  • Preserve the original intent; do not silently change the task.
  • Prefer concrete verbs over generic wording.
  • Convert fuzzy asks like "make it better" into measurable instructions.
  • Add output formatting when it helps execution, such as bullet list, table, JSON, checklist, or step-by-step plan.
  • Avoid over-engineering simple requests. A short request should become a short polished prompt.
  • When the user already gave enough detail, lightly polish instead of expanding aggressively.

Common Transformations

  • Replace vague verbs with precise actions.
  • Separate background information from required deliverables.
  • Turn implied preferences into explicit constraints.
  • State the expected audience or reader when relevant.
  • Add success criteria when quality is otherwise subjective.

Example

Rough request:

Write a product post for Xiaohongshu. Make it sound young and natural, not fake.

Polished prompt:

Write a Xiaohongshu product post for readers aged 20 to 30. Use a natural, young, and sincere tone without exaggerated marketing language. First provide 3 title options, then provide 1 main post. Keep the main post under 300 Chinese characters. Highlight real usage scenarios, core selling points, and user benefits. Avoid absolute claims. Output in Chinese.

If critical details are missing, append up to 3 short follow-up questions after the prompt.

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