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.
npx agentmods add instructions/googlecloudplatform/agent-starter-pack/gemini-mdgit clone --depth 1 https://github.com/GoogleCloudPlatform/agent-starter-packWhat 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 | $0.05853 | $0.05853 |
| Opus 5 | $0.02926 | $0.02926 |
| Sonnet 5 | $0.01171 | $0.01171 |
| Haiku 4.5 | $0.00585 | $0.00585 |
Grade A, and why
agent-starter-pack 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 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.
How it starts
The opening of the file, as written. The whole thing — 723 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Starter Pack - AI Coding Agent Guide
Scope: This document is for AI coding agents contributing to the Agent Starter Pack repository itself (the template generator). For guidance on working with generated projects, see llm.txt.
This document provides essential guidance, architectural insights, and best practices for AI coding agents tasked with modifying the Google Cloud Agent Starter Pack. Adhering to these principles is critical for making safe, consistent, and effective changes.
Core Principles for AI Agents
- Preserve and Isolate: Your primary objective is surgical precision. Modify only the code segments directly related to the user's request. Preserve all surrounding code, comments, and formatting. Do not rewrite entire files or functions to make a small change.
- Follow Conventions: This project relies heavily on established patterns. Before writing new code, analyze the surrounding files to understand and replicate existing conventions for naming, templating logic, and directory structure.
- Template-First Mindset: ASP is a template generator. The CLI should remain lean with good defaults. Most features belong in templates, not CLI code.
- Search Comprehensively: A single change often requires updates in multiple places. When modifying configuration, variables, or infrastructure, you must search across the entire repository, including:
agent_starter_pack/base_templates/(core templates by language)agent_starter_pack/deployment_targets/(environment-specific overrides).github/and.cloudbuild/(CI/CD workflows)docs/(user-facing documentation)
Project Architecture Overview
4-Layer Template System
Template processing follows this hierarchy (later layers override earlier ones):
| Layer | Directory | Purpose |
|---|---|---|
| 1. Base | agent_starter_pack/base_templates/<language>/ |
Core Jinja scaffolding (Python, Go, more coming) |
| 2. Deployment | agent_starter_pack/deployment_targets/ |
Environment overrides (cloud_run, gke, agent_engine) |
| 3. Frontend | agent_starter_pack/frontends/ |
UI-specific files |
| 4. Agent | agent_starter_pack/agents/*/ |
Agent-specific logic and configurations |
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.
- yesterday First seen · 723 lines · 5,853 tokens per session scan A e256e6fdc0fd
agent-starter-pack GEMINI.md is an instructions file published in the GitHub repository GoogleCloudPlatform/agent-starter-pack (6,547 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 5,853 tokens to every session, about $0.0293 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
adk-go AGENTS.md
Instructions for google/adk-go, covering agents.md, project overview, setup & core commands, definition of done and repository layout.
adk-go CLAUDE.md
Instructions for google/adk-go: See AGENTS.md for project context, commands, and contribution guidelines for AI coding agents.
langgraphjs AGENTS.md
Instructions for langchain-ai/langgraphjs, covering repository instructions and corridor security analysis.
codedb AGENTS.md
Instructions for justrach/codedb, covering codedb agent guidelines, what codedb is (and isn't), review guidelines, pre-merge verification and security-sensitive areas.
ai AGENTS.md
AGENTS.md instructions for vercel/ai, covering agents.md, project overview, repository structure, key directories and core package dependencies.
ai CLAUDE.md
Claude Code instructions for vercel/ai, a project described as: The AI Toolkit for TypeScript. From the creators of Next.js, the AI SDK is a free open-source library for building AI-powered applications and agents.