GitHub
arcgis-feature-effects
Apply visual effects to features including filters, drop shadows, blur, and grayscale. Use for highlighting features and creating visual emphasis.
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Documentation AI Skills
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GitHub
arcgis-coordinates-projection
Work with coordinate systems, projections, and coordinate conversion. Use for transforming coordinates and displaying position in multiple formats.
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GitHub
arcgis-imagery
Work with raster and imagery data including ImageryLayer, ImageryTileLayer, multidimensional data, pixel filtering, and raster analysis. Use for satellite imagery, elevation data, and scientific raster datasets...
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GitHub
arcgis-3d-advanced
Advanced 3D features including VoxelLayer, PointCloudLayer, weather effects, daylight simulation, glTF model imports, and custom WebGL rendering. Use for volumetric data, LiDAR visualization, and immersive 3D e...
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GitHub
arcgis-utility-networks
Work with ArcGIS Utility Networks for modeling and analyzing connected infrastructure. Use for network tracing, associations, and utility asset management.
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GitHub
example-skill
Use when working with examples, tutorials, or skill documentation. Invoke when the user asks about skill configuration, manifest structure, or creating new skills.
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GitHub
ntfy-notify
Send push notifications via ntfy.sh. Use this skill when the user asks to be notified, wants an alert, or when a long-running task completes and the user should be informed.
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GitHub
wyckoff-analyst
执行威科夫市场结构分析并生成交互式图表。触发场景：(1)分析股票吸筹/派发形态 (2)识别威科夫阶段(Phase A-E) (3)标注SC/AR/Spring/SOS等事件 (4)用户提到"威科夫分析"或"Wyckoff"
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GitHub
stock-data-fetcher
获取A股数据(baostock)并缓存到本地CSV文件，避免MCP返回大量数据占用上下文。触发场景：(1)获取超过100条的K线数据 (2)需要多次查询同一股票数据 (3)需要用grep/awk分析数据 (4)用户提到"保存数据"或"缓存数据"
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GitHub
pr-writing
Best practices for writing clear, effective pull request descriptions. Use when creating PRs to ensure they communicate changes effectively to reviewers.
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GitHub
work-issue
Core implementation logic for working on a single GitHub issue. Used by both /work command and /work-all subagents to ensure consistent behavior.
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GitHub
javascript-standards
JavaScript and TypeScript coding standards, conventions, and best practices. Use when writing, reviewing, or testing JS/TS code.
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GitHub
workflow-orchestration
Defines the autonomous development workflow. Use when orchestrating work between agents, managing issue lifecycles, or understanding the development loop.
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GitHub
css-standards
CSS, SCSS, and styling conventions. Use when writing, reviewing, or debugging styles and layouts.
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GitHub
user-stories
Guidelines for writing effective user stories with clear acceptance criteria. Use when creating issues from discovery findings.
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GitHub
project-commands
Manages project-specific commands for development, testing, and deployment. Use when needing to run project commands or when setting up commands for a new project.
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GitHub
notifications
System for alerting the user when attention is needed. Use when you need to get the user's attention for questions, approvals, or when stuck.
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GitHub
github-workflow
Manages GitHub workflow including issues, PRs, labels, and reviews. Use when working with GitHub issues, creating PRs, or coordinating reviews.
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GitHub
github-issues
Best practices for breaking down work into GitHub issues, proper sizing, and milestone organization. Use during discovery/planning phases.
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GitHub
infrastructure-standards
Infrastructure, cloud, and DevOps standards. Use when setting up new projects, configuring cloud resources, or working with IaC.
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GitHub
agent-coordination
Patterns for invoking and coordinating Automatasaurus agents. Use when delegating tasks to specialist agents.
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GitHub
requirements-gathering
Discovery questions, checklists, and techniques for gathering requirements. Use during discovery to ensure thorough understanding before creating issues.
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GitHub
code-review
Best practices for performing thorough, constructive code reviews. Use when reviewing PRs to ensure quality feedback that improves code and helps developers grow.
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GitHub
python-standards
Python coding standards, conventions, and best practices. Use when writing, reviewing, or testing Python code.
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