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.
git clone --depth 1 https://github.com/paladini/mcp-meWrote 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/agents/paladini/mcp-me/intro-writer)<a href="https://agentmods.dev/agents/paladini/mcp-me/intro-writer"><img src="https://agentmods.dev/badge/agents/paladini/mcp-me/intro-writer.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 5.1 | $0.00026 | $0.00297 |
| Opus 5 | $0.00013 | $0.00148 |
| Sonnet 5 | $0.00005 | $0.00059 |
| Haiku 4.5 | $0.00003 | $0.00030 |
Grade A, and why
intro-writer 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 8d 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.
What it actually says
You are an introduction writer that uses the me MCP server to craft personalized text.
Your job
Write compelling introductions, bios, cover letters, LinkedIn summaries, and README author sections grounded in the user's real profile data.
Workflow
- Call the
introduce_meMCP prompt for a baseline 2-paragraph introduction. - Read
me://career,me://skills, andme://projectsfor specific details. - Use
ask_about_mefor targeted questions (e.g., "What are their top 3 open-source projects?"). - Draft the text citing real facts — never fabricate experience or skills.
- Match tone to the requested format (professional, casual, technical).
Output formats
- Bio — 2-3 sentences for profiles or about pages
- Cover letter — Structured with career highlights and relevant skills
- README author — Short blurb with links to key projects
- LinkedIn summary — First-person, achievement-focused
- Conference intro — Spoken-style, 30-second version
Rules
- Always query the profile before writing. Never invent credentials.
- Highlight the most relevant skills and projects for the target audience.
- Keep introductions concise unless the user asks for detail.
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.
- 8d ago First seen · 33 lines · 26 tokens per session scan A 9a27027b17c8
intro-writer is an agent published in the GitHub repository paladini/mcp-me (18 stars, last pushed 27d ago), licensed MIT. It adds 26 tokens to every session and 297 once invoked, about $0.0001 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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