Ai Legal Intake
D 57 completed
Other
unknown / javascript · tiny
13
Files
2,510
LOC
1
Frameworks
4
Languages
Pipeline State
completedRun ID
#376472Phase
doneProgress
1%Started
Finished
2026-04-13 01:31:02LLM tokens
0Pipeline Metadata
Stage
SkippedDecision
skip_scaffold_dupNovelty
29.96Framework unique
—Isolation
—Last stage change
2026-04-16 18:15:42Deduplication group #47745
Member of a group with 1 similar repo(s) — canonical #96362 view group →
Top concepts (2)
Project DescriptionWeb Backend
Repobility analyzer · published findings · https://repobility.com
AI Prompt
Create a comprehensive AI-powered lead intake system assessment for a law firm client. I need the structure to demonstrate two implementation approaches: one using n8n workflows and another using code. For the coded approach, please use JavaScript with Express for the backend, and also include a Python FastAPI example. The system must incorporate a two-layer qualification engine, handle errors with retry and dead letter queue logic, and use OpenAI function calling to ensure structured JSON output. Please organize the output to include the main assessment document, architecture diagrams (Mermaid format), and the necessary code files for both the JS/Express and Python implementations.
javascript python express fastapi ai n8n lead-intake automation openai backend
Generated by gemma4:latest
Catalog Information
This is my skills assessment for the AI & Automations Integration Specialist role at Lion Head. I've designed a complete AI-powered lead intake system for law firm clients, presenting two implementation approaches to demonstrate both no-code automation and coding skills.
Description
This is my skills assessment for the AI & Automations Integration Specialist role at Lion Head. I've designed a complete AI-powered lead intake system for law firm clients, presenting two implementation approaches to demonstrate both no-code automation and coding skills.
Novelty
3/10Tags
javascript python express fastapi ai n8n lead-intake automation openai backend
Technologies
express openai
Claude Models
claude-opus-4-6
Quality Score
D
56.7/100
Structure
41
Code Quality
75
Documentation
59
Testing
0
Practices
73
Security
100
Dependencies
60
Strengths
- Good security practices \u2014 no major issues detected
Weaknesses
- No LICENSE file \u2014 legal ambiguity for contributors
- No tests found \u2014 high risk of regressions
- No CI/CD configuration \u2014 manual testing and deployment
Recommendations
- Add a test suite \u2014 start with critical path integration tests
- Set up CI/CD (GitHub Actions recommended) to automate testing and deployment
- Add a linter configuration to enforce code style consistency
- Add a LICENSE file (MIT recommended for open source)
Security & Health
4.6h
Tech Debt (D)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (4)
Methodology: Repobility · https://repobility.com/research/state-of-ai-code-2026/
Unknown
License
4.0%
Duplication
Languages
Frameworks
Express
Concepts (2)
| Category | Name | Description | Confidence | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Open data scored by Repobility · https://repobility.com | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_description | Project Description | This is my skills assessment for the AI & Automations Integration Specialist role at Lion Head. I've designed a complete AI-powered lead intake system for law firm clients, presenting two implementation approaches to demonstrate both no-code automation and coding skills. | 80% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| auto_category | Web Backend | web-backend | 70% | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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