Borrowing it
Nothing to install: this file belongs to gtmagents/gtm-agents. 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/gtmagents/gtm-agents/main/CLAUDE.mdgit clone --depth 1 https://github.com/gtmagents/gtm-agentsWrote 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/gtmagents/gtm-agents/claude-md)<a href="https://agentmods.dev/instructions/gtmagents/gtm-agents/claude-md"><img src="https://agentmods.dev/badge/instructions/gtmagents/gtm-agents/claude-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/gtmagents/gtm-agents/claude-md"><img src="https://agentmods.dev/badge/instructions/gtmagents/gtm-agents/claude-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 | $0.03521 | $0.03521 |
| Opus 5 | $0.01760 | $0.01760 |
| Sonnet 5 | $0.00704 | $0.00704 |
| Haiku 4.5 | $0.00352 | $0.00352 |
Grade A, and why
gtm-agents 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 10d 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 — 464 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md - GTM Agents
Project Overview
GTM Agents is an AI-powered automation platform for Go-To-Market teams. It provides 67 specialized plugins with 203 AI agents, 243 business skills, and 20+ workflow orchestrators designed for sales, marketing, growth, customer success, and revenue operations teams.
Mission: Save GTM professionals 15+ hours per week on repetitive busywork by automating prospecting, content creation, analytics, and campaign orchestration.
Value Proposition: Average value saved: $25,000+ per user per year.
Repository Structure
gtm-agents/
├── .claude-plugin/
│ └── marketplace.json # Plugin marketplace definition (67 plugins)
├── plugins/ # 67 GTM-focused plugins
│ └── [plugin-name]/
│ ├── agents/ # Specialized AI agents (.md files)
│ ├── commands/ # Tools and workflows (.md files)
│ └── skills/ # Modular knowledge packages (SKILL.md)
├── workspace/ # Agent working directory (see below)
├── docs/ # Documentation
│ ├── agent-reference.md # All 203 agents
│ ├── business-skills.md # All 243 skills
│ ├── plugin-reference.md # Plugin catalog
│ ├── usage-guide.md # Commands and workflows
│ └── use-cases/ # Real-world examples
├── scripts/ # Validation and scaffolding
│ ├── scaffold_asset.py # Create new agents/commands/skills
│ ├── validate_marketplace.py # Marketplace validation
│ └── smoke_test_plugins.py # Plugin smoke tests
├── templates/ # Asset templates
│ ├── agent.md
│ ├── command.md
│ └── skill.md
├── examples/ # Example implementations
└── inventory.json # Complete repository state
Workspace Structure
The workspace/ directory provides a consistent folder structure for all agent operations. All agent outputs should be saved to the appropriate workspace folder.
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.
- 10d ago First seen · 464 lines · 3,521 tokens per session scan A 811235018369
gtm-agents CLAUDE.md is an instructions file published in the GitHub repository gtmagents/gtm-agents (398 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 3,521 tokens to every session, about $0.0176 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.
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).
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.
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.