@shareAI-lab
Organization
building everything for Agent AI
28 skills4 repositories 88K
Extract text from PDFs, inspect page counts and document metadata, merge files, or split them into individual pages. Create PDFs from Markdown, HTML, or Python code, using the tools suited to each task.
Design and build AI agents for business, research, operations, or creative work. Define essential actions and knowledge, start with a simple execution loop, and add progress tracking or separate child agents as needs emerge.
Review code for security flaws, bugs, performance problems, maintainability, and test quality. Produce structured feedback with issue locations, likely impact, suggested fixes, positive observations, and a recommendation on whether changes are ready to merge.
Build MCP servers, which let Claude call external tools and read data through a shared protocol. Follow Python or TypeScript examples to implement tools, connect services, configure Claude, and test server behavior.
Draft internal communications such as progress reports, leadership updates, company newsletters, FAQs, and incident reports. The skill selects guidance for the communication type and follows its instructions for format, tone, and information gathering.
Diagnose missing language features in Kode by checking LSP, the protocol connecting code tools to language servers. Update plugin configuration, confirm servers are recognized, and test an operation such as jumping to a definition.
Investigate unexpected tool blocks and repeated permission prompts in Kode. The skill checks approved tools, command restrictions, inherited permissions, and session records, then verifies behavior by repeating the blocked action while preserving required user approval.
Guide an AI agent through feature development, bug fixes, and refactoring with clear requirements, explained design choices, and small, tested changes. Keep human decisions central while making progress and verification results visible.
Test local web applications with Python scripts using Playwright, a browser automation tool. Verify interface behavior, investigate problems, capture screenshots, and inspect browser logs, with a helper that manages one or more application servers.
Create original posters and static artwork by first defining a visual philosophy, then expressing it through color, shapes, spacing, and minimal text. Receive the artwork as PNG or PDF alongside a Markdown design statement.
Configure Kode features by describing the changes you want. The skill inspects settings, adjusts status displays, response styles, and plugins, and verifies changes through settings checks and small practical operations.
Turn scattered notes and discussions into proposals, requirements documents, or decision records. The workflow gathers essential context, builds an outline, drafts sections with feedback, and checks whether readers without prior knowledge can understand the result.
Build working web pages, components, and application interfaces around a clear visual direction. Shape typography, color, spacing, and animation to suit the audience and purpose, producing cohesive designs instead of repetitive, generic layouts.
Build MCP servers, which connect AI agents to external services, using TypeScript or Python. Plan API access, design understandable tools and structured responses, implement authentication and error handling, and check behavior with the intended client.
Turn specialized knowledge and repeatable workflows into an Agent Skill. Work through concrete usage examples, write SKILL.md, organize reusable scripts and resources, and validate the package before producing a distributable .skill file.
Review SKILL.md files and their supporting resources using eight quality dimensions. Get a score out of 120, evidence for each assessment, and prioritized suggestions to improve specialized knowledge, activation descriptions, organization, and practical instructions.
Give slides, documents, reports, and HTML landing pages consistent colors and fonts. Choose from ten preset themes using a visual showcase, or create a custom theme from a description and review it before application.
Try a simple skill invocation with `/example`, which returns a friendly greeting and explains that the demo was loaded from the workspace skills directory. The sample also shows the basic file structure for creating your own skills.
Coach workers, employees, and individual contributors to turn meetings, transcripts, minutes, and work notes into better execution: infer leader expectations, diagnose previous work, identify next actions, judge delivery readiness, and prepare a high-bandwidth update. Use after meetings, during work, before reviews, or across repeated low-value discussions. Perform semantic review from source evidence.
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Evaluate Agent Skill design quality with an opinionated, practice-derived rubric informed by public specifications and examples. Use when reviewing, auditing, comparing, or improving SKILL.md files and skill packages. Produces evidence-backed findings, optional multi-dimensional scoring, and prioritized changes; treat the result as diagnostic guidance, not official certification or a universal standard.
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Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about AI coding agents, agent runtimes, or similar internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
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Recover and review local human-AI conversations from Claude Code, Codex, opencode, Grok Build, and Cursor. Use when the user wants to revisit, search, extract, summarize, or compare work across Agent session stores, time ranges, projects, or named conversations. Follow the user's requested output; question clustering, problem-space mapping, artifact review, drift analysis, and insights are optional lenses.
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Deeply research technical architecture, source code, mechanisms, SDKs, frameworks, project comparisons, and system-design options across repositories, history, official docs, issues, discussions, and high-quality community signals. Use when the user asks for deep research, source-level understanding, architecture comparison, mechanism satisfaction, or evidence for designing a system. Always map the question and obtain confirmation before beginning substantive research; skip for simple factual lookups or straightforward implementation tasks.
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Create platform-native content that resonates with each community's culture. Use when adapting technical content for WeChat, Hacker News, Reddit, Medium, Twitter/X, Dev.to, or LinkedIn. Transforms generic writing into content that feels written BY that community, not AT them.
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