kartograph AGENTS.md

An AGENTS.md instruction file for the kartograph project. It documents the roles of major system areas and includes project-specific guidance for tests and the development environment.

In plain words
What is it for?
For understanding kartograph's authentication, management, ingestion, and extraction areas, setting up development work, checking running services, and running unit tests.
Why use it?
It gives a coding agent the project context and commands needed to work safely and run tests against the correct instance.

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/openshift-hyperfleet/kartograph/agents-md
Clone the repo
git clone --depth 1 https://github.com/openshift-hyperfleet/kartograph

Made for: Codex, OpenCode.

Per session 1,819 This file is loaded in full into every session.
When invoked 1,819 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 $0.01819 $0.01819
Opus 5 $0.00910 $0.00910
Sonnet 5 $0.00364 $0.00364
Haiku 4.5 $0.00182 $0.00182

Measured 2d ago against content hash 660be742a5e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

kartograph 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 · 202 lines

How it starts

The opening of the file, as written. The whole thing — 202 lines — stays where its author put it; the contents beside it link to each section on GitHub.

  1. Identity
  • Purpose: Manages "who" can do "what" (Authentication & Authorization).
  • Responsibilities:
    • User, Team, and Tenant management.
    • API Key lifecycle management.
  1. Management
  • Purpose: The "Control Plane" for the platform. Manages metadata and configuration.
  • Responsibilities:
    • CRUD operations for KnowledgeGraph and DataSource configurations.
    • Storing encrypted credentials (via Vault).
    • Defining and managing synchronization schedules.
  1. Ingestion
  • Purpose: Extracting raw data. This is where the Adapters (GitHub, K8s, etc.) live.
  • Responsibilities:
    • Running adapters to fetch "Raw Content Changesets" (what changed?).
    • Generating sync manifests.
    • Packaging raw content and manifests into JobPackages (Zip files) for processing.
  1. Extraction
  • Purpose: Transforming raw content into Graph Data. This is where the AI Agent lives.
  • Responsibilities:
    • Processing JobPackages from Ingestion.
    • Running the Claude Agent SDK to determine relationships and entities.
    • Running the Deterministic Processor for non-AI tasks (renames/deletes).
    • Producing a MutationLog (JSONL) of graph operations.
  1. Graph
  • Purpose: The persistence engine. Executes writes and serves reads.
  • Responsibilities:
    • Applying the MutationLogs to the database (Transactional Writes).
    • Managing database integrity (e.g., cascading deletes).
    • Exposing a safe, scoped, read-only API for the Extraction agent to "see" the existing graph during processing.
  1. Querying
  • Purpose: The consumer interface. Provides read access to end-users and agents.
  • Responsibilities:
    • Hosting the MCP (Model Context Protocol) Server.
    • Translating user/agent questions into database queries.
    • Enforcing rate limits and query complexity safety checks.

Logging should follow the Domain Oriented Observability pattern. Be sure to read the article to fully understand. Domain probes should be 100% preferred over logger.* and print().

Read the full file on GitHub · 202 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 · 202 lines · 1,819 tokens per session scan A 660be742a5e9

Subscribe to this mod's changes

kartograph AGENTS.md is an instructions file published in the GitHub repository openshift-hyperfleet/kartograph (10 stars, last pushed 29d ago), licensed Apache-2.0. It adds 1,819 tokens to every session, about $0.0091 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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