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.
npx agentmods add instructions/dip497/hivemind/agents-mdgit clone --depth 1 https://github.com/dip497/hivemindWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.01004 | $0.01004 |
| Opus 5 | $0.00502 | $0.00502 |
| Sonnet 5 | $0.00201 | $0.00201 |
| Haiku 4.5 | $0.00100 | $0.00100 |
Grade A, and why
hivemind 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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — hivemind
Guidance for AI agents (and humans) working in this repo. Subfolders have their
own AGENTS.md with local detail — read the one nearest the code you're
changing. For the research/knowledge-base workflow, see CLAUDE.md.
What this is
A Linux desktop app (Electron + an infinite xyflow
canvas) that is mission-control for AI coding agents. Every tile is a live
terminal / diff / file-tree / editor / issues board; tiles live in frames
(workspaces) bound to a real repo on disk — local, a git worktree, or a remote
SSH host. Issues are plain markdown under .hivemind/; agents read/update them
through an MCP server. Local-first, no cloud, no telemetry.
Monorepo layout
apps/
desktop/ Electron main + preload + React renderer (the canvas app) → apps/desktop/AGENTS.md
cli/ `hive` CLI (citty + bun-compile); hosts the MCP server
packages/
hive-core/ storage + parsing for .hivemind/ (gray-matter + zod) → packages/hive-core/AGENTS.md
hive-mcp/ stdio MCP server (tools wrapping hive-core)
tsconfig/ shared TS config
templates/ per-workspace agentic templates (`hive init --agentic`)
docs/design/ architecture design docs (e.g. remote-frames.md)
scripts/ release.sh + helpers
pnpm workspace; Node ≥ 22, pnpm ≥ 10, bun ≥ 1.1 (CLI compile only).
Build / test / verify (run from apps/desktop unless noted)
pnpm run typecheck # tsc --noEmit, web + node projects — ALWAYS run before commit
pnpm run build # electron-vite build (validates the real bundle path)
pnpm test:unit # node:test — fast, pure logic; add tests here first
pnpm test:e2e # Playwright + xvfb — needs `unset ELECTRON_RUN_AS_NODE` first
The minimum gate before any commit: typecheck + build + test:unit green. Run the relevant e2e when you touch canvas/frame/tile/issue behavior.
Conventions
- TypeScript strict. No
anyescapes without reason. - Comments document why, especially load-bearing trade-offs and the non-obvious. Match the density of the surrounding file. No restating the code.
- Icons:
lucide-reactonly — never emoji or unicode glyphs as UI icons (they render inconsistently and aren't theme-colorable). - Design tokens: use the
var(--color-*)palette + the.u-eyebrowutility; don't hard-code hex. Informational text uses--color-fg2(passes WCAG AA);--color-fg3is decoration only. Addaria-labelto icon-only buttons and a focus ring to every input. - Commit messages end with:
Co-Authored-By: Claude Opus 4.8 <[email protected]>. Commit tomain, in logical chunks. Keep stray files (.rig/, scratch) out of commits — add explicit paths, don'tgit add -Ablindly. - CHANGELOG hand-off rule: anything that ships to users gets a one-line entry
under
## [Unreleased]inCHANGELOG.mdbefore you hand back.
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.
- 2d ago First seen · 84 lines · 1,004 tokens per session scan A ecfb0762a2b2
hivemind AGENTS.md is an instructions file published in the GitHub repository dip497/hivemind (6 stars, last pushed 4d ago), licensed MIT. It adds 1,004 tokens to every session, about $0.0050 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.
Other instructions, from other repositories
agor CLAUDE.md
Claude Code instructions for preset-io/agor, a project described as: Agor - team command center for all things agentic.
agor AGENTS.md
AGENTS.md instructions for preset-io/agor, covering claude.md, important: where the docs live, quick start, terminal 1: daemon (watches core + daemon, auto-restarts) and terminal 2: ui dev server.
pi-agent-dashboard AGENTS.md
Instructions for BlackBeltTechnology/pi-agent-dashboard, covering pi dashboard, docs-first gate — kb before grep (per-turn doctrine), code instructions (per-turn doctrine), investigation protocol — index first and documentation update protocol.
agents-universe CLAUDE.md
Instructions for agents-universe/agents-universe, covering agents universe — enterprise ai agent framework, project overview, monorepo layout, development commands and api (from packages/api/).
AIWorkHub AGENTS.md
Instructions for shrec/AIWorkHub, covering aiworkhub mcp agent notes and aiworkhub mcp tool-use policy.
AIWorkHub copilot-instructions.md
Instructions for shrec/AIWorkHub, a project described as: Open-source, local-first control plane for multi-model AI coding agents in VS Code and MCP: task DAGs, source intelligence, durable context and evidence-based review.