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/bytedance/deer-flow/agents-mdgit clone --depth 1 https://github.com/bytedance/deer-flowWrote 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/bytedance/deer-flow/agents-md)<a href="https://agentmods.dev/instructions/bytedance/deer-flow/agents-md"><img src="https://agentmods.dev/badge/instructions/bytedance/deer-flow/agents-md.svg" alt="Measured on agentmods" 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 | $0.03552 | $0.03552 |
| Opus 5 | $0.01776 | $0.01776 |
| Sonnet 5 | $0.00710 | $0.00710 |
| Haiku 4.5 | $0.00355 | $0.00355 |
Grade A, and why
deer-flow 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 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.
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 — 242 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 (Claude Code, Codex, and others) when working with code in this repository. It is the source of truth; the sibling CLAUDE.md imports it via @AGENTS.md.
It is the monorepo orientation layer: it maps the whole repo and points to the module guides that own the depth. For anything inside a module, read that module's guide rather than expecting full detail here:
- backend/AGENTS.md — backend depth: harness/app split, agent & middleware chain, sandbox, MCP, skills, memory, IM channels, persistence/migrations, config system, test layout.
- frontend/AGENTS.md — frontend depth: Next.js App Router layout, thread/streaming data flow, code style, commands.
What is DeerFlow
DeerFlow is a LangGraph-based AI super-agent system with a full-stack architecture. The backend runs a "super agent" with sandboxed execution, persistent memory, subagent delegation, and extensible tools (built-in, MCP, community), all per-thread isolated. The frontend is a Next.js chat UI. External IM platforms (Feishu, Slack, Telegram, Discord, DingTalk) bridge into the same agent through the Gateway.
Service Topology
A single make dev / Docker stack runs four cooperating services:
| Service | Port | Role |
|---|---|---|
| Nginx | 2026 |
Unified reverse-proxy entry point — open this in the browser |
| Gateway API | 8001 |
FastAPI REST API + embedded LangGraph-compatible agent runtime |
| Frontend | 3000 |
Next.js web interface |
| Provisioner | 8002 |
Optional — only when sandbox is configured for provisioner/K8s mode |
Nginx is the single public entry: it serves the frontend and proxies /api/langgraph/*
to the Gateway's LangGraph runtime, rewriting it to Gateway's native /api/* routes; all
other /api/* go straight to the Gateway REST routers. See
backend/AGENTS.md for the runtime and router detail.
It compresses HTML and configured textual assets, while deliberately leaving SSE,
fonts, images, audio, and video uncompressed at the proxy layer.
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 · +7 lines · +122 tokens per session f11f6ee553bc
- yesterday Changed · +8 lines · +129 tokens per session 16a317990fe5
- 4d ago First seen · 227 lines · 3,301 tokens per session scan A 4931f9d6bfe7
deer-flow AGENTS.md is an instructions file published in the GitHub repository bytedance/deer-flow (81,317 stars, last pushed today), licensed MIT. It adds 3,552 tokens to every session, about $0.0178 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.
Other instructions, from other repositories
nexent AGENTS.md
AGENTS.md instructions for ModelEngine-Group/nexent, covering agents, available skills, project overview, developer commands and backend (python 3.11).
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/).
OpenOutreach CLAUDE.md
Claude Code instructions for eracle/OpenOutreach, covering claude.md, rules, project overview, architecture and commands.
agent-graph AGENTS.md
AGENTS.md instructions for keta1930/agent-graph, covering commands, architecture, git conventions and test and format infrastructure.
agenticloop AGENTS.md
Instructions for bartoszarendt/agenticloop, covering agents.md, agentic loop is the subject here, not the process, purpose, source of truth and optional private project context.
earnings-edge copilot-instructions.md
Copilot instructions for suhaas/earnings-edge, covering earnings-edge: agent development guidelines, architecture & core concepts, the graph, agent roles and tools & skills boundary.