prompt-generator

Original：🇺🇸 English

Translated

Meta-prompting skill that creates well-structured, verifiable, low-hallucination prompts for any use case. Use when the user wants to create, refine, or improve a prompt — including system prompts, role prompts, task prompts, or any AI instruction set. Triggers on requests like "create a prompt for...", "help me write a prompt", "refine this prompt", "make a better prompt for...", or "generate a prompt that...".

2installs

Sourcehoangvantuan/claude-plugin

Added on2026-02-13

NPX Install

npx skill4agent add hoangvantuan/claude-plugin prompt-generator

SKILL.md Content

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Prompt Generator

Create high-quality, structured prompts using meta-prompting best practices: task decomposition, expert personas, iterative verification, and hallucination minimization.

Workflow

Phase 1: Gather Requirements

Ask the user (one at a time, maximum 3 questions):

Goal: "What is the primary goal or role of the system you want to create?"
Output: "What specific outputs do you expect? (format, length, style)"
Accuracy: "How should it handle uncertainty? (disclaim, ask for sources, or best-effort)"

Skip questions when answers are obvious from context. Minimize friction.

Phase 2: Decompose (if complex)

For complex requests, break into subtasks and assign expert personas:

Expert Writer — for copywriting, narrative, tone
Expert Analyst — for data, logic, verification
Expert Python — for code generation, computation
Expert [Domain] — for specialized knowledge

Each expert gets complete, self-contained instructions (no shared memory between experts).

Use "fresh eyes" — never assign the same expert to both create AND validate.

Phase 3: Generate the Prompt

Consolidate into a single, cohesive prompt. Include all applicable sections, omit sections not relevant to the use case:

## Role
[Short, direct role definition. Emphasize verification and disclaimers for uncertainty.]

## Context
[User's task, goals, background. Summarize clarifications from user input.]

## Instructions
1. [Stepwise approach, including how to verify data]
2. [Expert assignments if needed]
3. [How to handle uncertain or missing information]

## Constraints
[Limitations: style, length, references, disclaimers]

## Output Format
[Exact structure of the final output — bullets, paragraphs, code blocks, etc.]

## Reasoning
[OPTIONAL — include only if the user wants chain-of-thought or rationale.
Otherwise, omit to keep the prompt concise.]

## Examples
[OPTIONAL — include when user provides input/output pairs or when examples
significantly improve output quality. Omit for straightforward tasks.]

Section inclusion guide:

Role, Context, Instructions, Constraints, Output Format — always include
Reasoning — include only for complex analytical or multi-step tasks
Examples — include when output quality depends on seeing concrete patterns

Phase 4: Verify and Deliver

Self-review: check for ambiguous instructions, missing constraints, or sections that could cause hallucination
If experts were used, note their review
Present the final prompt, organized and easy to follow
Offer to iterate if the user wants adjustments

Principles

Decompose complex tasks into smaller subtasks
Fresh eyes — separate creation from validation
Never guess — disclaim uncertainty, ask for data
Concise — only ask clarifying questions when critical
Iterative — verify before delivering, offer refinement
Section-aware — include only relevant sections, omit what doesn't apply