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autonomous-ai-agency: Instructions file for Claude Code

AGENTS.md

autonomous-ai-agency AGENTS.md is an instructions file for Claude Code, Codex, OpenCode from strikersam/autonomous-ai-agency. It costs 3,476 tokens per session, scanned A, original, MIT.

A repository instruction and reference file for coding agents working on the autonomous-ai-agency project. It describes the system's architecture, code layout, risky areas, and operating details.

In plain words
What is it for?
It helps agents locate modules, understand how the application is deployed, and identify files that need extra care during maintenance.
Why use it?
It gives agents project-specific context before they change code, reducing the chance of violating repository rules or misunderstanding where components belong.

Instructions file for Claude CodeCodexOpenCode

Written for Claude Code and Codex and OpenCode: SessionStart hook event, but also the file is AGENTS.md. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

This is strikersam/autonomous-ai-agency's own configuration. It tells Claude Code, Codex and OpenCode how to work on autonomous-ai-agency itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything autonomous-ai-agency configures →

not rated 8repo changed 4d ago A scan 3,476 tokens original MIT
View source ↗ strikersam/autonomous-ai-agency autonomous-ai-agency.strikersam.workers.dev
Reuse

Borrowing it

Nothing to install: this file belongs to strikersam/autonomous-ai-agency. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/strikersam/autonomous-ai-agency/master/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/strikersam/autonomous-ai-agency

Made for: Claude Code, Codex, OpenCode.

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Per session 3,476 This file is loaded in full into every session.
When invoked 3,476 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.03476 $0.03476
Opus 5 $0.01738 $0.01738
Sonnet 5 $0.00695 $0.00695
Haiku 4.5 $0.00348 $0.00348

Measured 4d ago against content hash 275b0f72a3ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

autonomous-ai-agency 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.

AGENTS.md · 283 lines

How it starts

The opening of the file, as written. The whole thing — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Codebase Map & Operations Reference

The rules are in CLAUDE.md §1. All 44 of them, binding on every agent — Claude, Codex, Cursor, Aider, or anything else. Read that section before changing code.

This file is reference: where things are, how big they are, how the system is deployed and monitored. It deliberately does not restate a single rule. If you catch it doing so, delete the copy — see .claude/rules-archive/CONFLICTS.md for what duplicated rule sets did to this repo.

Architecture

Client: Claude Code / Cursor / Aider / Continue / Telegram / SPA
                          │  HTTP (OpenAI / Anthropic / Ollama format)
                    Bearer Auth / JWT
                          ▼
              proxy.py (FastAPI :8000)
              Auth → Rate Limit → Route
                          │
     ┌────────────────────┼────────────────────┐
 /v1/messages   /v1/chat/completions        /api/*
 Anthropic compat   OpenAI handlers      Ollama native
     └────────────────────┼────────────────────┘
                          ▼
                    router/ModelRouter
                    classify_task()
                          ▼
                       Ollama
                          ▲
                 agent/AgentRunner
                 Plan → Execute → Verify

backend/server.py (FastAPI :8001) is the second app: dashboard API, company graph, onboarding, workflow orchestrator, secrets, skills.

Codebase map

Line counts re-measured 2026-08-10 (wc -l). Re-run before trusting them — the previous version of this table was off by up to 4,179 lines on a single file.

Path Purpose Lines Risk
backend/server.py Dashboard API server 10,666 HIGH
proxy.py Main entry point, auth, rate limit, routing 4,116 HIGH
agent/loop.py AgentRunner — plan/execute/verify loop 2,940 RISKY
packages/ai/router.py Multi-provider backend with fallback 1,988 Medium
services/workflow_orchestrator.py Workflow execution engine 1,940 HIGH
services/scanner.py Tech stack scanner (Playwright) 1,726 Medium
services/company_graph_store.py Company knowledge graph persistence 1,722 Medium
services/ceo_dispatcher.py CEO delegation + supervised escalation 1,083 HIGH
packages/config/control_catalogue.py Declarative platform-control table 1,064 Low
direct_chat.py Direct chat sessions, intent classification 892 Medium
agent/repowise.py RepowiseIntelligence — codebase analysis 867 Low
chat_handlers.py OpenAI/Ollama streaming handlers 866 Medium
handlers/anthropic_compat.py Anthropic API adapter 739 Medium
router/registry.py Model capability registry 671 Medium
services/ceo_micromanager.py Tier ladder, decomposition, subtask briefs 643 Medium
services/ceo_ledger.py Durable goal/subtask/attempt record 616 Medium
router/model_router.py ModelRouter — central routing logic 529 HIGH
services/ceo_supervisor.py 24x7 sweep: close / re-drive / abandon goals 497 HIGH
agent/web_reach.py Zero-key read-only internet access 460 RISKY
langfuse_obs.py Langfuse trace emission 451 Low
packages/config/settings.py Central settings / env resolution 415 Medium
packages/auth/rbac.py Role-based access control 391 RISKY
key_store.py API key CRUD, SHA-256 hashing, persistence 305 RISKY
services/ceo_quality.py Anti-slop gate + bounded escalation ladder 222 Medium
agent/tools.py WorkspaceTools — filesystem read/write 210 RISKY
handlers/v3_auth.py JWT validation 177 RISKY
router/classifier.py Task classification 172 Medium

Read the full file on GitHub · 283 lines

Changes

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.

  1. 4d ago Changed · +47 lines · +705 tokens per session 275b0f72a3ef
  2. 7d ago First seen · 236 lines · 2,771 tokens per session scan A 490e96be45a2

Subscribe to this mod's changes

autonomous-ai-agency AGENTS.md is an instructions file published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed yesterday), licensed MIT. It adds 3,476 tokens to every session, about $0.0174 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 2026-09-03.

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