Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add instructions/ianphil/promptbin/claude-mdgit clone --depth 1 https://github.com/ianphil/promptbinWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/ianphil/promptbin/claude-md)<a href="https://agentmods.dev/instructions/ianphil/promptbin/claude-md"><img src="https://agentmods.dev/badge/instructions/ianphil/promptbin/claude-md.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01124 | $0.01124 |
| Opus 5 | $0.00562 | $0.00562 |
| Sonnet 5 | $0.00225 | $0.00225 |
| Haiku 4.5 | $0.00112 | $0.00112 |
Grade A, and why
promptbin CLAUDE.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
PromptBin is the easiest way to run a Model Context Protocol (MCP) server with full prompt management capabilities. It's designed as a reference implementation and example for MCP server integration.
Primary use case: uv add promptbin && uv run promptbin
Modes:
- Both Mode (default): MCP server + auto-launching web interface
- MCP Server Mode: MCP protocol only with
--mcpflag - Web Mode: Web interface only with
--webflag
Development Commands
For PyPI distribution (recommended):
# Install from PyPI
uv add promptbin
# Run both MCP server + web interface (primary use case)
uv run promptbin
# Run only MCP server
uv run promptbin --mcp
# Run only web interface
uv run promptbin --web
# Setup verification
uv run promptbin-setup
# Install Dev Tunnels CLI
uv run promptbin-install-tunnel
For development:
# Clone and develop
git clone https://github.com/ianphil/promptbin
cd promptbin
uv sync
uv run promptbin
Architecture Overview
Core Components
- Flask Web App (
app.py): HTMX-powered interface on localhost:5000 - MCP Server (
mcp_server.py): Model Context Protocol integration with auto-lifecycle management - File-Based Storage: JSON files in
~/promptbin-data/{category}/{prompt_id}.json - Microsoft Dev Tunnels: Secure sharing with automatic security protections
Data Organization
~/promptbin-data/
├── coding/ # Development-related prompts
├── writing/ # Content creation prompts
├── analysis/ # Data analysis prompts
└── shares.json # Share token management
Key Design Principles
- Local-First: All data stored locally by default
- Zero Database: File-based storage only
- HTMX Integration: No full page reloads, dynamic interactions
- Security by Design: Rate limiting (5 attempts per IP kills tunnel)
- Template Variables: Support for
{{variable}}syntax with special highlighting
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 135 lines · 1,124 tokens per session scan A 695fb0a79de6
promptbin CLAUDE.md is an instructions file published in the GitHub repository ianphil/promptbin (0 stars, last pushed 8mo ago), licensed MIT. It adds 1,124 tokens to every session, about $0.0056 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other instructions, from other repositories
apex-accelerator vendor-prompting.instructions.md
Vendor prompting best-practice rules for Anthropic Claude and OpenAI GPT-5.6-Terra agents and prompts. Each rule cites a rule ID in the vendor-prompting skill rules.json registry. Validator: npm run lint:vendor-prompting.
Awesome-Prompt-Engineering AGENTS.md
Instructions for natnew/Awesome-Prompt-Engineering, covering agents.md, repository north star, agent role, trust boundary and read order.
pydantic-ai-gepa AGENTS.md
AGENTS.md instructions for indexedlabs/pydantic-ai-gepa, covering repository guidelines, mighty workflow, project structure & module organization, build, test, and development commands and coding style & naming conventions.
SkillOpt AGENTS.md
Instructions for mitkox/SkillOpt, covering agent instructions for skillopt, project identity, default example workflow, documentation expectations and repo hygiene.
vscode-copilot-chat model-prompts.instructions.md
Model-specific prompt authoring and registry guidelines.
comfy-prompt-studio AGENTS.md
Instructions for yxhpy/comfy-prompt-studio, covering agents.md - ai 代理配置文档, ai 提供商, 1. ollama (默认), 2. gemini and 提示词生成服务.