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GitHub 저장소

ace-framework

ace-framework에는 jonnabio에서 수집한 skills 14개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.

수집된 skills
14
Stars
6
업데이트
2026-05-04
Forks
3
직업 범위
직업 카테고리 4개 · 100% 분류됨
저장소 탐색

이 저장소의 skills

documentation-generation
소프트웨어 개발자

Procedural knowledge for generating and maintaining code documentation, API specs, and architecture diagrams.

2026-05-04
a2a-communication
소프트웨어 개발자

Procedural knowledge for orchestrating multi-agent systems and Agent-to-Agent (A2A) handoffs.

2026-05-02
agent-design
소프트웨어 개발자

Procedural knowledge for designing autonomous AI agents with tools, memory, and reasoning loops.

2026-05-02
mcp-implementation
소프트웨어 개발자

Procedural knowledge for implementing the Model Context Protocol (MCP) to expose local tools to LLMs.

2026-05-02
accessibility-audit
소프트웨어 품질 보증 분석가·테스터

Procedural knowledge for ensuring frontend interfaces comply with WCAG standards.

2026-05-02
ci-cd-pipeline
소프트웨어 개발자

Procedural knowledge for designing and configuring continuous integration and deployment pipelines.

2026-05-02
error-handling
소프트웨어 개발자

Procedural knowledge for standardizing error boundaries, logging, and graceful degradation.

2026-05-02
performance-optimization
소프트웨어 개발자

Procedural knowledge for identifying bottlenecks and optimizing system performance.

2026-05-02
security-audit
정보 보안 분석가

Procedural knowledge for conducting focused security reviews and enforcing secure coding practices.

2026-05-02
state-management
소프트웨어 개발자

Procedural knowledge for managing application state, data flow, and avoiding race conditions.

2026-05-02
data-pipeline-design
데이터 과학자

Procedural knowledge for designing robust, idempotent, and scalable data pipelines (ETL/ELT).

2026-05-02
feature-engineering
데이터 과학자

Procedural knowledge for transforming raw data into high-value features for machine learning models.

2026-05-02
model-evaluation
데이터 과학자

Procedural knowledge for evaluating machine learning models and AI systems systematically.

2026-05-02
prompt-engineering
소프트웨어 개발자

Procedural knowledge for designing, evaluating, and versioning robust LLM prompts.

2026-05-02