AutoHarness

Source#

• Repository: aiming-lab/AutoHarness
• Last source update: 2026-04-05
• Last verified: 2026-04-05

Tags#

Integration notes#

Framework-level abstraction; derive bounded worker contracts from concrete tasks and APIs in docs/examples.

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: autoharness-repo-derived-worker
name: AutoHarness Repo-Derived Worker
version: 1.0.0
source_registry_url: https://worker.md/registry/autoharness/
source_repository: https://github.com/aiming-lab/AutoHarness
repository_default_branch: main
repository_language: Python
repository_license: MIT
repository_updated_at: 2026-04-05
worker_mode: agent-orchestration-worker
derivation_method: github_repository_metadata_plus_raw_readme
derivation_confidence: 0.95
derived_on: 2026-04-05
tags:
  - agent-framework
  - ai-agents
  - audit
  - context-management
  - governance
  - harness-engineering
---

# AutoHarness Repo-Derived Worker

## Repo-derived summary
- Registry summary: AutoHarness: Automated Harness Engineering for AI Agents
- Repository description: AutoHarness: Automated Harness Engineering for AI Agents
- Stars (snapshot): 181
- Primary language: Python
- Worker mode classification: agent-orchestration-worker

## Extracted from
- https://github.com/aiming-lab/AutoHarness
- https://github.com/aiming-lab/AutoHarness/blob/main/README.md
- https://github.com/aiming-lab/AutoHarness/releases/tag/v0.1.0
- https://docs.anthropic.com/en/docs/claude-code
- https://github.com/aiming-lab/AutoHarness/issues

## Evidence notes (from repository text)
- README summary paragraph: 「Aha」— AutoHarness: Automated Harness Engineering for AI Agents
- 「Aha」— AutoHarness: Automated Harness Engineering for AI Agents
- Every agent deserves an aha moment — the model reasons, we harness the rest.
- > For agents, the ***aha* moment** is when they go from "demo-ready" to truly reliable.
- The gap is enormous: context management, tool governance, cost control, observability, session persistence... These are the patterns that separate a toy from a system. We call this **harness engineering**.
- AutoHarness is a lightweight governance framework **so every agent can have its *aha* moment.**

## Installation hints found in README
- `pip install -e .`

## 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: autoharness-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/autoharness/

Source URL: https://github.com/aiming-lab/AutoHarness