Ai Handoff

C 69 completed
Framework
cli / python · small
132
Files
11,381
LOC
0
Frameworks
8
Languages

Pipeline State

completed
Run ID
#348775
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
69.67
Framework unique
Isolation
Last stage change
2026-05-10 03:35:10
Deduplication group #55751
Member of a group with 2 similar repo(s) — this repo is canonical view group →
Top concepts (2)
Project DescriptionData/ML
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)

AI Prompt

Create a command-line framework in Python for managing structured handoffs between multiple AI systems, incorporating human oversight. The tool should allow users to initialize agents by specifying names and roles (lead or reviewer) and generate an `ai-handoff.yaml` configuration file. It needs to support a workflow using commands like `/handoff status` to check the project status and `/handoff start [phase]` to begin a new phase, which initiates a plan and review cycle. The framework should guide the user through a lead/reviewer/arbiter pattern and manage state using a JSON file.
python cli ai framework automation workflow command-line llm
Generated by gemma4:latest

Catalog Information

A framework that enables structured handoffs between AI systems with human oversight.

Description

The framework provides a standardized protocol for passing data, models, and decisions from one AI system to another while keeping a human operator in the loop. It defines clear interfaces, metadata, and validation steps to ensure that each handoff is traceable and auditable. Developers can plug in their own AI components and rely on the framework to manage state, versioning, and error handling across the workflow. The system is designed for complex, multi‑model pipelines where coordination and accountability are critical. It helps teams build reliable, maintainable AI services that comply with governance and safety requirements.

الوصف

يُقدِّم الإطار بروتوكولاً موحداً لنقل البيانات والنماذج والقرارات من نظام ذكاء اصطناعي إلى آخر مع إبقاء المشرف البشري في الحلقة. يعرِّف واجهات واضحة، وبيانات وصفية، وخطوات تحقق لضمان تتبع كل تحويل وتوثيقه. يتيح للمطورين توصيل مكوّناتهم الذكائية الخاصة والاعتماد على الإطار لإدارة الحالة، وإصدار النسخ، ومعالجة الأخطاء عبر سير العمل. صُمم للتعامل مع خطوط الأنابيب المعقدة التي تتطلب تنسيقاً وتفويضاً واضحاً. يساهم في بناء خدمات ذكاء اصطناعي موثوقة وقابلة للصيانة، مع الالتزام بمعايير الحوكمة والسلامة. يدمج آليات المراجعة البشرية لتقليل الأخطاء وتحسين الشفافية. يسهِّل على الفرق تحقيق التعاون بين نماذج متعددة دون فقدان السيطرة على النتائج.

Novelty

8/10

Tags

ai-collaboration structured-handoffs human-oversight ai-workflow-orchestration model-coordination decision-support ai-governance

Claude Models

claude-opus-4.6 claude-opus-4.5

Quality Score

C
69.4/100
Structure
69
Code Quality
74
Documentation
80
Testing
50
Practices
56
Security
92
Dependencies
60

Strengths

  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Good security practices \u2014 no major issues detected

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • No CI/CD configuration \u2014 manual testing and deployment
  • 438 duplicate lines detected \u2014 consider DRY refactoring
  • 1 'god files' with >500 LOC need decomposition

Recommendations

  • Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
  • Add a LICENSE file (MIT recommended for open source)

Security & Health

5.6h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (1)
Want this analysis on your repo? https://repobility.com/scan/
MIT
License
1.9%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

python
43.6%
markdown
35.8%
javascript
12.2%
css
6.2%
html
1.4%
toml
0.4%
shell
0.3%
yaml
0.0%

Frameworks

None detected

Concepts (2)

Scored by Repobility's multi-pass pipeline · https://repobility.com
CategoryNameDescriptionConfidence
Repobility · severity-and-effort ranking · https://repobility.com
auto_descriptionProject DescriptionA collaboration framework for structured AI-to-AI handoffs with human oversight.80%
auto_categoryData/MLdata-ml70%

Quality Timeline

1 quality score recorded.

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