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agent-os

An operating system for coordinating specialized AI agents.

Structured briefs. Verification gates. Memory that survives sessions.

License: MIT Docs PRs Welcome


Most multi-agent frameworks treat agents as interchangeable workers: you describe a task, an agent reports success, and you discover later that the work was never done. agent-os is a set of patterns for the opposite approach — narrow specialists, explicit contracts, and completion that has to be proven rather than claimed.

It is framework-agnostic. There is nothing to install; these are documented patterns you implement in whatever agent runtime you already use.

Contents

Why this exists

Three failures show up repeatedly when delegating real work to agents:

Failure What it looks like
Unverified completion The agent reports success. The build was never run.
Scope drift A narrow task quietly becomes a refactor of unrelated code.
Lost context Every session starts from zero; the same corrections get repeated.

agent-os addresses each with a specific mechanism: verification gates, delegation contracts, and persistent memory.

How it works

Work flows through an orchestrator that never executes tasks itself. It plans, delegates to a specialist, then independently validates the result before reporting back.

                    ┌──────────────────────┐
   request ────────▶│     ORCHESTRATOR     │
                    │  plan → delegate →   │
   report  ◀────────│  validate → report   │
                    └──────────┬───────────┘
                               │  brief + acceptance criteria
              ┌────────────────┼────────────────┐
              ▼                ▼                ▼
      ┌──────────────┐ ┌──────────────┐ ┌──────────────┐
      │  RESEARCHER  │ │   BUILDER    │ │  COMMERCIAL  │
      │ read-only    │ │ writes code  │ │ market data  │
      └──────────────┘ └──────────────┘ └──────────────┘
              │                │                │
              └────────────────┴────────────────┘
                     evidence of completion

The critical property is that the arrow back up carries evidence — build output, HTTP status codes, test results — not an assertion of success.

Core patterns

Pattern Problem it solves Reference
Agent registry Agents with unclear capabilities take on work they cannot do AGENT_REGISTRY_PATTERN.md
Delegation brief Vague instructions produce vague results DELEGATION_PATTERN.md
Memory system Context is lost between sessions MEMORY_PATTERN.md
Scheduled continuity Recurring jobs re-report unchanged information CRON_PATTERN.md

Verification gates

A gate is the contract that makes delegation safe. Every brief declares, before work begins, how completion will be proven:

ACCEPTANCE CRITERIA:
- GET /api/documents/<token> returns 200 with application/pdf
- GET /api/documents/<invalid-token> returns 404

VALIDATION:
- npm run build exits 0
- curl -sI $DEPLOY_URL/api/documents/$TOKEN | head -1

An agent that cannot produce this evidence has not finished, regardless of what it reports. Acceptance criteria written after the work are not gates — they are rationalizations.

Usage

1. Define an agent

Each agent needs responsibilities, hard boundaries, and an escalation path.

# Builder

## Responsibilities
- Application code, APIs, database schema, deployment

## Boundaries
- MUST NOT deploy to production without explicit authorization
- MUST NOT report completion without validation output
- MUST NOT modify files outside the declared scope

## Escalation
Architecture decisions beyond the brief's scope → return to orchestrator

2. Write a delegation brief

OBJECTIVE
Add tokenized public document links so recipients can open a file without an account.

CONTEXT
Documents are currently reachable only behind an authenticated admin session.

REQUIREMENTS
- Add a `pdf_token` column (UUID, unique) to the documents table
- Serve GET /api/documents/<token> with Content-Disposition: inline
- Include the resulting URL in the outbound notification

CONSTRAINTS
- The token is the access control; the route stays unauthenticated
- Existing authenticated download must keep working

ALLOWED SCOPE
- src/api/documents/**, src/db/schema.*, migrations/

ACCEPTANCE CRITERIA
- Valid token returns 200 with application/pdf
- Invalid token returns 404
- Existing admin download still returns 200

VALIDATION
- npm run build exits 0
- curl -sI on both a valid and an invalid token

STOP AND RETURN IF
- The migration conflicts with the existing schema
- Deployment credentials are unavailable

3. Persist what should not be re-learned

## Preferences
- Evidence-based completion reports, not status claims

## Standards
- Edge deployment via Workers; no Node-native database drivers
- RTL-first layout for Arabic interfaces

4. Give recurring jobs continuity

schedule: "0 12 * * *"
prompt: "Pull search analytics, diff against the previous report, surface only changes."
continuity: true   # injects the prior run's output to prevent duplicate reporting

Further examples: research · implementation · planning · commercial · escalation

Skills

Self-contained capabilities that compose with the patterns above.

Skill Purpose
structured-delegation Delegation briefs and the anti-patterns that break them
arabic-edge-pdf Arabic PDF generation at the edge, without font bundling
gps-cluster-engine Proximity clustering under capacity constraints
nextjs-cloudflare-deploy Next.js on Cloudflare Workers, including the dead ends

Integrations

These patterns require no particular vendor. The runtimes below are the ones we have exercised in production.

Integration Role
Cloudflare Workers Edge runtime for orchestration and scheduling
D1 Edge SQLite for agent state and memory
Workers Workflows Durable multi-step execution
Browser Rendering Headless Chrome for PDFs and screenshots
Next.js Application layer for agent-facing interfaces
AnyDoc Document parsing ahead of agent processing

Prior art

agent-os is a pattern library, not a runtime, and is complementary to the frameworks below.

Project Focus Relationship
LangGraph Stateful graph execution Use as the runtime; apply these patterns on top
AutoGen Conversational multi-agent orchestration Overlapping goals, different abstraction
CrewAI Role-based agent crews Similar specialization model, no verification layer

The distinguishing choice here is treating verification as the primary abstraction rather than orchestration.

Contributing

Read the patterns first, then open an issue describing the change before submitting a pull request. Pattern documents should include the failure mode being addressed, not only the recommended approach.

License

MIT © Project Alpha Tech

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The operating system for coordinating specialized AI agents. Structured delegation. Verification gates. Persistent memory.

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