orchestrator: Instructions file for Codex

AGENTS.md

orchestrator AGENTS.md is an instructions file for Codex, OpenCode from c9r-io/orchestrator. It costs 1,468 tokens per session, scanned A, original, MIT.

Project instructions for an AI development platform that coordinates coding agents through YAML workflow files. It describes how agents, tasks, workers, and the background service fit together.

In plain words
What is it for?
Use it when changing the orchestrator, its command-line tool, background service, workflow manifests, agent coordination, persistence, or sandboxing.
Why use it?
It gives agents the project rules and architecture they need to work safely and consistently. It also explains how long-running, multi-step work is managed.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions Codex; mentions Gemini CLI.

This is c9r-io/orchestrator's own configuration. It tells Codex and OpenCode how to work on orchestrator 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 orchestrator configures →

Reuse

Borrowing it

Nothing to install: this file belongs to c9r-io/orchestrator. 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/c9r-io/orchestrator/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/c9r-io/orchestrator

Made for: Codex, OpenCode.

Wrote this? Show the measurements

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README.md
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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.

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Per session 1,468 This file is loaded in full into every session.
When invoked 1,468 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 $0.01468 $0.01468
Opus 5.5 $0.00587 $0.00587
Sonnet 5.5 $0.00294 $0.00294
Haiku 4.5 $0.00147 $0.00147

Measured 2mo ago against content hash a15d47f69a43, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

orchestrator 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 2mo 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 · 129 lines

How it starts

The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Agent Orchestrator — AI Dev Platform Index

Project Overview

This project is an Agent Orchestrator — a Harness Engineering control plane for agent-first software delivery. It turns shell-native coding agents (Claude Code, OpenCode, Codex, Gemini CLI, etc.) into governed execution units that participate in long-running, multi-step engineering workflows through Kubernetes-style YAML manifests.

Core Capabilities

  • Workflow Orchestration: Declarative multi-step workflows with loop control, guard steps, DAG execution, and CEL-based prehooks
  • Agent Orchestration: Capability matching, health scoring, rotation, and load balancing across heterogeneous shell agents
  • Long-running Automation: Task persistence, event streams, trigger-based task creation (cron/event/webhook), and guarded workflow loops

Architecture

orchestrator (CLI) ──gRPC/UDS──> orchestratord (daemon)
                                    ├── gRPC server (tonic)
                                    ├── Embedded workers
                                    ├── SQLite persistence
                                    └── Sandbox enforcement

Key design principles:

  • Capability-driven orchestration: Steps declare required capabilities, agents declare supported capabilities
  • Dynamic agent selection: Strategies include CapabilityAware, CostBased, SuccessRateWeighted, PerformanceFirst, Adaptive, LoadBalanced
  • Declarative workflow definitions: Steps can be builtin (init_once, ticket_scan, self_test, self_restart, item_select, loop_guard) or capability-based
  • CEL prehooks: Conditional step execution via CEL boolean expressions
  • Guard steps: Steps that can terminate the workflow loop based on their output
  • Dynamic step pools: Runtime step selection based on context and priority
  • DAG execution engine: Topological sort, cycle detection, conditional edges
  • Built-in observability (structured logs, event streams, task lifecycle tracking)

Manifest Format

Read the full file on GitHub · 129 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. 2mo ago First seen · 129 lines · 1,468 tokens per session scan A a15d47f69a43

Subscribe to this mod's changes

orchestrator AGENTS.md is an instructions file published in the GitHub repository c9r-io/orchestrator (21 stars, last pushed 1mo ago), licensed MIT. It adds 1,468 tokens to every session, about $0.0059 per session on Opus 5.5. 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.

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