coderadius AGENTS.md

Instructions for AI coding agents working on CodeRadius, a command-line tool that maps architecture and dependencies across codebases. It covers the project’s commands, runtime, dashboard, tests, and graph-database integrations.

In plain words
What is it for?
Use it to install dependencies, compile the project, run the CLI or dashboard, execute unit and integration tests, and run evaluation tests.
Why use it?
It gives agents the repository-specific rules needed to build, run, test, and change the project correctly.

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

Made for: Codex, OpenCode.

Per session 5,788 This file is loaded in full into every session.
When invoked 5,788 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 $0.05788 $0.05788
Opus 5 $0.02894 $0.02894
Sonnet 5 $0.01158 $0.01158
Haiku 4.5 $0.00579 $0.00579

Measured yesterday against content hash a35114300a55, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

coderadius 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 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

AGENTS.md · 263 lines

How it starts

The opening of the file, as written. The whole thing — 263 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to AI coding agents working with code in this repository.

What This Is

CodeRadius is a CLI tool that builds an architectural knowledge graph from polyglot codebases. It statically analyzes source code (TypeScript, PHP, Go, Python), extracts infrastructure dependencies via LLM-driven semantic analysis, persists everything to a Neo4j/Memgraph graph database, and enables cross-repo impact analysis ("blast radius") and governance policy enforcement.

Build & Run Commands

Runtime: Bun (not Node.js for development). The project uses ES modules ("type": "module").

bun install                # Install dependencies
bun run build              # TypeScript compilation (tsc, noEmit)
bun run dev                # Run CLI directly: bun run src/cli/index.ts
bun run dev:dashboard      # Dashboard dev server with live reload (http://localhost:3456)

Testing

bun run test:unit                                    # All unit tests
bun vitest run tests/unit/path/to/file.test.ts       # Single unit test
bun run test:integration                             # Integration tests (requires running Memgraph)
make test-eval-golden      # Eval tests (LLM golden + replay-cached patterns)
make test-patterns         # Pattern fixtures, deterministic subset (no LLM, no DB)

The repo organises tests by determinism level and dependency footprint. Pick the right tier when adding a feature or fixing a bug:

  • Unit tests (tests/unit/): pure logic, no external services. Defaults for sanitizer rules, schema validation, regex guards, in-memory pipelines. Run: bun run test:unit (~7s).

  • Integration tests (tests/integration/): exercise real graph mutations against Memgraph. Required for any change to src/graph/mutations/, the welder (dynamic-infra-resolver.ts), or DB-backed pipelines. Run sequentially (no file parallelism). Run: bun run test:integration (~20s).

  • Eval tests — agents (tests/eval/agents/): LLM extraction quality on per-function snippets, replay-cached. Use when a fix changes prompt rules, sanitizer behaviour visible to the LLM, or the LLM output schema. Three modes via EVAL_LLM_MODE:

    • replay (default): cached LLM outputs from tests/eval/.llm-cache/, ~2s, deterministic
    • live: real LLM calls, saves to cache
    • refresh: real LLM calls, overwrites cache

Read the full file on GitHub · 263 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. yesterday First seen · 263 lines · 5,788 tokens per session scan A a35114300a55

Subscribe to this mod's changes

coderadius AGENTS.md is an instructions file published in the GitHub repository coderadius-ai/coderadius (24 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 5,788 tokens to every session, about $0.0289 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.