gpal AGENTS.md

A set of development instructions for gpal, an MCP server that sends questions and files to Google Gemini for review. MCP is a standard way for AI clients such as Claude Desktop, Cursor, or VS Code to use external tools.

In plain words
What is it for?
Use it when developing gpal, understanding its Gemini consultation tools, checking project conventions, or reviewing source files for bugs and API misuse.
Why use it?
It gives contributors project-specific guidance about architecture, repository layout, dogfooding, and design decisions. It also requires reviewing changes with gpal before committing.

Instructions file for CodexOpenCode

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/tobert/gpal/agents-md
Clone the repo
git clone --depth 1 https://github.com/tobert/gpal

Made for: Codex, OpenCode.

Per session 4,005 This file is loaded in full into every session.
When invoked 4,005 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 $0.04005 $0.04005
Opus 5 $0.02003 $0.02003
Sonnet 5 $0.00801 $0.00801
Haiku 4.5 $0.00400 $0.00400

Measured 2d ago against content hash d4ef792ca974, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gpal AGENTS.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 2d 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.

AGENTS.md · 348 lines

How it starts

The opening of the file, as written. The whole thing — 348 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Development Guide

Internal documentation for gpal development.

Dogfooding

Before committing changes to gpal, use gpal to review them:

consult_gemini(
    query="Review server.py for bugs, edge cases, and API misuse",
    model="pro",
    file_paths=["src/gpal/server.py"]
)

Gemini catches real issues — see git history for proof.

Architecture

┌─────────────────────────────────────────────────────┐
│              MCP Client                             │
│    (Claude Desktop, Cursor, VS Code, etc.)          │
└─────────────────────┬───────────────────────────────┘
                      │ MCP Protocol
                      ▼
┌─────────────────────────────────────────────────────┐
│                 gpal Server                         │
│                                                     │
│  ┌─────────────────┐  ┌────────────────────────┐    │
│  │ consult_gemini  │  │ consult_gemini_oneshot │  ← Tools │
│  └────────┬────────┘  └───────────┬────────────┘    │
│           │                    │                    │
│           └──────────┬─────────┘                    │
│                      ▼                              │
│  ┌──────────────────────────────────────┐          │
│  │       Session Manager                 │          │
│  │  (history preservation, model switch) │          │
│  └──────────────────┬───────────────────┘          │
│                      │                              │
└──────────────────────┼──────────────────────────────┘
                       ▼
┌─────────────────────────────────────────────────────┐
│              Google Gemini API                      │
│                                                     │
│  Gemini has internal tools:                         │
│  • list_directory  • read_file  • search_project   │
│  • git  • gemini_search                            │
│  • file_search (when stores exist)                 │
│                                                     │
│  Automatic Function Calling enabled                 │
│  (Gemini autonomously explores the codebase)        │
└─────────────────────────────────────────────────────┘

Read the full file on GitHub · 348 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. 2d ago First seen · 348 lines · 4,005 tokens per session scan A d4ef792ca974

Subscribe to this mod's changes

gpal AGENTS.md is an instructions file published in the GitHub repository tobert/gpal (10 stars, last pushed 2mo ago), licensed MIT. It adds 4,005 tokens to every session, about $0.0200 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 2026-08-31.

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