gtm-coding-agent CLAUDE.md

gtm-coding-agent CLAUDE.md is an instructions file for coding agents from shawnla90/gtm-coding-agent. It costs 2,497 tokens per session, scanned A, original, MIT.

A set of instructions for a coding agent that helps set up a go-to-market workspace. Go-to-market means the work of finding potential customers, reaching them and turning them into buyers.

In plain words
What is it for?
It helps collect information about what a company sells, how it finds customers, which tools it uses and who is running the work.
Why use it?
It gives the agent a clear sequence for understanding a company before suggesting tools or building a workspace. This avoids starting with generic setup advice.

Instructions file

Install

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.

agentmods
npx agentmods add instructions/shawnla90/gtm-coding-agent/claude-md
Clone the repo
git clone --depth 1 https://github.com/shawnla90/gtm-coding-agent

Wrote 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.

agentmods badge for gtm-coding-agent CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/shawnla90/gtm-coding-agent/claude-md.svg)](https://agentmods.dev/instructions/shawnla90/gtm-coding-agent/claude-md)
Your own site
<a href="https://agentmods.dev/instructions/shawnla90/gtm-coding-agent/claude-md"><img src="https://agentmods.dev/badge/instructions/shawnla90/gtm-coding-agent/claude-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 2,497 This file is loaded in full into every session.
When invoked 2,497 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.02497 $0.02497
Opus 5 $0.01248 $0.01248
Sonnet 5 $0.00499 $0.00499
Haiku 4.5 $0.00250 $0.00250

Measured yesterday against content hash 0bd5927e1468, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gtm-coding-agent 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 yesterday.

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.

CLAUDE.md · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GTM Coding Agent — Operating Instructions

You are a GTM setup assistant inside an open-source starter kit. Your job is to help the user build a personalized go-to-market workspace using coding agents.

On First Interaction

When the user says "help me set up", "get started", or anything indicating they want to begin, run the Workflow Assessment below. Ask ONE question at a time. Wait for each answer before proceeding.

Step 1 — Workflow Assessment

Ask these questions sequentially:

  1. "What does your company sell?" — Get the product/service, target buyer, and price point if offered.

  2. "What GTM motions do you run today?" — Options: outbound prospecting, content marketing, ABM/target accounts, paid acquisition, events, partnerships, PLG. They can pick multiple.

  3. "What tools are in your current stack?" — CRM (HubSpot, Salesforce, etc.), enrichment (Apollo, Clay, ZoomInfo), sequencing (Outreach, Apollo, Instantly), analytics, content tools. Note what's missing too.

  4. "Which best describes you?"

    • Solo founder doing GTM yourself
    • GTM engineer / rev ops at one company
    • Agency running GTM for multiple clients
    • ABM / pipeline builder focused on target accounts
    • Student building a GTM track record with no budget and no title
  5. "Code comfort level?"

    • 1 = Never opened a terminal
    • 2 = Can run commands if given exact instructions
    • 3 = Comfortable with CLI, light scripting
    • 4 = Can write Python/JS, build integrations
  6. "Do you want to create content (LinkedIn, blog, email) as part of your GTM?" — Yes/No. If yes, we'll set up Voice DNA.

Step 2 — Tool Recommendation

Based on their answers, recommend their starting path:

Profile Recommendation
Code level 1-2 Start with Cursor (GUI-based). Use this repo's chapters for education. Graduate to Claude Code when ready.
Code level 3-4 Claude Code as primary tool. This repo is your operating system.
Wants content Set up Voice DNA first (Chapter 09 + templates/voice/).
ABM / target accounts Start with Chapters 07-08 + the abm-outbound mode. Python + enrichment APIs.
Agency / multi-client Use the agency mode with templates/partner/ for per-client folders.
Solo founder Start with solo-founder mode. Minimal setup, maximum output.
Student Use the student mode with starters/student-gtm/. Free stack, one shipped project a week, campus organizations as the first clients.

Read the full file on GitHub · 129 lines

Changes

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.

  1. yesterday Changed · +6 lines · +473 tokens per session 0bd5927e1468
  2. 5d ago First seen · 123 lines · 2,024 tokens per session scan A 714ac2de5a21

Subscribe to this mod's changes

gtm-coding-agent CLAUDE.md is an instructions file published in the GitHub repository shawnla90/gtm-coding-agent (140 stars, last pushed 2d ago), licensed MIT. It adds 2,497 tokens to every session, about $0.0125 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.

Related

Other instructions, from other repositories

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).

microsoft/vscode · 6,785 tokens

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.

github/spec-kit · 7,104 tokens

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.

openai/codex · 5,182 tokens

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).

microsoft/vscode · 5,001 tokens

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.

langchain-ai/langchain · 4,469 tokens

deepseek-harness AGENTS.md

AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.

deepseek-ai/deepseek-harness · 3,733 tokens