소스 정보
- 저장소
- aRustyDev/agents
- 최근 소스 활동
- 2026년 3월 17일 04:20
- 감지된 SKILL.md 언어
- 영어
- 스타
- 8
- 포크
- 3
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/aRustyDev/agents --skill codebase-analysis명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
Strategic search planning for agent-driven research. Generates structured search-term matrices with tiered fallback strategies, engine-specific operators, and grading criteria before executing any searches. Use this skill whenever research requires more than a single search query — comparing technologies, verifying claims across sources, surveying a landscape, investigating a multi-faceted question, or building evidence for a decision. Do NOT use for quick factual lookups, fetching a single known URL, or questions answerable from a single source. Covers tech, academic, regulatory, and general domains. Think of it as "research planning" — the matrix is the plan, execution comes after.
Create language conversion skills for translating code from language A to language B. Use when building 'convert-X-Y' skills, designing type mappings between languages, establishing idiom translation patterns, or defining conversion methodologies. Provides foundational patterns that specific conversion skills extend.
Guide for translating code between programming languages. Use when converting code from one language to another, planning language migrations, understanding conversion challenges, asking about type mappings, idiom translations, or referencing pattern mappings. Covers APTV workflow, type systems, error handling, concurrency, and language-specific gotchas.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | Codebase Analysis |
| version | 1.0.0 |
| description | Extract IR from source code for cross-language conversion |
| category | conversion |
| languages | ["python","typescript","rust","java","go","scala","roc","kotlin","swift","elixir"] |
| tools | ["ir-extract-python","ir-extract-rust","ir-extract-typescript","ir-extract-go","ir-extract-scala","ir-extract-roc"] |
Extract an Intermediate Representation (IR) from source code to enable cross-language conversion and analysis.
/codebase-analysis <path> [--language <lang>] [--depth <0-4>] [--output <format>]
| Parameter | Description | Default |
|---|---|---|
path | File or directory to analyze | Required |
--language | Source language (auto-detected if omitted) | auto |
--depth | IR extraction depth (0-4) | 4 |
--output | Output format (json, yaml, summary) | json |
If --language is not specified, detect based on:
.py, .rs, .ts, .go, .scala, .roc)pyproject.toml, Cargo.toml, package.json)Identify all modules and their relationships:
Extract type definitions and relationships:
Extract function signatures and semantics:
Infer semantic properties:
Mark concepts that may not convert cleanly:
The IR is organized into 5 layers of increasing abstraction:
| Layer | Name | Description |
|---|---|---|
| 0 | Expressions | AST-level expression nodes |
| 1 | Data Flow | Value flow through variables |
| 2 | Control Flow | Execution paths and branches |
| 3 | Type System | Type definitions and relationships |
| 4 | Module Structure | Imports, exports, dependencies |
ir:
version: "1.0"
source_language: "python"
source_path: "src/main.py"
modules:
- name: "main"
imports: [...]
exports: [...]
types:
- name: "User"
kind: "struct"
properties:
- name: "id"
type: "int"
- name: "name"
type: "str"
functions:
- name: "get_user"
parameters:
- name: "id"
type: "int"
return_type: "Optional[User]"
purity: "pure"
annotations:
- kind: "PY-003"
target: "get_user"
message: "Generator usage detected"
severity: "medium"
Gaps are annotated with:
kind: Gap identifier (e.g., "PY-RS-001")target: What element has the gapmessage: Human-readable descriptionseverity: critical, high, medium, low, infosuggestion: Recommended resolution/codebase-analysis src/models.py
/codebase-analysis ./src --language rust --output summary
/codebase-analysis lib/ --depth 2 # Control flow only