Eflclaw

D 55 completed
Other
monorepo / rust · medium
1,083
Files
270,995
LOC
5
Frameworks
15
Languages

Pipeline State

completed
Run ID
#325439
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0
Previous runs
Open methodology · Repobility · https://repobility.com/research/
#StatusPhaseStartedFinished
Repobility · MCP-ready · https://repobility.com
#49881failedCREDENTIAL_SCAN2026-03-19 23:41:36

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
69.40
Framework unique
Isolation
Last stage change
2026-05-10 03:35:31
Deduplication group #61652
Member of a group with 2 similar repo(s) — this repo is canonical view group →
Top concepts (2)
Project DescriptionWeb Frontend
About: code-quality intelligence by Repobility · https://repobility.com

AI Prompt

Create a description for an AI agent runtime based on the provided repository structure. The agent should feature persistent memory, proactive voice capabilities, and a highly modular architecture, all built using pure Rust. I need to highlight its ability to handle multi-channel messaging (like Telegram and Email), full-text search over conversation history, and support for text-to-speech voice messages. The project should feel production-ready and be a fork of an existing project, emphasizing its robustness over the upstream version.
rust ai-agent runtime memory modular voice telegram email llm
Generated by gemma4:latest

Catalog Information

Persistent memory. Proactive voice. Modular architecture. Production-ready AI agent runtime in pure Rust.

Description

Persistent memory. Proactive voice. Modular architecture. Production-ready AI agent runtime in pure Rust.

Novelty

3/10

Tags

rust ai-agent runtime memory modular voice telegram email llm

Claude Models

claude-opus-4-6

Quality Score

D
54.6/100
Structure
71
Code Quality
40
Documentation
76
Testing
55
Practices
45
Security
40
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Code linting configured (ruff (possible))
  • Consistent naming conventions (snake_case)
  • Containerized deployment (Docker)

Weaknesses

  • No LICENSE file \u2014 legal ambiguity for contributors
  • 3 files with critical complexity need refactoring
  • Potential hardcoded secrets in 31 files
  • 53831 duplicate lines detected \u2014 consider DRY refactoring
  • 116 'god files' with >500 LOC need decomposition

Recommendations

  • Add a LICENSE file (MIT recommended for open source)
  • Move hardcoded secrets to environment variables or a secrets manager
  • Address 661 TODO/FIXME items \u2014 consider tracking them as issues

Security & Health

225.8h
Tech Debt (B)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (2)
Repobility — the code-quality scanner for AI-generated software · https://repobility.com
Apache-2.0
License
10.9%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

rust
72.1%
markdown
10.7%
json
5.9%
python
4.1%
typescript
3.1%
shell
1.6%
javascript
0.7%
kotlin
0.6%
css
0.5%
yaml
0.3%
toml
0.3%
xml
0.1%

Frameworks

React Jetpack Compose Axum pytest Vite

Concepts (2)

Findings produced by Repobility · scan your repo at https://repobility.com/scan/
CategoryNameDescriptionConfidence
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auto_descriptionProject DescriptionPersistent memory. Proactive voice. Modular architecture. Production-ready AI agent runtime in pure Rust.80%
auto_categoryWeb Frontendweb-frontend70%

Quality Timeline

1 quality score recorded.

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