Meta-Prompt: Build Role-Specific Skills
A meta-prompt for drafting reusable skill files that encode role standards, operating rules, failure handling, and output expectations.
Use cases
Operations & Workflow, Strategy & Planning
Platforms
Claude, GPT, Model-Agnostic
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The resource
Copy and adapt. Do not paste blind.
Design a reusable AI skill for a specific role.
Inputs to collect:
- role name
- audience or user
- recurring task types
- non-negotiable standards
- forbidden behaviour
- preferred output style
- common failure cases
Return:
1. Skill title
2. Skill description
3. Full skill file in markdown
4. Explanation of why each section exists
5. What still needs human testing
Requirements for the skill:
- It must describe how the role operates, not just what tone it uses.
- It must include a fallback for missing context.
- It must stay narrow enough to debug later.When to Use This
Use this when you want to turn a repeated working setup into a reusable skill instead of rewriting the same instructions every time.
It is useful for teams building libraries of role-specific AI behaviours: researcher, proposal writer, support triager, founder ghostwriter, and similar.
Why It Works
The prompt is designed to create operational roles, not character sketches. That distinction matters because good skills are about standards, fallback behaviour, and scope, not decorative adjectives.
The “what still needs human testing” section also matters. It stops the model from pretending a generated skill is already production-ready.
How to Customise
If you already have examples of good and bad outputs, provide them as part of the input. That makes the resulting skill much sharper.
You can also ask the meta-prompt to produce both a “light” and “strict” version of the same skill for different workflows.
Limitations
This creates first drafts, not finished capability packs. The generated skill still needs real testing across multiple tasks.
If the requested role is too broad, the meta-prompt will usually produce something vague. Narrow roles win.
Model Notes
Claude tends to produce cleaner rationale and better guardrails.
GPT is useful if you want the skill output in more rigid structure. Model-agnostic overall, but the quality of the input role definition sets the ceiling.
Related Resources
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A skill file that configures an LLM to write clear, structured technical documentation. Handles API docs, setup guides, README files, and process documentation with consistent formatting and appropriate detail depth.
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Related Guides
How to Turn a Good Prompt into a Reusable Skill
A practical guide to recognising when a one-off prompt has become a reusable capability and how to package it into a cleaner skill.
Custom Instructions vs Skills vs Agents
When to use light behavioural setup, reusable capability packs, or full multi-step systems without muddling the three together.