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Kahtaf
GitHub 创作者资料

Kahtaf

按仓库查看 1 个 GitHub 仓库中的 9 个已收集 skills。

已收集 skills
9
仓库
1
更新
2026-07-08
仓库分布

Skills 分布在哪些仓库

按已收集 skill 数展示主要仓库,并显示它们在该创作者目录中的占比和职业覆盖。

仓库浏览

仓库与代表性 skills

codex-first
软件开发工程师

Route implementation work to Codex CLI; Claude specs, reviews, verifies.

2026-07-08
autoreview
软件质量保证分析师与测试员

Run OpenCandle's repo-local autoreview helper for local branch, PR, or commit review. Use when the user asks for autoreview, PR review, second-model review, or a final closeout review before commit, push, merge, or release.

2026-07-03
openspec-apply-change
软件开发工程师

Implement tasks from an OpenSpec change. Use when the user wants to start implementing, continue implementation, or work through tasks.

2026-06-26
openspec-archive-change
软件开发工程师

Archive a completed change in the experimental workflow. Use when the user wants to finalize and archive a change after implementation is complete.

2026-06-26
openspec-propose
软件开发工程师

Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.

2026-06-26
graphify
软件开发工程师

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

2026-06-13
graphify
软件开发工程师

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

2026-06-13
prompt-engineering-patterns
软件开发工程师

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

2026-05-24
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