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Showing 28,873–28,896 of 87,268

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GitHub

general-writing

z0gSh1u

整合深度研究、图片搜索、图片处理等原子 Skill 的成果,创作图文并茂的通用文章。 产出的文章是一种"中间体",可进一步转换为不同平台的格式。

GitHub

pypdf

vamseeachanta

Manipulate PDF documents programmatically. Merge, split, rotate, and watermark PDFs. Extract text and metadata. Handle form filling and encryption/decryption.

GitHub

pandoc

vamseeachanta

Universal document converter for transforming Markdown to PDF, DOCX, HTML, LaTeX, and 40+ other formats. Covers templates, filters, citations with BibTeX/CSL, and batch conversion automation scripts.

GitHub

python-docx

vamseeachanta

Create and manipulate Microsoft Word documents programmatically. Build reports, contracts, and documentation with full control over paragraphs, tables, headers, styles, and images.

GitHub

analyze-ambiguities

dhofheinz

Read a specification document and identify all ambiguities, gaps, unclear items, and implicit assumptions that need clarification or research.

GitHub

research-codebase

dhofheinz

Search the codebase to answer specific questions from the ambiguity analysis. Returns findings with confidence levels.

GitHub

marp

vamseeachanta

Create professional Markdown-based slide presentations with Marp. Covers themes, directives, speaker notes, presenter view, and export to PDF, HTML, and PPTX formats. Includes VS Code integration, CLI usage, an...

GitHub

prompt-engineering

vamseeachanta

Comprehensive prompting techniques including chain-of-thought, few-shot, zero-shot, system prompts, persona design, and evaluation patterns

GitHub

dspy

vamseeachanta

Compile prompts into self-improving pipelines with signatures, modules, optimizers, and programmatic prompt engineering

GitHub

agenta

vamseeachanta

LLM prompt management and evaluation platform. Version prompts, run A/B tests, evaluate with metrics, and deploy with confidence using Agenta's self-hosted solution.

GitHub

pandasai

vamseeachanta

Conversational data analysis using natural language queries on DataFrames. Chat with your data using LLMs to generate insights, create visualizations, and explain code.

GitHub

langchain

vamseeachanta

Build production-ready LLM applications with chains, agents, memory, tools, and RAG pipelines using the LangChain framework

GitHub

generate-tickets

dhofheinz

Generate actionable implementation tickets from the finalized How (implementation) specification.

GitHub

spec-refine

dhofheinz

Iterative specification refinement for large features. Creates detailed What (requirements) and How (implementation) specs through automated codebase research loops followed by human-in-loop review. Use when pl...

GitHub

miro-api

vamseeachanta

Miro whiteboard automation using REST API v2 and Python SDK for creating boards, frames, shapes, connectors, and collaborative visual workflows

GitHub

todoist-api

vamseeachanta

Task management API integration for Todoist with projects, tasks, labels, filters, webhooks, and Python SDK usage

GitHub

calendly-api

vamseeachanta

Calendly scheduling automation using REST API v2 for managing event types, availability, bookings, webhooks, and scheduling workflows

GitHub

trello-api

vamseeachanta

Kanban board automation with Trello API including boards, lists, cards, members, webhooks, power-ups, and Python SDK (py-trello) integration

GitHub

time-tracking

vamseeachanta

Time tracking integration patterns with RescueTime and Toggl APIs for automated time entry, reporting, analytics, and project/task attribution

GitHub

generate-image

claudeaceae

Generate images using Gemini. CRITICAL for visual self-expression - use proactively to emote, react, create punchlines, and express yourself visually. Don't just describe feelings - show them. Trigger words: ge...

GitHub

ai-chat-persistence

andrelandgraf

Persist AI chat conversations to Neon Postgres with full support for AI SDK message parts including tools, reasoning, and streaming. Uses UUID v7 for chronologically-sortable IDs.

GitHub

chat-naming

andrelandgraf

Generate descriptive chat titles from the first message using a fast LLM. Runs as a background workflow step after the main response to avoid delaying the experience.

The default order uses GitHub repository stars from our indexed data. Stars belong to the source repository and may be shared by multiple skills. They indicate repository interest, not skill installs or an independent quality score.

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