القائمة
LLM application patterns, prompt optimization techniques, and AI-powered data analysis workflows.
يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.
اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
يتجاوز الأمر المباشر Prompt المخصّص للمراجعة. افحص المصدر قبل تشغيله.
npx skills add https://github.com/vamseeachanta/workspace-hub --skill ai-promptingيبقى الأمر في سطر واحد. مرّر أفقيًا لمراجعته كاملًا قبل النسخ.
تفضّل نسخة محلية؟ نزّل الملفات المتاحة حاليًا لدى SkillsMP.
Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
عرض SKILL.md
استنادا إلى تصنيف SOC المهني
| name | ai-prompting |
| version | 1.0.0 |
| category | ai |
| description | LLM application patterns, prompt optimization techniques, and AI-powered data analysis workflows. |
| type | reference |
| tags | [] |
| scripts_exempt | true |
This library contains 5 production-ready skills for building LLM-powered applications, optimizing prompts, and integrating AI into data workflows. Each skill covers a specific aspect of AI application development with patterns for reliability, evaluation, and scaling. Skills follow the Anthropic Skills format with practical examples from real-world AI implementations.
# Browse available skills
ls skills/ai-prompting/
# Read a skill
cat skills/ai-prompting/langchain/SKILL.md
# Skills are documentation - implement patterns in your AI applications
These skills represent patterns refined across production LLM applications processing millions of queries with optimized cost and quality.