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# nidhinjs/prompt-master
## Metadata
- **Stars:** 4,992
- **License:** MIT
- **Last pushed:** 2026-03-31
- **Description:** A Claude skill that writes the accurate prompts for any AI tool. Zero tokens or credits wasted. Full context and memory retention.
## Archetype: Specialization Process (prompt-engineering domain)
## Structure
- `SKILL.md` — Complete prompt engineering skill with tool-routing logic
- `references/` — `templates.md` and `patterns.md` for category-specific templates
## Extractable Value
### As a Babysitter Process: `specializations/shared/prompt-engineering`
The SKILL.md contains a well-structured prompt engineering methodology:
1. **9-dimension intent extraction framework** — Task, Target tool, Output format, Constraints, Input, Context, Audience, Success criteria, Examples. Each dimension marked as critical/conditional.
2. **Tool-specific routing logic** — Detailed prompting guidance for 16+ tools/models:
- Claude (4.x), ChatGPT/GPT-5.x, o3/o4-mini reasoning models, Gemini 2.x/3, Qwen 2.5/3, Ollama, Llama/Mistral, DeepSeek-R1, MiniMax M2.7/M2.5, Claude Code, Antigravity, Cursor/Windsurf, Cline, GitHub Copilot
3. **Anti-pattern enforcement** — Hard rules against techniques that cause fabrication in single-prompt execution (Mixture of Experts, Tree of Thought, Graph of Thought, etc.)
4. **Model-specific constraints** — e.g., "NEVER add CoT to reasoning-native models", "Claude Opus 4.x over-engineers by default"
### Key Differentiators
- The tool-routing approach is unique — maps target tool to specific prompting strategy
- Anti-fabrication rules are concrete and actionable (not vague "be careful" advice)
- The 9-dimension intent extraction is a reusable analysis framework
- Output format is strictly enforced: copyable prompt block + target + optimization note
### Process Mapping
Would map well to a babysitter process with:
- Breakpoint for tool identification when ambiguous
- Task for intent extraction across 9 dimensions
- Tool-routing logic as branching in the process
- Output formatting as final stage
## Processes
### 1. Advanced Prompt Engineering Methodology
- **Source**: SKILL.md 9-dimension intent extraction framework and tool-routing logic
- **Placement**: `specializations/shared/advanced-prompt-engineering.js`
- **Description**: Comprehensive prompt engineering process: extract intent across 9 dimensions (task, target tool, output format, constraints, input, context, audience, success criteria, examples) → apply tool-specific routing logic for 16+ AI models → enforce anti-fabrication rules → generate optimized prompt with target tool and optimization notes.
## Plugin Ideas
- **Prompt Engineering Suite**: Babysitter marketplace plugin that provides advanced prompt engineering capabilities with tool-routing logic and anti-pattern enforcement for optimal AI model communication.
## Library Mapping
| Extractable Process | Library Status | Action | Existing Path | Target Placement |
|-------------------|----------------|--------|---------------|------------------|
| Advanced Prompt Engineering Methodology | NEW | 9-dimension intent extraction with tool-specific routing for 16+ AI models | - | specializations/shared/advanced-prompt-engineering.js |
| Tool-Specific Routing Logic | NEW | Detailed prompting guidance mapped to specific AI tools and models | - | specializations/shared/tool-specific-routing-logic.js |
| Anti-Fabrication Pattern Enforcement | NEW | Hard rules against techniques that cause hallucination in single-prompt execution | - | specializations/shared/anti-fabrication-pattern-enforcement.js |
| Model-Specific Constraint Systems | NEW | Model-specific prompting constraints (e.g., no CoT for reasoning models, over-engineering prevention) | - | specializations/shared/model-specific-constraint-systems.js |
## Plugin Marketplace Mapping
| Plugin Idea | Marketplace Status | Action | Existing Plugin | Target Placement |
|-------------|-------------------|--------|-----------------|------------------|
| Prompt Engineering Suite | NEW | Advanced prompt engineering with tool routing, anti-pattern enforcement, and optimization | - | plugins/a5c/marketplace/plugins/prompt-engineering-suite/ |
## Classification Rationale
Cross-domain (works for any AI tool/model), so fits in `specializations/shared/`. The tool-routing logic and anti-fabrication rules are unique contributions not found in the current process library.
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