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/labsai/eddi/agents-mdgit clone --depth 1 https://github.com/labsai/EDDIWhat 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 | $0.15605 | $0.15605 |
| Opus 5 | $0.07803 | $0.07803 |
| Sonnet 5 | $0.03121 | $0.03121 |
| Haiku 4.5 | $0.01561 | $0.01561 |
Grade C, and why
EDDI AGENTS.md scanned grade C 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 3d 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
> **Warning**: `scope: "secret"` requires the vault to be active (`EDDI_VAULT_MASTER_KEY` env var set). If vault is disabled (common in dev mode), `autoVaultSecret()` fails and falls back to storing plaintext — but logs How it starts
The opening of the file, as written. The whole thing — 973 lines — stays where its author put it; the contents beside it link to each section on GitHub.
EDDI Backend — AI Agent Instructions
This file is automatically loaded by AI coding assistants. Follow ALL rules below.
New here? Read the README first — it has setup, the quick start, and a feature tour. This file is the working guide for building in the codebase: architecture, code patterns, and conventions.
Contents: 1. Project Context · 2. Workflow Protocol · 3. Roadmap · 4. Backend Java Guidelines · 5. Agent Config Authoring · 6. Session Protocol
1. Project Context
EDDI (Enhanced Dialog Driven Interface) is a multi-agent orchestration middleware for conversational AI. This repo is the Java/Quarkus backend.
EDDI is a config-driven engine, not a monolithic application. Agent behavior lives in JSON configurations; Java code builds the components and infrastructure (the "engine") that reads and executes those configurations.
Ecosystem
| Repo | Tech | Purpose |
|---|---|---|
| EDDI (this repo) | Java 25, Quarkus, MongoDB | Backend engine, REST API, lifecycle pipeline |
| quarkus-eddi | Java 21, Quarkus Extension | Quarkus SDK — @Inject EddiClient, Dev Services, MCP bridge |
| EDDI-Manager | React 19, Vite, Tailwind | Admin dashboard (served from EDDI at /manage; / redirects to the /welcome chooser, /workforce is the group-conversation workspace) |
| eddi-chat-ui | React, TypeScript | Standalone chat widget |
| eddi-website | Astro, Starlight | Marketing site + documentation at eddi.labs.ai |
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.
- 3d ago First seen · 973 lines · 15,605 tokens per session scan C 15c237edad54
EDDI AGENTS.md is an instructions file published in the GitHub repository labsai/EDDI (372 stars, last pushed 3d ago), licensed Apache-2.0. It adds 15,605 tokens to every session, about $0.0780 per session on Opus 5. A static security scan graded it C with 1 finding (harvests environment variables). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
atmosphere AGENTS.md
AGENTS.md instructions for Atmosphere/atmosphere, covering build system: maven, commands, module build, build only atmosphere-runtime (cpr) and build only spring-boot-starter.
dograh AGENTS.md
AGENTS.md instructions for dograh-hq/dograh, covering dograh - project overview, project structure, tech stack, local development and environment configuration.
elevenlabs-python AGENTS.md
AGENTS.md instructions for elevenlabs/elevenlabs-python, covering agent instructions and fern-generated code.
camel-quarkus AGENTS.md
Instructions for apache/camel-quarkus, covering apache camel quarkus - ai agent guidelines, project overview, what not to do, technology stack and repository structure.
camel-quarkus-examples AGENTS.md
Instructions for apache/camel-quarkus-examples, covering apache camel quarkus examples - ai agent guidelines, project info, rules of engagement (essentials), repository structure and anatomy of an example.
veryfront-code AGENTS.md
Instructions for veryfront/veryfront-code, covering veryfront code agent guide, default working style, commands, command discovery and mcp server.