Tracelight
D 55 completed
Other
containerized / json · tiny
23
Files
5,032
LOC
0
Frameworks
5
Languages
Pipeline State
completedRun ID
#1545754Phase
doneProgress
0%Started
2026-04-16 23:32:25Finished
2026-04-16 23:32:25LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
28.02Framework unique
—Isolation
—Last stage change
2026-05-10 03:34:51Deduplication group #47389
Member of a group with 182 similar repo(s) — canonical #1447986 view group →
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🧪 Code Distillation
Browse all specs →AI Prompt
Create a web application, similar to Tracelight, that visualizes hidden offshore connections between world leaders using real ICIJ data. The frontend should feature a 3D force-directed network graph built with Three.js, allowing users to select "Power Players" from a grid of politically exposed persons. The core logic needs a backend API that uses a PathFinder walker agent to trace connections through shell companies and intermediaries. This agent should leverage a Python SQLite database for pathfinding and use an LLM call, specifically a `by llm()` function, to generate a structural narrative summary based only on the discovered graph facts. The system should expose REST endpoints for searching and investigating connections.
javascript three.js python web-app graph-visualization llm api sqlite data-analysis network-graph
Generated by gemma4:latest
Catalog Information
Create a web application, similar to Tracelight, that visualizes hidden offshore connections between world leaders using real ICIJ data. The frontend should feature a 3D force-directed network graph built with Three.js, allowing users to select "Power Players" from a grid of politically exposed persons. The core logic needs a backend API that uses a PathFinder walker agent to trace connections through shell companies and intermediaries. This agent should leverage a Python SQLite database for pat
Tags
javascript three.js python web-app graph-visualization llm api sqlite data-analysis network-graph
Quality Score
D
55.3/100
Structure
46
Code Quality
75
Documentation
51
Testing
0
Practices
64
Security
100
Dependencies
80
Strengths
- Consistent naming conventions (snake_case)
- Good security practices — no major issues detected
- Containerized deployment (Docker)
- Properly licensed project
Weaknesses
- No tests found — high risk of regressions
- No CI/CD configuration — manual testing and deployment
- 175 duplicate lines detected — consider DRY refactoring
- 1 'god files' with >500 LOC need decomposition
Recommendations
- Add a test suite — 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
Languages
Frameworks
None detected
Symbols
function33
constant17
variable3
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