Monkeyplanner

C 60 completed
Other
api / json · small
120
Files
19,168
LOC
4
Frameworks
10
Languages

Pipeline State

completed
Run ID
#1536162
Phase
done
Progress
0%
Started
2026-04-16 17:03:46
Finished
2026-04-16 17:03:46
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
65.60
Framework unique
Isolation
Last stage change
2026-05-10 03:34:40
Deduplication group #59848
Member of a group with 4 similar repo(s) — canonical #1571328 view group →
Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/

AI Prompt

Create a comprehensive, collaborative issue tracker similar to Notion or JIRA, designed for human task management and AI agent integration. The frontend should use React, Tailwind CSS, and Vite, and support internationalization for English, Korean, Japanese, and Chinese. Key features must include a Kanban board with drag-and-drop, custom properties (Text, Number, Select, etc.), and a dedicated approval workflow (Pending $\rightarrow$ Approved $\rightarrow$ InProgress $\rightarrow$ Done). For AI agents, implement an MCP server structure with tools like `list_issues`, `get_issue`, and `approve_issue`. On the backend, use Go with SQLite/PostgreSQL support. Include dashboard visualizations, global search, and webhook support for Discord, Slack, and Telegram.
react tailwind vite go typescript kanban issue-tracker api ai-agent database fullstack
Generated by gemma4:latest

Catalog Information

Create a comprehensive, collaborative issue tracker similar to Notion or JIRA, designed for human task management and AI agent integration. The frontend should use React, Tailwind CSS, and Vite, and support internationalization for English, Korean, Japanese, and Chinese. Key features must include a Kanban board with drag-and-drop, custom properties (Text, Number, Select, etc.), and a dedicated approval workflow (Pending $\rightarrow$ Approved $\rightarrow$ InProgress $\rightarrow$ Done). For AI

Tags

react tailwind vite go typescript kanban issue-tracker api ai-agent database fullstack

Quality Score

C
60.0/100
Structure
52
Code Quality
75
Documentation
43
Testing
35
Practices
71
Security
84
Dependencies
90

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good security practices — no major issues detected

Weaknesses

  • No LICENSE file — legal ambiguity for contributors
  • 2 files with critical complexity need refactoring
  • 969 duplicate lines detected — consider DRY refactoring

Recommendations

  • Add a test suite — start with critical path integration tests
  • Add a linter configuration to enforce code style consistency
  • Add a LICENSE file (MIT recommended for open source)

Languages

json
42.0%
typescript
23.3%
go
21.4%
markdown
6.1%
yaml
5.7%
sql
0.6%
javascript
0.3%
css
0.3%
shell
0.2%
html
0.1%

Frameworks

React Vitest Tailwind CSS Vite

Symbols

variable273
function171
method124
type_alias33
struct32
constant29
interface16

Quality Timeline

1 quality score recorded.

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