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/camiproject/semantic-deer-flow/agents-mdgit clone --depth 1 https://github.com/CamiProject/semantic-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/camiproject/semantic-deer-flow/agents-md)<a href="https://agentmods.dev/instructions/camiproject/semantic-deer-flow/agents-md"><img src="https://agentmods.dev/badge/instructions/camiproject/semantic-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 | $0.02125 | $0.02125 |
| Opus 5 | $0.01063 | $0.01063 |
| Sonnet 5 | $0.00425 | $0.00425 |
| Haiku 4.5 | $0.00213 | $0.00213 |
Grade A, and why
semantic-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 4d 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 — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md
Public Downstream Identity
This repository is Semantic DeerFlow, an unofficial downstream of ByteDance
DeerFlow. It is not affiliated with or endorsed by ByteDance or the official project.
The primary product surface is the SaaS backend API; the bundled frontend is a
development and debugging interface. Keep deerflow.*, DEER_FLOW_*, existing APIs,
core data structures, and Docker compatibility identifiers unchanged.
Committed SaaS examples use only public-tenant-001, public_demo,
public-user-001, site-demo-001, project-demo-001, demo, semantic_demo,
demo_sites, and demo_projects. DEER_FLOW_SEMANTIC_DEMO_DATA=true selects the
public in-memory SQLite demo and must be disabled for a real datasource integration.
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 Semantic 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 make dev / Docker stack runs the core application plus internal SaaS semantic
services when configured:
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.
- 4d ago First seen · 156 lines · 2,125 tokens per session scan A 63de69b0805e
semantic-deer-flow AGENTS.md is an instructions file published in the GitHub repository CamiProject/semantic-deer-flow (21 stars, last pushed 29d ago), licensed MIT. It adds 2,125 tokens to every session, about $0.0106 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
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
spec-kit AGENTS.md
AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.
codex AGENTS.md
AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).
next.js AGENTS.md
Instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.