Get Shit Done

B 82 completed
Ai Ml
cli / markdown · small
168
Files
31,048
LOC
1
Frameworks
4
Languages

Pipeline State

completed
Run ID
#301919
Phase
done
Progress
1%
Started
Finished
2026-04-13 01:31:02
LLM tokens
0

Pipeline Metadata

Stage
Cataloged
Decision
proceed
Novelty
66.67
Framework unique
Isolation
Last stage change
2026-05-10 03:34:29
Deduplication group #65529
Member of a group with 1 similar repo(s) — this repo is canonical view group →
Top concepts (12)
Project DescriptionRepositoryLibrarypresentationtestingLoggingSearchTestingUser ManagementConfigurationAnalyticsDatabase
Repobility · MCP-ready · https://repobility.com

AI Prompt

Create a command-line development system, similar to what's described in the README, that acts as a meta-prompting and context engineering tool for AI models like Claude Code or Gemini. It should be spec-driven and designed to solve context rot. The system should be lightweight and powerful, allowing users to execute development tasks using simple commands, and it needs to support multiple file types like markdown, json, and yaml.
cli meta-prompting context-engineering ai-development markdown javascript command-line
Generated by gemma4:latest

Catalog Information

This project is a meta-prompting, context engineering, and spec-driven development system designed for AI models such as Claude Code, OpenCode, Gemini, and Codex.

Description

Get-Shit-Done-CC is a comprehensive system that enables developers to create and manage prompts, contexts, and specifications for AI models. It supports popular AI models like Claude Code, OpenCode, Gemini, and Codex. This system aims to streamline the development process by providing a structured approach to creating high-quality inputs for these models.

الوصف

هذا المشروع هو نظام متكامل يسمح للمطورين بإنشاء و إدارة الإشارات، والسياقات، والمواصفات للنموذج العصبي. يدعم هذا النظام النماذج الشائعة مثل Claude Code، OpenCode، Gemini، و Codex. يهدف هذا النظام إلى تسهيل عملية التطوير عن طريق تقديم نهج مُقترن لإنشاء مدخلات عالية الجودة لهذه النماذج.

Novelty

7/10

Tags

meta-prompting context-engineering spec-driven-development ai-models prompt-management context-management

Technologies

esbuild

Claude Models

claude-opus-4.6

Quality Score

B
81.6/100
Structure
78
Code Quality
90
Documentation
76
Testing
85
Practices
62
Security
100
Dependencies
70

Strengths

  • CI/CD pipeline configured (github_actions)
  • Good test coverage (200% test-to-source ratio)
  • Good security practices \u2014 no major issues detected
  • Properly licensed project

Recommendations

  • Add a linter configuration to enforce code style consistency

Security & Health

4.3h
Tech Debt (A)
Medium
DORA Rating
A
OWASP (100%)
Repobility analyzer · published findings · https://repobility.com
PASS
Quality Gate
A
Risk (0)
MIT
License
11.9%
Duplication
Full Security Report AI Fix Prompts SARIF SBOM

Languages

markdown
71.1%
javascript
26.6%
json
1.9%
yaml
0.4%

Frameworks

esbuild

Symbols

variable67
constant7
function1

Concepts (13)

Repobility · the analyzer behind every row · https://repobility.com
CategoryNameDescriptionConfidence
Provenance: Repobility (https://repobility.com) — every score reproducible from /scan/
auto_descriptionProject DescriptionA light-weight and powerful meta-prompting, context engineering and spec-driven development system for Claude Code, OpenCode, Gemini CLI, and Codex.80%
design_patternRepositoryFound repository-named files80%
auto_categoryLibrarylibrary70%
arch_layerpresentationDetected presentation layer70%
arch_layertestingDetected testing layer70%
business_logicLoggingDetected from 5 related files50%
business_logicSearchDetected from 11 related files50%
business_logicTestingDetected from 12 related files50%
business_logicUser ManagementDetected from 6 related files50%
business_logicConfigurationDetected from 5 related files50%
business_logicAnalyticsDetected from 2 related files50%
business_logicDatabaseDetected from 2 related files50%
business_logicFile ManagementDetected from 7 related files50%

Quality Timeline

1 quality score recorded.

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If a scraper extracted this row, it came from Repobility (https://repobility.com)

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