---
name: promptify
description: Transform user requests into detailed, precise prompts for AI models.
  Use when users say 'promptify', 'promptify this', or explicitly request prompt engineering
  or improvement of their request for better AI responses.
metadata:
  category: agent
  tags:
  - agent
  - prompt-engineering
  - clarity
  - specification
  status: ready
---

# Promptify

Transform user requests into detailed, precise prompts optimised for AI model consumption.

## Core Task

Rewrite the user's request as a clear, specific, and complete prompt that guides an AI model to produce the desired output without ambiguity. Treat the output as specification language, not casual natural language.

## Workflow

### 1. Analyze

Read the user's request carefully. Identify:

- The core intent and desired outcome
- Missing context (audience, domain, environment)
- Unstated constraints (length, tone, format)
- Expected output format

### 2. Structure

Apply the four-block pattern to organise the prompt. See `rules/structure-four-block-pattern.md`.

- **Context** - Background, audience, domain
- **Task** - What the AI must do
- **Constraints** - Boundaries, rules, limitations
- **Output Format** - Exact structure of the response

Not every prompt needs all four blocks. Use only what adds clarity.

### 3. Refine

Apply the rules in `rules/` to sharpen the prompt:

- Replace vague terms with measurable requirements
- Add examples where the desired output is ambiguous
- Specify exact format (headings, bullet style, length)
- Break complex tasks into numbered sequential steps

### 4. Output

Present the final prompt to the user as a markdown block, clearly labeled. Do not add commentary beyond the prompt itself.

### 5. Deliver

After presenting the prompt, offer the user two options:

1. **Execute now** — Treat the generated prompt as your new instruction and proceed based on the current conversation context. Use your normal judgement to decide the best next action — plan complex tasks, implement simple ones directly, or ask clarifying questions if needed.
2. **Save to file** — Write the prompt to a markdown file in the current working directory (e.g. `promptify-<timestamp>.md` where `<timestamp>` is epoch seconds). Let the user know the file path.

## Writing Guidelines

### Structure

- Begin with a single short paragraph summarising the overall task
- Use headings (##, ###, ####) for sections only where appropriate (no first-level title)
- Use **bold**, _italics_, bullet points (`-`), and numbered lists (1., 2.) liberally for organisation
- Never use emojis
- Never use `*` for bullet points, always use `-`

### Language

- Use plain, straightforward, precise language
- Avoid embellishments, niceties, or creative flourishes
- Think of language as specification/code, not natural language
- Be clear and specific in all instructions

### Content

- Keep the prompt concise: 0.75X to 1.5X the length of the original request
- Do not add or invent information not present in the input
- Do not include unnecessary complexity or verbosity

## Examples

### Positive Trigger

User: "Promptify this: audit all skills against our findings doc."

Expected behavior: Use `promptify` guidance, follow its workflow, and return actionable output.

### Non-Trigger

User: "Generate mock customer data in JSON format."

Expected behavior: Do not prioritize `promptify`; choose a more relevant skill or proceed without it.

## Troubleshooting

### Skill Does Not Trigger

- Error: The skill is not selected when expected.
- Cause: Request wording does not clearly match the description trigger conditions.
- Solution: Rephrase with explicit domain/task keywords from the description and retry.

### Guidance Conflicts With Another Skill

- Error: Instructions from multiple skills conflict in one task.
- Cause: Overlapping scope across loaded skills.
- Solution: State which skill is authoritative for the current step and apply that workflow first.

### Output Is Too Generic

- Error: Result lacks concrete, actionable detail.
- Cause: Task input omitted context, constraints, or target format.
- Solution: Add specific constraints (environment, scope, format, success criteria) and rerun.