Run Agent

C+ 72 completed
Other
containerized / shell · small
75
Files
3,577
LOC
0
Frameworks
8
Languages

Pipeline State

completed
Run ID
#350284
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Skipped
Decision
skip_scaffold_dup
Novelty
25.96
Framework unique
Isolation
Last stage change
2026-04-16 18:15:42
Deduplication group #48127
Member of a group with 1 similar repo(s) — canonical #118574 view group →
Top concepts (2)
Project DescriptionDevOps/Infrastructure
Repobility · code-quality intelligence · https://repobility.com

AI Prompt

Create a system that allows me to split complex development tasks across multiple AI Agents. I want the system to research, implement, review, and test code in parallel, treating the codebase like a real team project. The core functionality should involve an orchestrator that delegates work to specialized agents, such as research, implementation, review, and testing. Please ensure the setup supports monitoring the agents' progress and handles communication between them. The system should be containerized and use shell scripting for execution.
shell containerization ai-agents automation development-workflow orchestration scripting llm
Generated by gemma4:latest

Catalog Information

Split complex tasks across multiple AI Agents that research, implement, review, and test in parallel -- so each agent stays focused and your codebase gets treated like a real team project. Built by Eugene Petrenko.

Description

Split complex tasks across multiple AI Agents that research, implement, review, and test in parallel -- so each agent stays focused and your codebase gets treated like a real team project. Built by Eugene Petrenko.

Novelty

3/10

Tags

shell containerization ai-agents automation development-workflow orchestration scripting llm

Claude Models

claude-opus-4-6

Quality Score

C+
71.9/100
Structure
67
Code Quality
80
Documentation
56
Testing
65
Practices
69
Security
100
Dependencies
60

Strengths

  • CI/CD pipeline configured (github_actions)
  • Consistent naming conventions (kebab-case)
  • Good security practices \u2014 no major issues detected
  • Containerized deployment (Docker)
  • Properly licensed project

Recommendations

  • Add a linter configuration to enforce code style consistency

Security & Health

4.1h
Tech Debt (C)
A
OWASP (100%)
PASS
Quality Gate
A
Risk (3)
Generated by Repobility's multi-pass static-analysis pipeline (https://repobility.com)
Apache-2.0
License
20.3%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

shell
38.3%
html
23.0%
markdown
17.8%
css
10.8%
python
6.7%
yaml
2.8%
toml
0.5%
text
0.2%

Frameworks

None detected

Concepts (2)

Analysis by Repobility (https://repobility.com) · MCP-ready
CategoryNameDescriptionConfidence
Repobility (the analyzer behind this table) · https://repobility.com
auto_descriptionProject DescriptionSplit complex tasks across multiple AI Agents that research, implement, review, and test in parallel -- so each agent stays focused and your codebase gets treated like a real team project. Built by Eugene Petrenko.80%
auto_categoryDevOps/Infrastructuredevops-infra70%

Quality Timeline

1 quality score recorded.

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