Amure Do

D 52 completed
Other
monorepo / rust · small
83
Files
13,922
LOC
2
Frameworks
8
Languages

Pipeline State

completed
Run ID
#1545211
Phase
done
Progress
0%
Started
2026-04-16 23:11:18
Finished
2026-04-16 23:11:18
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
73.33
Framework unique
Isolation
Last stage change
2026-05-10 03:34:51
Deduplication group #1938257
Member of a group with 1 similar repo(s) — this repo is canonical view group →
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)

AI Prompt

Create a hypothesis-driven research engine, similar to amure-do. I need a system that structures research by managing Claims, Reasons, Evidence, Experiments, and Verdicts. It should enforce rigor using multiple quality gates like the Claim Gate and Argument Gate. The engine must support pluggable backends (HTTP, File-based, Subprocess) and integrate with various LLM providers, supporting at least Claude, OpenAI, and Ollama. Finally, build a web dashboard with a 4-tab interface (Research, Knowledge, Lab, Settings) and a Canvas for idea mapping. The core logic should be written in Rust, using an async runtime like Tokio.
rust monorepo research-engine llm web-dashboard async api knowledge-graph
Generated by gemma4:latest

Catalog Information

Create a hypothesis-driven research engine, similar to amure-do. I need a system that structures research by managing Claims, Reasons, Evidence, Experiments, and Verdicts. It should enforce rigor using multiple quality gates like the Claim Gate and Argument Gate. The engine must support pluggable backends (HTTP, File-based, Subprocess) and integrate with various LLM providers, supporting at least Claude, OpenAI, and Ollama. Finally, build a web dashboard with a 4-tab interface (Research, Knowled

Tags

rust monorepo research-engine llm web-dashboard async api knowledge-graph

Quality Score

D
51.6/100
Structure
48
Code Quality
52
Documentation
48
Testing
40
Practices
57
Security
72
Dependencies
80

Strengths

  • Consistent naming conventions (snake_case)

Weaknesses

  • No LICENSE file — legal ambiguity for contributors
  • No CI/CD configuration — manual testing and deployment
  • 1537 duplicate lines detected — consider DRY refactoring
  • 6 'god files' with >500 LOC need decomposition

Recommendations

  • 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)

Languages

rust
78.5%
html
10.2%
markdown
5.0%
python
4.7%
toml
0.9%
javascript
0.5%
text
0.1%
json
0.1%

Frameworks

Flask Axum

Symbols

function407
struct154
extension42
constant29
enum24
variable12
method4
type_alias3
class1

API Endpoints (8)

All metrics by Repobility · https://repobility.com
MethodPathHandlerFramework
Open data scored by Repobility · https://repobility.com
GET/api/eventsapi_eventsFastAPI/Flask
GET/api/narrativesapi_narrativesFastAPI/Flask
POST/api/pipelineapi_pipelineFastAPI/Flask
GET/api/searchapi_searchFastAPI/Flask
POST/execexec_codeFastAPI/Flask
POST/execexec_codeFastAPI/Flask
GET/healthhealthFastAPI/Flask
GET/healthhealthFastAPI/Flask

Quality Timeline

1 quality score recorded.

View File Metrics
Repobility · open methodology · https://repobility.com/research/

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BinComp Dependency Hardening

All packages →
4 of this repo's dependencies have been scanned for binary hardening. Grade reflects RELRO / stack canary / FORTIFY / PIE coverage.
Nflask3.1.3 · 0 gadgets · risk 574.2Fnumpy2.4.4 · 6,596 gadgets · risk 0.0Fpandas3.0.2 · 6,381 gadgets · risk 0.0Fscipy1.17.1 · 21,805 gadgets · risk 0.0