Prompt-Mini: Claude Code Plugin Intercepts Vague Prompts to Reduce Credit Waste

What Prompt-Mini Does
Prompt-mini is a Claude Code plugin that hooks into prompts before Claude executes them. When you type an idea, it intercepts the prompt, asks clarifying questions, builds a structured prompt, and then executes it immediately. The goal is to prevent vague prompts that can lead to hallucinations, wrong output, credit waste on retries, and incorrect framework usage.
Key Features
- Automatic stack detection: Reads your project files to detect your stack automatically or provides options to choose from—never asks for information it can read itself.
- Prompt interception: Intercepts every prompt before Claude Code runs a single line. Clear prompts pass through without modification.
- Comprehensive upfront questioning: Asks about stack, UI style, auth approach, and which pages to build so Claude Code never has to guess.
- Structured prompt building: Creates a 6-block structured prompt with file paths, hard stop conditions, and MUST NOT rules locked in the first 30% where attention is highest.
Problem Patterns Addressed
The plugin catches and fixes 35 credit-killing patterns including:
- No scope
- No stop conditions
- No file path
- Ghost features
- Building the whole thing in one shot
Framework Support
Supports 40+ stacks and frameworks with specific routing rules to prevent generic output. Mentioned frameworks include:
- Next.js
- Expo
- Supabase
- FastAPI
- Chrome MV3
- LangChain
- Drizzle
- Cloudflare Workers
GitHub Status
The project has reached 4300 stars on GitHub according to the developer's announcement.
📖 Read the full source: r/ClaudeAI
👀 See Also

Sonarly: AI-driven Production Alert Triage and Resolution
Sonarly connects with observability tools to triage and resolve production alerts, reducing noise and focusing on critical issues.

Keyoku Plugin Replaces OpenClaw's Static Heartbeat with Memory-Driven Autonomy
Keyoku is a free OpenClaw plugin that changes the agent's heartbeat from reading a static HEARTBEAT.md file to scanning the agent's actual memory store for stalled work, dropped commitments, conflicting information, and quiet relationships. It uses a local Go engine with SQLite + HNSW and offers three autonomy levels: observe, suggest, and act.

GuppyLM: A 9M Parameter LLM Built from Scratch for Educational Purposes
GuppyLM is a ~9M parameter language model trained from scratch on 60K synthetic conversations, using a vanilla transformer architecture with 6 layers, 384 hidden dimensions, and 6 attention heads. It trains in about 5 minutes on a free Colab T4 GPU and speaks with a fish personality focused on water, food, and tank life.

OpenClaw A2A Plugin: Direct Agent-to-Agent Messaging Over the Internet
An OpenClaw A2A plugin enables direct file and message transfer between OpenClaws and other agents over the internet without third-party services like WhatsApp or email.