Borrowing it
Nothing to install: this file belongs to lusha-oss/lusha-mcp-plugin. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lusha-oss/lusha-mcp-plugin/master/GEMINI.mdgit clone --depth 1 https://github.com/lusha-oss/lusha-mcp-pluginWrote 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/lusha-oss/lusha-mcp-plugin/gemini-md)<a href="https://agentmods.dev/instructions/lusha-oss/lusha-mcp-plugin/gemini-md"><img src="https://agentmods.dev/badge/instructions/lusha-oss/lusha-mcp-plugin/gemini-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/lusha-oss/lusha-mcp-plugin/gemini-md"><img src="https://agentmods.dev/badge/instructions/lusha-oss/lusha-mcp-plugin/gemini-md.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00955 | $0.00955 |
| Opus 5.5 | $0.00382 | $0.00382 |
| Sonnet 5.5 | $0.00191 | $0.00191 |
| Haiku 4.5 | $0.00096 | $0.00096 |
Grade A, and why
lusha-mcp-plugin GEMINI.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 11d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lusha for Gemini CLI
This extension connects Gemini to Lusha's B2B intelligence platform through the Lusha MCP server. Use it to enrich contacts, build prospect lists, prioritize accounts by buying signals, and expand target lists with lookalikes — always surfacing verified direct and mobile phone numbers.
When to use it
Activate Lusha when the user wants to:
- Look up a person — get verified phones, email, and company context.
→ use the
enrich-contactworkflow. - Build a list from an ICP — describe a persona/segment in plain English and
return a filtered, enriched lead list. → use the
prospectworkflow. - Start from a buying signal — funding rounds, hiring surges, job changes —
and reach the right decision makers. → use the
signal-prospectworkflow. - Expand from references — give 5+ example companies or contacts and get a
matched lookalike list. → use the
lookalike-prospectworkflow. - Decide who to go after — no criteria, just "who should I work next?";
get recommended accounts with reasons, then their decision makers.
→ use the
work-my-accountsworkflow. - Prioritise a list the user already has — score a CSV, domains or a
Workspace table by ICP fit and buying signals into A/B/C tiers.
→ use the
score-my-listworkflow. - Follow up on website visitors — hot companies on the user's own site,
then their decision makers. → use the
website-visitor-followupworkflow. - Set up the ICP — build a Lusha Target Profile one question at a time.
→ use the
set-up-my-icpworkflow. - Save or export a result — to a Lusha Workspace table or the user's CRM.
→ use the
save-or-exportworkflow. - Capture positioning for outreach — what the user sells, to whom, with what
proof, and against which competitors, saved as a reusable brief.
→ use the
outreach-researchworkflow. - Draft outreach — personalized Email 1 (optionally Emails 2–3 and LinkedIn
messages) for contacts the user already has, from that brief plus Lusha
signals. → use the
outreach-sequenceworkflow.
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.
- 11d ago Changed · +16 lines · +267 tokens per session 0da099ae0342
- 24d ago Changed · +12 lines · +204 tokens per session 41889dd2cb01
- 2mo ago First seen · 44 lines · 484 tokens per session scan A 6e8fa82f3060
lusha-mcp-plugin GEMINI.md is an instructions file published in the GitHub repository lusha-oss/lusha-mcp-plugin (4 stars, last pushed 2d ago), licensed MIT. It adds 955 tokens to every session, about $0.0038 per session on Opus 5.5. 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.
lusha-mcp-plugin GEMINI.md compared with instructions from other repositories
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|---|---|---|---|---|---|---|---|
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