cartograph AGENTS.md

cartograph AGENTS.md is an instructions file for Codex, OpenCode from onixhdz/cartograph. It costs 1,039 tokens per session, scanned A, original, MIT.

Project-specific guidance for Cartograph, a local-first tool that analyzes code and provides code intelligence. It sets design and safety principles for keeping changes small, understandable, and local.

In plain words
What is it for?
Use it when changing Cartograph's commands, code analysis, data structures, or supported execution paths. It is also a reference for naming, readability, architecture, and deciding whether a new public feature is needed.
Why use it?
It helps coding agents avoid unnecessary features, outside services, duplicated logic, and changes that expose internal details. This keeps the tool's behavior consistent and easier to maintain.

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

Made for: Codex, OpenCode.

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 cartograph AGENTS.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/onixhdz/cartograph/agents-md.svg)](https://agentmods.dev/instructions/onixhdz/cartograph/agents-md)
Your own site
<a href="https://agentmods.dev/instructions/onixhdz/cartograph/agents-md"><img src="https://agentmods.dev/badge/instructions/onixhdz/cartograph/agents-md.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,039 This file is loaded in full into every session.
When invoked 1,039 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 $0.01039 $0.01039
Opus 5 $0.00519 $0.00519
Sonnet 5 $0.00208 $0.00208
Haiku 4.5 $0.00104 $0.00104

Measured 5d ago against content hash 71cdaf89072b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cartograph 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 5d 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 · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cartograph

Cartograph is local-first code intelligence. Every change should make the tool more accurate, reliable, and useful without adding unnecessary surface area.

Principles

  • KISS: Prefer the simplest design that solves the real problem clearly.
  • YAGNI: Do not build speculative capabilities, abstractions, or compatibility layers before they are needed.
  • Locality of Behavior: Keep related behavior close together so code can be understood without chasing distant indirection.
  • Open/Closed: Extend existing seams when appropriate, but do not force abstractions that make simple changes harder.
  • Avoid new public surface area unless it is clearly needed. Extend existing concepts before adding commands, flags, endpoints, tools, fields, storage, or graph schema.
  • Keep behavior consistent across all supported execution paths. Do not implement CLI-only or mode-specific behavior unless explicitly required.
  • Do not expose internal implementation details as user-facing concepts just because they exist in the code.
  • Keep everything local by default. Do not introduce external services, network dependencies, or cloud assumptions without an explicit requirement.
  • Avoid speculative aliases, compatibility layers, convenience APIs, or migration paths unless there is shipped behavior or persisted data that requires them.
  • Check existing local plans before starting substantial feature work. Put new plans or design notes in the local planning area.

Design Discipline

  • Spend design effort upfront for non-trivial changes. Simple, durable designs usually require revision, not the first idea.
  • Preserve existing graph, storage, API, and UX conventions by inspecting the code before changing them.
  • Always explain why when a decision is non-obvious. Rationale helps future maintainers evaluate and preserve intent.
  • Solve known correctness, performance, and maintainability risks before shipping changed code.

Safety And Bounds

  • Prefer explicit, easy-to-follow control flow over clever branching or hidden behavior.
  • Put bounds on work: avoid unbounded loops, queues, goroutines, filesystem walks, graph traversals, and result sets.
  • Keep variable scope small. Compute values close to where they are used.
  • Handle all errors intentionally with useful context. Do not ignore errors unless the reason is explicit and safe.
  • Prefer modern, idiomatic Go with clear errors, minimal abstraction, and no panics outside tests.
  • Use assertions or test-only checks for invariants when they make programmer errors fail early.

Read the full file on GitHub · 72 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. 5d ago First seen · 72 lines · 1,039 tokens per session scan A 71cdaf89072b

Subscribe to this mod's changes

cartograph AGENTS.md is an instructions file published in the GitHub repository onixhdz/cartograph (11 stars, last pushed yesterday), licensed MIT. It adds 1,039 tokens to every session, about $0.0052 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