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。
Fetch unresolved PR review comments using GitHub GraphQL API, filtering out resolved and outdated feedback.
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。
Uses GitHub's GraphQL API to fetch only unresolved review thread comments from a pull request.
Parse PR information:
PR_NUMBER and GITHUB_REPOSITORY are set, read them and parse GITHUB_REPOSITORY as owner/repo and use PR_NUMBER directlygh pr view --json url -q '.url' to get the current branch's PR URL and parse to extract owner, repo, and PR numberRun the Python script:
GITHUB_TOKEN=$(gh auth token) \
uv run python .claude/skills/fetch-unresolved-comments/fetch_unresolved_comments.py <owner> <repo> <pr_number>
Script options:
--token <token>: Provide token explicitly (default: GITHUB_TOKEN or GH_TOKEN env var)Parse the JSON output: The script always outputs JSON with:
total: Total number of unresolved comments across all threadsby_file: Review threads grouped by file path (each thread contains multiple comments in a conversation){
"total": 3,
"by_file": {
".github/workflows/resolve.yml": [
{
"thread_id": "PRRT_kwDOAL...",
"isOutdated": false,
"line": 40,
"startLine": null,
"diffHunk": "@@ -0,0 +1,245 @@\n+name: resolve...",
"comments": [
{
"id": 2437935275,
"body": "We can remove this once we get the key.",
"author": "harupy",
"createdAt": "2025-10-17T00:53:20Z"
},
{
"id": 2437935276,
"body": "Good catch, I'll update it.",
"author": "contributor",
"createdAt": "2025-10-17T01:10:15Z"
}
]
}
],
".gitignore": [
{
"thread_id": "PRRT_kwDOAL...",
"isOutdated": false,
"line": 133,
"startLine": null,
"diffHunk": "@@ -130,0 +133,2 @@\n+.claude/*",
"comments": [
{
"id": 2437935280,
"body": "Should we add this to .gitignore?",
"author": "reviewer",
"createdAt": "2025-10-17T01:15:42Z"
}
]
}
]
}
}
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。