Octopoda-OS

Source#

• Repository: RyjoxTechnologies/Octopoda-OS
• Last source update: 2026-07-19
• Last verified: 2026-07-19

Tags#

Integration notes#

Repository is focused on tool/server interoperability; wrap in bounded worker contracts for production use.

worker.md example#

Starter worker.md contract mapped from this registry entry. Copy this file and adapt schemas, constraints, and statuses for your task.

---
id: octopoda-os-repo-derived-worker
name: Octopoda-OS Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/octopoda-os/
source_repository: https://github.com/RyjoxTechnologies/Octopoda-OS
repository_default_branch: main
repository_language: Python
repository_license: NOASSERTION
repository_updated_at: 2026-07-19
worker_mode: agent-orchestration-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.95
derived_on: 2026-07-19
tags:
  - agent-framework
  - ai-agents
  - ai-memory
  - autogen
  - crash-recovery
  - crewai
---

# Octopoda-OS Repo-Derived Worker

## Repo-derived summary
- Registry summary: The open-source memory and observability layer for AI agents — persistent memory, loop detection, hash-chained audit trails, and a live dashboard, automatic on pip install.
- Repository description: The open-source memory and observability layer for AI agents — persistent memory, loop detection, hash-chained audit trails, and a live dashboard, automatic on pip install.
- Stars (snapshot): 518
- Primary language: Python
- Worker mode classification: agent-orchestration-worker

## Extracted from
- https://github.com/RyjoxTechnologies/Octopoda-OS
- https://github.com/RyjoxTechnologies/Octopoda-OS/blob/main/README.md

## Evidence notes (from repository text)
- README summary paragraph: The open-source memory and observability layer for AI agents. Persistent memory, loop detection, audit trails, and a live dashboard — automatic on pip install .
- The open-source memory and observability layer for AI agents.
- Persistent memory, loop detection, audit trails, and a live dashboard — automatic on pip install .
- Live fleet overview: agent health, operations volume, per-agent scores, the anomaly stream, and the loops caught before they burned tokens. The same dashboard runs locally and in the cloud.
- - [Agents](#agents) · [Memory](#memory) · [Shared memory](#shared-memory) · [Audit trail](#audit-trail)
- - [Framework integrations](#framework-integrations)

## Installation hints found in README
- `pip install</code>.`
- `pip install` and zero infrastructure. When you outgrow local, the same code syncs to the cloud with a single environment variable — no re-architecture, no migration. The whole thing is MIT-licensed.`
- `pip install octopoda`
- `pip install octopoda[server]`

## worker.md contract (derived starter)
Purpose: Execute one orchestrated agent task as a bounded worker step.

### Input schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "task",
    "context"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "task": {
      "type": "string"
    },
    "context": {
      "type": "object"
    }
  }
}
```

### Output schema
```json
{
  "type": "object",
  "additionalProperties": false,
  "required": [
    "run_id",
    "status",
    "result"
  ],
  "properties": {
    "run_id": {
      "type": "string"
    },
    "status": {
      "type": "string",
      "enum": [
        "ok",
        "retryable_error",
        "invalid_request",
        "invalid_output"
      ]
    },
    "result": {
      "type": "object"
    }
  }
}
```

### Constraints
- timeout_seconds: 30
- max_attempts: 2
- idempotency_key: run_id
- status_enum: [ok, retryable_error, invalid_request, invalid_output]
- notes: adapt to concrete APIs/classes documented in this repository before production use

## How this should be used
1. Treat this file as a repo-derived starter profile, not a claim of an official repository API contract.
2. Replace schemas with exact interfaces from code/docs you adopt.
3. Keep execution bounded and auditable using worker protocol constraints.

How to use#

• Save this as a worker spec file (for example: octopoda-os-my-task.worker.md).
• Replace the input/output schemas and purpose with your real bounded task.
• Enforce schema validation + timeout + retry policy in your runtime before production use.

Citation#

Reference URL: https://worker.md/registry/octopoda-os/

Source URL: https://github.com/RyjoxTechnologies/Octopoda-OS