Borrowing it
Nothing to install: this file belongs to MattArtzAnthro/gephi-ai. 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/MattArtzAnthro/gephi-ai/main/GEMINI.mdgit clone --depth 1 https://github.com/MattArtzAnthro/gephi-aiWrote 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/mattartzanthro/gephi-ai/gemini-md)<a href="https://agentmods.dev/instructions/mattartzanthro/gephi-ai/gemini-md"><img src="https://agentmods.dev/badge/instructions/mattartzanthro/gephi-ai/gemini-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 5.1 | $0.00819 | $0.00819 |
| Opus 5 | $0.00409 | $0.00409 |
| Sonnet 5 | $0.00164 | $0.00164 |
| Haiku 4.5 | $0.00082 | $0.00082 |
Grade A, and why
gephi-ai 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 7d 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.
This is a copy
100% identical to gephi-ai AGENTS.md — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Gephi AI — Instructions for AI Coding Agents
This repository ships an MCP server (gephi-ai on PyPI) that controls a
running Gephi Desktop through a local HTTP API provided by the Gephi AI plugin
(gephi-ai-<version>.nbm), plus a portable skill that teaches network-analysis
practice. The server exposes 113 tools whose names start with gephi_
(Claude Code shows them as mcp__gephi-mcp__gephi_*).
When a user asks to build, analyze, lay out, style, or export a network, follow this chain:
-
MCP tools present (tool names start with
gephi_): use them. Callgephi_health_checkfirst. It confirms that Gephi Desktop is running with the plugin installed, reports the plugin and server versions, and says whether an update is available. If it fails, tell the user to start Gephi (with the plugin installed from the Releases page) and stop; nothing else works without it. -
Your agent supports MCP but the server is not registered: the user can add it with one command. The launcher is the same everywhere; only the registration syntax differs.
claude mcp add gephi-mcp -- uvx gephi-ai codex mcp add gephi-mcp -- uvx gephi-ai gemini mcp add -s user gephi-mcp uvx gephi-aiuvxfetches the currentgephi-airelease from PyPI on first run and caches it. Any other MCP client: point it atuvx gephi-aiover stdio. -
No MCP at all: there is no fallback. The server talks to Gephi Desktop on
127.0.0.1:8080, so it has to run on the machine where Gephi runs. Say so, and point the user at the README's Install section.
The skill
plugins/claude-code/skills/gephi/ is a self-contained skill folder (SKILL.md plus
references/): tool reference, layout guide, statistics guide, filtering,
claim verification, text networks, and how to read a network map. It is
written for any agent that reads the portable skill format. Install it by
copying the folder into your agent's skills directory (~/.codex/skills/,
~/.cursor/skills/, ~/.copilot/skills/, or .agents/skills/ in a project);
Claude Code users get it through the plugin, together with slash commands and
subagents that only Claude Code can run.
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.
- 7d ago First seen · 65 lines · 819 tokens per session scan A f0a137811719
gephi-ai GEMINI.md is an instructions file published in the GitHub repository MattArtzAnthro/gephi-ai (21 stars, last pushed 5d ago), licensed Apache-2.0. It adds 819 tokens to every session, about $0.0041 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to gephi-ai AGENTS.md, differing in 0 lines, and is treated as a copy.
Other instructions, from other repositories
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.