GitHub
write-comments
Writes explanatory comments to code to improve readability for developers and AI systems. Use when documenting code or improving code comprehension.
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GitHub
magnus-the-world-builder
World-building companion for the Aphebis platform that helps users explore, discuss, and extend fictional worlds. Use when users want to browse existing worlds/areas/locations, brainstorm world expansion ideas,...
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GitHub
pso
Project Support Officer - Interface to the organization's project management system. Manages project list (project-list.csv), activity logs (project-activity-logs.csv), and project artifacts in org/projects/. U...
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GitHub
business-context
Access shared business context including company identity, mission, org chart, staff directory, and policies. Use this when an agent needs to understand the business they work for, organizational structure, who...
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GitHub
bandit-security-scan
Run Bandit security analysis to find common security issues and vulnerabilities in Python code. Use when the user mentions Bandit, security analysis, vulnerability scanning, security audit, software composition...
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GitHub
sonarqube-scan
Run SonarQube/SonarCloud static code analysis to check code quality, detect security vulnerabilities, code smells, and bugs. Use when the user mentions SonarQube, code quality analysis, security scanning, stati...
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GitHub
authoring-skills
MUST BE USED when creating, improving, or reviewing Skills. Use PROACTIVELY when user mentions "create a skill", "new skill", "write a skill", "improve skill", "skill description", or "progressive disclosure"....
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GitHub
cursor-explorer-mcp
Use for token-expensive operations requiring multi-file analysis - codebase exploration, broad searches, architecture understanding, tracing flows, finding implementations across files. Uses MCP cursor-agent se...
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GitHub
checking-dependabot-prs
DependabotのPRをレビューの必要度の観点で検証する。「DependabotのPRを確認して」「Dependabotの更新は安全？」などの依頼時に使用する。
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GitHub
code-explainer
Explains code in simple terms with visual diagrams. Use when the user asks to explain code, understand how something works, or wants a code walkthrough.
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GitHub
test-runner
Runs tests and explains results. Use when user asks to run tests, check tests, or verify code works.
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GitHub
telegram
This skill should be used when fetching, searching, downloading, or sending messages on Telegram. Use for queries like "show my Telegram messages", "search Telegram for...", "get unread messages", "send a messa...
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GitHub
unity-bootstrap
Bootstrap a new Unity project for a 2D management/simulation game. Use when you need to create the Unity project, choose URP/UI approach, set up folder structure, gitignore, packages (Input System/TextMeshPro),...
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GitHub
unity-migration
Migrate a browser-based JavaScript/Canvas game to Unity (C#). Use for Shelter 2250 (or similar) when you need: (1) Unity project setup decisions (2D/URP/input/UI), (2) mapping existing JS classes/systems to Uni...
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GitHub
beads-task-show
Show details for a Beads task by id (including audit trail)
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GitHub
beads-session-sync
Flush and sync Beads changes to git (export/commit/pull/import/push)
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GitHub
beads-task-create
Create a new Beads task (issue) with priority and (optional) type
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GitHub
beads-task-dep-add
Add a dependency relationship between Beads tasks
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GitHub
task-spec
Create or update a task specification
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GitHub
beads-pr-prepare
Prepare a pull request title/body from a Beads task (optionally using gh)
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GitHub
beads-task-ready
List Beads tasks that are ready to start (no open blockers)
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GitHub
project-architecture-patterns
Architecture patterns for rRNA-Phylo project including FastAPI backend design, service organization, async task processing with Celery, Pydantic schemas, testing with pytest, Biopython integration, and API desi...
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GitHub
ml-tree-level4
Advanced Maximum Likelihood phylogenetics with model selection (AIC/BIC), tree search algorithms (NNI/SPR/TBR), and performance optimization (Numba/GPU)
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GitHub
ml-integration-patterns
Machine learning integration patterns for rRNA-Phylo covering three use cases - rRNA sequence classification (supervised learning with sklearn/PyTorch), multi-tree consensus (ensemble methods), and generative t...
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