Buzz is a self-hostable workspace where people and AI agents share rooms, communicate through signed events, and collaborate on repositories, workflows, canvases, and code reviews. It is for teams that want humans and agents to work together on software through a relay they control. The catalogue entries are agents, skills, and instructions for using Buzz’s collaborative workflows.
Borrowing it
Nothing to install: this file belongs to block/buzz. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/block/buzz/main/AGENTS.mdgit clone --depth 1 https://github.com/block/buzzWrote 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.
[](https://agentmods.dev/instructions/block/buzz/agents-md)<a href="https://agentmods.dev/instructions/block/buzz/agents-md"><img src="https://agentmods.dev/badge/instructions/block/buzz/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/block/buzz/agents-md"><img src="https://agentmods.dev/badge/instructions/block/buzz/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.11525 | $0.11525 |
| Opus 5.5 | $0.04610 | $0.04610 |
| Sonnet 5.5 | $0.02305 | $0.02305 |
| Haiku 4.5 | $0.01153 | $0.01153 |
Grade A, and why
buzz AGENTS.md scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
(through the app or `curl`), or by running the changed command. Agent testing How it starts
The opening of the file, as written. The whole thing — 879 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md — AI Agent Contributor Guide
This guide is for AI agents contributing to the Buzz codebase. It covers agent-specific context and conventions. For general contributor info (setup, code style, PR process, architecture), see CONTRIBUTING.md.
Product Contract
Before planning or reviewing a non-trivial change:
- Read VISION.md.
- Read the
VISION_*.mddocuments relevant to the affected product surface. - Read the applicable guidance in TESTING.md and any
package-local
TESTING.md. - For any change to
migrations/,schema/, or schema-dependentbuzz-dbqueries, read docs/database.md: no new triggers, functions, or foreign keys; no data backfills in migrations; update every schema location; keep every migration compatible with the relay that is currently deployed; and never make a migration refuse a populated table. - Check that the proposed design advances, or at least does not contradict, that product intent. Call out any intentional tension explicitly.
Implementation describes the product today; the vision documents describe the product it is becoming. A locally correct change can still be wrong if it works against that direction. Scale validation to the change's risk and exercise the real workflow for user-visible or integration behavior when practical; green CI and runtime evidence answer different questions.
Before opening a PR
Open work in progress as a draft PR. Mark it ready for review only when this checklist holds for the current change. Scale it to what changed: documentation-only changes need content, link, and diff checks plus human confirmation, not app runs.
- Agent review ran under Reviewing, and its recommended blockers were fixed or explicitly declined by the human author. Optional suggestions do not gate readiness.
- An agent exercised the changed behavior. Client changes: the affected flow in the app, using the native app or a device when the behavior needs it (browser or headless Playwright counts only for what it can exercise). Relay changes: a local relay, exercising the changed events or endpoints. CLI or tooling changes: the affected command or workflow. The human may skip this step, for example for a small change or while iterating.
- A human then tested it themselves: in the app, against the local relay
(through the app or
curl), or by running the changed command. Agent testing does not substitute. Agents give the human exact steps and what working looks like, then wait for explicit confirmation. Never mark this step done yourself. - Add
buzz-review-completedto the PR description once steps 1–3 hold. It attests the checklist, and automated reviewers may skip review because of it. If later edits change behavior, remove it and return the PR to draft until the affected steps are redone.
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.
- today Changed · +35 lines · +687 tokens per session ed9ffcd684cc
- 5d ago Changed · +11 lines · +166 tokens per session 474124dfc8e7
- 16d ago Changed · +5 lines · +135 tokens per session 0e7f64be7206
- 17d ago Changed · +6 lines · +127 tokens per session d2c7f4d7cf93
- 18d ago Changed · +25 lines · +368 tokens per session ec5787202328
- 22d ago Changed · +2 lines · +30 tokens per session 28271c7c2f89
- 29d ago Changed · +73 tokens per session 8c181fa2e9d7
- 1mo ago Changed · +42 lines · +571 tokens per session 3f899f49921d
- 1mo ago Changed · +4 lines · +45 tokens per session 66f9bc5f242e
- 1mo ago First seen · 749 lines · 9,323 tokens per session scan A b9691ce3036c
buzz AGENTS.md is an instructions file published in the GitHub repository block/buzz (36,764 stars, last pushed today), licensed Apache-2.0. It adds 11,525 tokens to every session, about $0.0461 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
buzz AGENTS.md compared with instructions from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| buzz AGENTS.mdblock/buzz | Instructions file | 37k | today | Apache-2.0 | A | 11,525 | Codex, OpenCode |
| vscode buildNext.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 9,719 | GitHub Copilot |
| next.js AGENTS.mdvercel/next.js | Instructions file | 143k | today | MIT | A | 7,461 | Codex, OpenCode |
| vscode oss-third-party-notices.instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 5,516 | GitHub Copilot |
| langchain AGENTS.mdlangchain-ai/langchain | Instructions file | 149k | today | MIT | A | 4,680 | Codex, OpenCode |
| vscode copilot-instructions.mdmicrosoft/vscode | Instructions file | 195k | today | MIT | A | 3,093 | GitHub Copilot |
| deepseek-harness AGENTS.mddeepseek-ai/deepseek-harness | Instructions file | 274k | 2d ago | MIT | A | 4,313 | Codex, OpenCode |