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NodeBenchAI AGENTS.md

A set of AGENTS.md instructions for working on the NodeBenchAI project, covering agent coordination, production-like UI work, code ownership, and content quality.

In plain words
What is it for?
Use it to guide coordination between Codex and Claude, claim editing areas, follow the project's UI and production-parity process, and handle social posts, duplicate content, cleanup, and scope.
Why use it?
It tells coding agents which files and workflows are sensitive, reducing conflicts between agents and mistakes in shared backend or production-related work.

Instructions file for CodexOpenCode

14 18d ago C scan 30,200 tokens original MIT
View the source file HomenShum/NodeBenchAI
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/homenshum/nodebenchai/agents-md
Clone the repo
git clone --depth 1 https://github.com/HomenShum/NodeBenchAI

Made for: Codex, OpenCode.

Per session 30,200 This file is loaded in full into every session.
When invoked 30,200 The same file — it is already loaded in full.
Security scan C 3 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 $0.30200 $0.30200
Opus 5 $0.15100 $0.15100
Sonnet 5 $0.06040 $0.06040
Haiku 4.5 $0.03020 $0.03020

Measured 2d ago against content hash aedd6a398ba9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade C, and why

NodeBenchAI AGENTS.md scanned grade C with 3 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.

Sends data to an external URLmediumData exfiltration

A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.

requests.post("https://nodebench-mcp-unified.onrender.com",

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

**Claude Code** (`~/.claude/settings.json`):

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- Health: `curl https://nodebench-mcp-unified.onrender.com/health` (must return `{"status":"ok","tools":114}`)
AGENTS.md · 2,459 lines

How it starts

The opening of the file, as written. The whole thing — 2,459 lines — stays where its author put it; the contents beside it link to each section on GitHub.

NodeBench Agent Workflow

Agent coordination (Codex ↔ Claude) — read FIRST

AGENT_COORDINATION.md (repo root) is the live ledger of who is editing what right now and what backend contracts are ready to call. Before editing a hot file (public/proto/home-v5.html, backend/convex/events.ts, backend/convex/schema/eventsSchema.ts): scan Active claims, claim your region before you start, and hand off new backend contracts there. Never convex deploy/deploy:prod out-of-band to the shared prod deployment — it pushes un-reviewed schema/functions and breaks the other agent's next deploy (this caused a Convex schema-validation incident this session). Declare new shared-table fields v.optional(...) and announce them in the ledger instead.

Prod-parity and UI kit workflow

Use this rule before any UI, design-system, route-parity, or newly uploaded UI kit task.

Source of truth:

  • Git source of truth: origin/main
  • Start UI/design work from a clean worktree based on origin/main.
  • In this desktop session, the clean prod-parity worktree is D:\VSCode Projects\cafecorner_nodebench\nodebench_ai4\nodebench-ai\.worktrees\prod-parity-runtime.
  • A UI kit packet is a design target, not an implementation branch.

Rules:

  • Do not work from hotfix/workspace-routing-export unless the user explicitly names one file to salvage.
  • Do not wholesale merge old dirty worktrees or old design/parity branches.
  • Start from prod parity, inspect the new UI kit packet, compare, then implement only the delta.
  • Preserve live Convex-backed runtime flows; no silent fixture fallback in production paths.
  • Preserve web nav as Home - Reports - Chat - Inbox - Me.
  • Keep Workspace as a separate deployed surface, not a sixth web tab.
  • Verify against the latest UI kit packet and current prod/prod-parity screenshots, not stale local branch screenshots.

Required runbook:

  • docs/runbooks/PROD_PARITY_UI_KIT_WORKFLOW.md

Required checks for UI-kit work:

  • npx tsc --noEmit --pretty false
  • Targeted Vitest for touched surfaces
  • npm run build
  • Browser screenshots for changed views
  • Explicit before/after comparison against the UI kit packet

Read the full file on GitHub · 2,459 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 · 2,459 lines · 30,200 tokens per session scan C aedd6a398ba9

Subscribe to this mod's changes

NodeBenchAI AGENTS.md is an instructions file published in the GitHub repository HomenShum/NodeBenchAI (14 stars, last pushed 18d ago), licensed MIT. It adds 30,200 tokens to every session, about $0.1510 per session on Opus 5. A static security scan graded it C with 3 findings (sends data to an external url, reads agent configuration directories, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

FrontendResearchWriting and docsagentsaicontext-packsconvexentity-intelligencemcp
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