By tolibear
Optimize AI prompts using +ask, +deep, +web modifiers: clarify ambiguities with targeted questions, research codebase for project context and patterns, or fetch web best practices and docs. Get refined prompt in code block, copied to clipboard, with explanation.
Optimize your prompts. One command, stackable modifiers.
Works in Claude Code and molt.bot.
Claude Code:
claude plugin install promptify@tolibear
Molt.bot:
npx molthub install promptify
/promptify [+modifiers] your prompt here
| Modifier | Effect |
|---|---|
+ask | Ask clarifying questions first |
+deep | Explore codebase for context |
+web | Search web for best practices |
Stack them:
/promptify +ask+deep+web Build a payment system
Skip modifiers - promptify auto-detects what's needed:
| Your Prompt | Auto-Triggers |
|---|---|
| "Add auth to our API" | Codebase research |
| "Help me with this thing" | Clarifying questions |
| "Best practices for React hooks" | Web search |
| "Write a landing page" | Direct optimization |
Before:
Build a payment system
After:
You are a senior backend engineer with Stripe integration experience.
<task>
1. Analyze payment requirements (one-time vs recurring, currencies, refunds)
2. Design the data model (customers, payments, subscriptions)
3. Implement Stripe integration with proper error handling
4. Add webhook handlers for payment events
5. Include idempotency keys for safe retries
</task>
<constraints>
- Use Stripe API v2024-01
- Handle card failures gracefully with user-friendly messages
- Log all payment events for debugging
- Never store raw card numbers
</constraints>
<output>
Working implementation with:
- Payment service class
- Webhook controller
- Database migrations
- Test coverage for happy path and failure cases
</output>
v3.0.0 - Rewritten for Claude 4.x. 65% shorter (163→57 lines). Progressive disclosure. Contract-first design.
MIT
Uses power tools
Uses Bash, Write, or Edit tools
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Turn broad Codex and Claude Code work into pressured /goal runs with oracles, local boards, receipts, and verification.
npx claudepluginhub tolibear/promptify-skillIntelligent prompt optimization: injects the right context at the right moment so Claude lands a better first output. Clarifies vague prompts with research-based questions, plus targeted nudges for approach selection, plan readability, workflow routing, background execution, subagent routing, output readability, user-decision questions, and plan-mode assessment
DevsForge Enterprise Prompt Optimization Architect delivering strategic prompt engineering methodologies, AI interaction optimization, and communication excellence frameworks
Tools for crafting, reviewing, analyzing, refining, and optimizing LLM prompts for clarity, precision, goal effectiveness, and token efficiency
Meta-cognition: refine input through brainstorming, refine output through challenge and condensed communication mode.
Improve and test AI prompts for better Claude Code interactions
Testany AI/LLM 工具集:Prompt 优化