Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
This skill fetches open tasks assigned to the user from the Linear API and generates a markdown todo list file in the project root. This skill should be used when the user asks about their work items, wants to see what they need to work on, or requests to load/sync their Linear tasks. Requires Python 3.7+, requests, mdutils, and python-dotenv packages. Requires LINEAR_API_KEY in .env file.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Automatically fetch assigned Linear tasks and generate a comprehensive markdown todo list in your project root. This skill queries the Linear GraphQL API to retrieve all open tasks assigned to you, organizing them by project with full details including status, priority, labels, estimates, and due dates.
Install the Python dependencies:
pip install requests mdutils python-dotenv
Or using conda:
conda install requests python-dotenv
pip install mdutils
Create a .env file in your project root:
cp .claude/skills/linear-todo-sync/assets/.env.example .env
Edit .env and add your API key:
LINEAR_API_KEY=lin_api_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
Important: Ensure .env is in your .gitignore to protect your API key.
Test the configuration by running:
python .claude/skills/linear-todo-sync/scripts/sync_linear_tasks.py
A markdown file named linear-todos-YYYY-MM-DD.md should appear in your project root.
When triggered, this skill:
.env file in your project rootlinear-todos-YYYY-MM-DD.md in the project rootThe generated markdown file provides a comprehensive view of your work with all relevant task metadata, making it easy to review priorities and plan your day.
Trigger this skill with phrases like:
The skill will execute the sync script and create a dated markdown file in your project root.
The markdown file follows this structure:
# Linear Tasks - January 18, 2025
Generated: 2025-01-18 09:30:45
Total Tasks: 12
## Project Alpha
### Implement user authentication (High)
- **Status**: In Progress
- **Labels**: backend, security
- **Estimate**: 5 points
- **Due**: 2025-01-20
- **Link**: https://linear.app/team/issue/PROJ-123
Add JWT-based authentication to the API endpoints...
### Fix login bug (Urgent)
- **Status**: Todo
- **Labels**: bug, frontend
- **Estimate**: 2 points
- **Due**: 2025-01-19
- **Link**: https://linear.app/team/issue/PROJ-124
Users cannot log in when using Safari...
## Project Beta
...
To modify the skill's behavior, edit scripts/sync_linear_tasks.py:
Modify the QUERY variable to fetch additional fields:
QUERY = """
query {
viewer {
assignedIssues(filter: { state: { type: { nin: ["completed", "canceled"] } } }) {
nodes {
id
title
description
state { name }
priority
labels { nodes { name } }
estimate
dueDate
project { name }
url
# Add more fields here
createdAt
updatedAt
assignee { name }
}
}
}
}
"""
Modify the filter in the GraphQL query to change which tasks are fetched:
# Include completed tasks from the last week
filter: {
state: { type: { nin: ["canceled"] } }
completedAt: { gte: "2025-01-11" }
}
Customize the markdown generation in the generate_markdown() function to change structure, add sections, or include different metadata.
Update the output_path variable in main():
# Save to a different directory
output_path = os.path.join(project_root, "docs", filename)
Cause: The .env file is missing or doesn't contain the API key.
Solution:
.env exists in your project root (not in the skill directory)LINEAR_API_KEY=lin_api_...= signCause: The API key is incorrect or expired.
Solution:
.env with the correct keyCause: Cannot connect to Linear API (network issue, timeout, or API downtime).
Solution:
Cause: Too many API requests in a short period.
Solution:
Cause: You have no assigned tasks in non-completed states.
Solution: This is informational only. The skill will still create a markdown file indicating zero tasks.
Cause: Insufficient file system permissions.
Solution:
Cause: File created in unexpected location or script error.
Solution:
python scripts/sync_linear_tasks.py --verbose.env file: Always add .env to .gitignorepip install --upgrade requests mdutils python-dotenvAdd to your shell profile (.bashrc, .zshrc) to sync on terminal startup:
# Auto-sync Linear tasks daily
if [ -f "/path/to/project/.env" ]; then
python /path/to/project/.claude/skills/linear-todo-sync/scripts/sync_linear_tasks.py
fi
Create a post-checkout hook to sync after changing branches:
#!/bin/bash
# .git/hooks/post-checkout
python .claude/skills/linear-todo-sync/scripts/sync_linear_tasks.py
Use in continuous integration to track team tasks:
# .github/workflows/sync-tasks.yml
- name: Sync Linear Tasks
run: |
pip install requests mdutils python-dotenv
python .claude/skills/linear-todo-sync/scripts/sync_linear_tasks.py
env:
LINEAR_API_KEY: ${{ secrets.LINEAR_API_KEY }}
For detailed API reference and advanced GraphQL queries, see the Linear API documentation.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Testing patterns for PHPUnit and Playwright E2E tests. Use when writing tests, debugging test failures, setting up test coverage, or implementing test patterns for ActivityPub features.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.
日本語の概要は準備中です。原文の説明を表示しています。
Add unsigned integer (uint) type support to PyTorch operators by updating AT_DISPATCH macros. Use when adding support for uint16, uint32, uint64 types to operators, kernels, or when user mentions enabling unsigned types, barebones unsigned types, or uint support.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
日本語の概要は準備中です。原文の説明を表示しています。
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
日本語の概要は準備中です。原文の説明を表示しています。
Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
日本語の概要は準備中です。原文の説明を表示しています。