promptify

name	promptify
description	Transform user requests into detailed, precise prompts for AI models. Use when users say 'promptify', 'promptify this', 'rewrite this prompt', 'make this prompt better/more specific', or explicitly request prompt engineering or improvement of their request for better AI responses.
allowed-tools	["Bash","Read","Write","Edit","Grep","Glob","Agent","AskUserQuestion"]
metadata	{"category":"assistant","tags":["agent","prompt-engineering","clarity","specification","rewriting"],"status":"ready","version":10,"triggers":{"positive":["Promptify this: audit all skills against our findings doc.","Rewrite this prompt for better results.","Make this prompt more specific.","Can you improve this prompt?"],"negative":["Generate mock customer data in JSON format.","Write a React component for a login form.","Fix the bug in the checkout flow."]},"guidance":"`promptify` transforms user requests into precise, structured prompts.\nOnly activate when the user explicitly requests prompt improvement or rewriting.\nDo not activate for direct task execution requests."}

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

User-input rule: Any time this skill needs a decision, preference, or clarification from the user, it MUST use the AskUserQuestion tool with structured options — never free-text prose questions. This applies to the clarifying-questions path in step 2 and the delivery choice in step 7.

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. Decide Output Mode

Based on the analysis, choose how to proceed:

• Request is clear and complete — produce direct rewritten prompt
• 1-2 minor gaps — fill with marked [Assumption: X] placeholders and proceed
• Major gaps (audience, scope, tech stack unknown) — ask clarifying questions via the AskUserQuestion tool (structured options, not prose) before rewriting
• Multiple distinct objectives — split into separate prompts

3. 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. For common prompt types, start from the skeletons in references/prompt-blueprints.md.

4. Draft

Apply the rules in rules/ to sharpen the prompt:

• Replace vague terms with measurable requirements
• Surface missing information as placeholders or questions (see rules/clarity-surface-missing-info.md)
• Include success criteria defining what a good answer must include or avoid
• Mark any assumptions explicitly
• Add examples only where the desired output is genuinely ambiguous
• Specify exact format (headings, bullet style, length)
• Break complex tasks into numbered sequential steps

5. Self-Check

Before delivery, verify the draft against the rule checklist (see rules/quality-self-check.md):

• No vague qualifiers (be-specific)
• Missing info surfaced (surface-missing-info)
• Success criteria defined (include-success-criteria)
• Assumptions marked (state-assumptions)
• Format specified (specify-format)
• Examples only if ambiguous (examples-only-when-needed)
• No filler or politeness (minimal-fluff)

If any check fails, fix the violation and re-check. Stop after the checklist passes or after two refinement passes (whichever comes first).

6. Output

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

7. Deliver

After presenting the prompt, use the AskUserQuestion tool (not a prose list) to ask the user how to proceed, offering these 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.