Gemini CLI is a terminal-based AI agent that lets developers interact with Google Gemini models and use tools for tasks such as file operations, shell commands, web fetching, and search. Developers use it from the command line, and the catalogue add-ons extend its workflows and integrations.
Borrowing it
Nothing to install: this file belongs to google-gemini/gemini-cli. 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/google-gemini/gemini-cli/main/.gemini/commands/code-guide.tomlgit clone --depth 1 https://github.com/google-gemini/gemini-cliWrote 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/commands/google-gemini/gemini-cli/code-guide)<a href="https://agentmods.dev/commands/google-gemini/gemini-cli/code-guide"><img src="https://agentmods.dev/badge/commands/google-gemini/gemini-cli/code-guide/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/commands/google-gemini/gemini-cli/code-guide"><img src="https://agentmods.dev/badge/commands/google-gemini/gemini-cli/code-guide.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 | $0.00000 | $0.00445 |
| Opus 5.5 | $0.00000 | $0.00178 |
| Sonnet 5.5 | $0.00000 | $0.00089 |
| Haiku 4.5 | $0.00000 | $0.00044 |
Grade A, and why
code-guide 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 1mo 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- code-guide — 100% identical, 0 lines differ
- code-guide — 100% identical, 0 lines differ
- code-guide — 91% identical, 17 lines differ
How it starts
The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
description = "Answer questions about the Gemini CLI codebase with explanations and code snippets."
prompt = """
Mission: Explain the Gemini CLI Codebase
Your primary task is to help a new engineer understand the Gemini CLI codebase by answering their questions about architecture, specific functions, and project structure.
Objective:
Your primary task is to help a new engineer understand the Gemini CLI codebase. You will answer their questions about architecture, specific functions, and project structure by providing clear explanations grounded in the actual source code.
Instructions:
-
Always Consult "Getting Started": Before providing any answer, you MUST first consult the getting started documentation located in the
docs/get-startedfolder. -
Consult Documentation and Specific Folders: Before answering, you MUST first consult any relevant documentation within the
docsfolder. Base all your code-related answers exclusively on the contents of the following folders:integration-tests,packages, andscripts. -
Provide Specific Code Examples: Always support your explanations with relevant code snippets. You MUST include the full file path (e.g.,
packages/gemini/core.py) so the user can easily locate the code. -
Explain the "Why": Go beyond simply showing the code. Explain the design choices and the rationale behind the implementation. Discuss why a particular approach was taken and what trade-offs might have been considered.
-
Suggest a Learning Path: Where appropriate, guide the user by suggesting related files to examine next or other relevant concepts to explore within the codebase to deepen their understanding.
-
Handle Unknowns Gracefully: If the answer cannot be found in the provided folders and documentation, you must state that the information is unavailable and ask the user for clarification. Do not invent answers or speculate.
Constraints:
- No Hallucination: If the answer cannot be found in the provided context, you must state that the information is unavailable and ask the user for clarification. Do not invent answers or speculate.
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.
- 1mo ago First seen · 40 lines · 0 tokens per session scan A d1b7eacb0d9f
code-guide is a command published in the GitHub repository google-gemini/gemini-cli (107,525 stars, last pushed today), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 445 tokens. 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 2026-09-02.
Other commands, from other repositories
maestro-learn
User-invoked learning toolkit — guided reading, investigation, pattern extraction, or second opinions. Manual /maestro-learn only; NEVER auto-invoke for code exploration or analysis — route those intents to the analyze step via /maestro-next.
docs
Command "docs" from getsentry/toolkit, covering examples, ask a documentation question and search the documentation index.
maestro-odyssey
Long-running iterative cycle — one entry, seven modes (debug|improve|planex|review|security|defensive|ui). Shared archaeology/audit → fix → verify → generalize → discover → persist skeleton with mode-specific dimensions. User-invoked campaign entry; single-step fixes route via /maestro-next.
dispatch
Every task description uses structured format for clarity.
maestro-companion
Quick execution for small tasks — minimal run lifecycle (start + done) with evidence recording. Full LLM capability, scoped to mechanically clear tasks.
maestro-update
Detect version, preview changes, apply workflow upgrades.