Monkeyplanner
C 60 completed
Other
api / json · small
120
Files
19,168
LOC
4
Frameworks
10
Languages
Pipeline State
completedRun ID
#1536162Phase
doneProgress
0%Started
2026-04-16 17:03:46Finished
2026-04-16 17:03:46LLM tokens
0Pipeline Metadata
Stage
CatalogedDecision
proceedNovelty
65.60Framework unique
—Isolation
—Last stage change
2026-05-10 03:34:40Deduplication 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/
🧪 Code Distillation
Browse all specs →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
Frameworks
React Vitest Tailwind CSS Vite
Symbols
variable273
function171
method124
type_alias33
struct32
constant29
interface16
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