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概要と使いどころ
Diagnose active BIRD daemon incidents across config, runtime, environment, sockets, logs, source, and tooling. Use when BIRD fails to start or reload, crashes, loses sessions/routes, behaves differently after lint passes, or when birdcc and bird -p disagree. Collect read-only evidence first, protect routing secrets, and route isolated config edits to bird-agent or pure implementation research to bird-source-explorer.
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Write, review, discover, lint, format, and validate BIRD 2/3 routing-daemon projects with the @birdcc toolchain. Use for bird.conf, bird2.conf, bird3.conf, bird6.conf, .bird/.bird2/.bird3 files, bird.config.json, birdcc.config.json, include graphs, BIRD filters and protocols, birdcc init/lint/fmt/lsp, or bird -p checks. Treat BIRD 1 as legacy and verify it with the actual BIRD 1 binary. Route editor and CLI installation to birdcc-installer, GitHub Actions to birdcc-cicd, runtime incidents to bird-troubleshooting, and implementation archaeology to bird-source-explorer.
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。
Install or migrate BIRD 2/3 editor support and @birdcc/cli. Use for the BIRD2 LSP VS Code extension, the separate TextMate syntax extension or extension pack, VS Code forks, BIRD.nvim, BIRD.vim, manual Neovim LSP wiring, JetBrains TextMate bundles, birdcc CLI installation, offline VSIX setup, or migrations from BIRD2.nvim/BIRD2.vim. Route config diagnostics to bird-agent and GitHub Actions to birdcc-cicd.
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。
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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。
Trace BIRD routing-daemon behavior through the actual C source tree. Use for implementation questions, suspected upstream bugs, parser/keyword origins, filter instructions, protocol state machines, route attributes, birdc commands, stack traces, or BIRD 2 versus BIRD 3 source comparisons. Prefer a local checkout or exact upstream tag/commit and cite concrete files, functions, and revisions. Route config linting to bird-agent and active incidents to bird-troubleshooting.
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。
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatt...
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。
B @ 3/4 bits models [2024-10-18] Open source community contributes Mistral Large Instruct 2407 (12
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。
Build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port code onto ZeroGPU, fix a Space that won't build or run, or otherwise work with `hf spaces …`, `@spaces.GPU`, Space README frontmatter, or the `spaces` Python package.
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。
Expert en developer advocacy (communauté, contenu, docs, demos, feedback loop, métriques)
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。
Expert en écosystème d'agents IA (plugins, extensions, thèmes, communauté, contributions, gouvernance)
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。
Search and analyze Reddit discussions for market research, product feedback, and community insights using Xpoz. Use when asked to "search Reddit", "what does Reddit think about X", "Reddit feedback on X", "subreddit analysis", or "Reddit market research".
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。
Use this skill whenever the user asks to inspect JoCoHunt, 조코헌트, jocohunt.jocoding.io products, ideas, rankings, makers, public security headers, or wants a CLI workflow for the Korean builder community. It runs the local `jocohunt` Go CLI, including authenticated product submission when explicitly requested.
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。
Discuss a community-edition product requirement with the user, draft a bilingual (Chinese + English) PRD for review, then — after explicit user approval — create the English-only issue on GitHub (<OWNER/REPO>). Use whenever the user wants to turn a requirement (from a Feishu doc, a meeting note, a customer ask, or a rough idea) into a GitHub issue. Triggers on phrases like "create requirement doc", "create a requirement", "put this requirement on GitHub", "create new feature issue", "draft an issue for...", or anytime the user describes a product feature/improvement they want tracked. The format is opinionated (Background / Goal / Spec / Verification / Related, NO implementation details, draft shown bilingually for human review, issue itself written in English only).
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。
Shared foundation for all human-voice writing skills. Load before any profession-specific skill. Contains: burstiness principle, perplexity principle, soul injection techniques, community-discovered AI patterns with sources, additional core patterns, banned AI vocabulary, and scoring rubric.
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。
To access Anthropic's official brand identity and style resources, use this skill.
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。
Kelly's market-intelligence desk (Busabase App-in-Skill). Merges passive competitor monitoring (Radar), agent-run deep research with approved briefs and cited reports (Research), and keyword/topic demand signals (Trends) over one Busabase-backed snapshot, watchlist, and review model. Use when the user invokes $kelly-radar or /kelly-radar, or asks for competitor monitoring, market intelligence, market research, research reports, trends, rising keywords, pricing changes, product launches, changelog diffs, competitor reviews, funding or hiring news, or opportunity triage.
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。
Digital-human implementation and demo skill for choosing, prototyping, and QA-ing low-cost 2D photoreal digital humans and high-control 3D custom digital humans. Use when the user wants a digital-human avatar, AI host, customer-service presenter, multimodal voice-to-lip-sync video stream, vendor comparison for services such as Silicon Intelligence / Tencent Zhiying / ZEGO-like real-time providers, or a UE/Unity 3D digital-human architecture and launch-ready demo.
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。
Finish an existing Japanese creator, challenge, comeback, vlog, or community-building vertical social rough cut as an evidence-grounded short-form story. Use for strong opening declarations, identity and struggle arcs, crisis-to-goal recovery, multi-source B-roll and evidence stills, emotional typography, semantic punch-ins, pinned SFX, dialogue-first audio, platform-added music delivery, and creator-short retention QA.
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。
Installs, configures, and tunes Snort 3 intrusion detection system to monitor network traffic for malicious activity using custom and community rulesets, preprocessors, and alert output plugins on authorized network segments.
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Conduct internal Active Directory reconnaissance using BloodHound Community Edition to map attack paths, identify privilege escalation chains, and discover misconfigurations in domain environments.
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。
Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Use when creating portable detection logic from threat intelligence, mapping rules to MITRE ATT&CK techniques, or converting community Sigma rules into platform-specific queries using sigmac or pySigma backends.
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。
Authors reproducible Nextflow DSL2 pipelines built on reactive dataflow, where processes communicate only through channels and execution order is not guaranteed. Use when deciding channel/dataflow (Nextflow) vs rule-based (Snakemake) authoring; wiring queue vs value channels and fixing shared-reference exhaustion with .first(); composing DSL2 modules and subworkflows with take/main/emit; selecting container/conda profiles and pinning images by digest for portability across local/SLURM/LSF/AWS Batch/Google Batch/Kubernetes executors; diagnosing why -resume misses the cache (nondeterministic input order, mtime on network filesystems, mutable :latest tags) with cache 'lenient' and -dump-hashes; managing work/ vs publishDir and dynamic retry escalation; and choosing whether to adopt an nf-core community pipeline or author from scratch.
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。
Review Stellar Community Fund (SCF) Build Award applications. Use when evaluating SCF submissions, covering project fit assessment, technical architecture evaluation, team readiness, traction validation, budget analysis, and funding recommendations.
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。
Draft Stellar Community Fund Build Award applications interactively. Use when helping teams write their SCF submission — walks through project description, Stellar integration rationale, technical architecture, team section, deliverables, budget, and traction evidence. Produces a complete draft aligned with what funded projects look like.
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。