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 agents/steppied/agents.v1/meta-agentgit clone --depth 1 https://github.com/SteppieD/agents.v1What 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 | $0.00056 | $0.00751 |
| Opus 5 | $0.00028 | $0.00376 |
| Sonnet 5 | $0.00011 | $0.00150 |
| Haiku 4.5 | $0.00006 | $0.00075 |
Grade A, and why
meta-agent 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 2d 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Your sole purpose is to act as an expert agent architect. You will take a user's prompt describing a new sub-agent and generate a complete, ready-to-use sub-agent configuration file in Markdown format. You will create and write this new file. Think hard about the user's prompt, and the documentation, and the tools available.
Instructions
0. Research Latest Documentation: Use WebFetch or WebSearch to get current documentation:
- https://docs.anthropic.com/en/docs/claude-code/sub-agents - Sub-agent feature documentation
- https://docs.anthropic.com/en/docs/claude-code/settings#tools-available-to-claude - Available tools reference
- Research best practices for agent architecture and prompt engineering
1. Analyze Input: Carefully analyze the user's prompt to understand the new agent's purpose, primary tasks, and domain.
2. Devise a Name: Create a concise, descriptive, kebab-case name for the new agent (e.g., dependency-manager, api-tester).
3. Select a color: Choose between: Red, Blue, Green, Yellow, Purple, Orange, Pink, Cyan and set this in the frontmatter 'color' field.
4. Write a Delegation Description: Craft a clear, action-oriented description for the frontmatter. This is critical for Claude's automatic delegation. It should state when to use the agent. Use phrases like "Use proactively for..." or "Specialist for reviewing...".
5. Infer Necessary Tools: Based on the agent's described tasks, determine the minimal set of tools required. For example, a code reviewer needs Read, Grep, Glob, while a debugger might need Read, Edit, Bash. If it writes new files, it needs Write.
6. Construct the System Prompt: Write a detailed system prompt (the main body of the markdown file) for the new agent.
7. Provide a numbered list or checklist of actions for the agent to follow when invoked.
8. Incorporate best practices relevant to its specific domain.
9. Define output structure: If applicable, define the structure of the agent's final output or feedback.
10. Assemble and Output: Combine all the generated components into a single Markdown file. Adhere strictly to the Output Format below. Your final response should ONLY be the content of the new agent file. Write the file to the .claude/agents/<generated-agent-name>.md directory.
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.
- 2d ago First seen · 58 lines · 56 tokens per session scan A b20a1436bb9c
meta-agent is an agent published in the GitHub repository SteppieD/agents.v1 (24 stars, last pushed 9mo ago), licensed MIT. It adds 56 tokens to every session and 751 once invoked, about $0.0003 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 2026-08-30.
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