1万 件 ・ 関連度順
概要と使いどころ
Bridges Claude Code and Codex sessions when native tools can't reach the target. Use for 跨产品通信 / 脚本回帖 / 送达排查: cross-product messages, hooks or scripts posting to a session, verifying delivery (Held messages included), shared-work ownership, or an inbound peer assertion. Not for same-product or parent/subagent messaging (use native tools), spawning agents, moving full history, or cross-machine pairing (deprecated).
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。
Stress-test a decision or claim through a sharp, fair Q&A — the questions a good lawyer or skeptical friend would ask before you commit. Use when asked to cross-examine me, ask me hard questions about this, interrogate my plan, or make me defend this. Produces a sequenced line of probing questions (from clarifying to challenging to the killer question), space to answer, and a debrief on where your answers were strong, evasive, or exposed a gap — so weaknesses surface in private before they surface in public.
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。
Write a cold sales/B2B outreach email that earns a reply. Use when asked to write a cold email, a sales outreach email, a prospecting email, or a cold email sequence to a business prospect. Produces a short, personalised email — subject, a relevant opener, one clear value-led ask, and a low-friction CTA — plus 2 follow-ups, written to be replied to, not deleted.
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。
Start a cross-team project with the collaboration contract that prevents the classic collisions — who decides what, how work flows between teams, the communication channels and cadence, and what done means — agreed before the first collision instead of during it. Use when asked kick off this cross-team project right, our two teams keep colliding, define how we'll work with the other team, or set up the partnership before we start. Produces the one-page contract: decision rights, interfaces, cadence, and the done-definition.
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。
Allocate a finite budget or headcount across competing initiatives by return and strategic fit. Use when asked to allocate budget, decide where to invest, build a funding/portfolio plan, or make trade-offs across initiatives under a cap. Produces a capital-allocation plan — initiatives scored by expected return × strategic fit per dollar, a funded/unfunded split against the cap, the cut line, and the reasoning.
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 Newark, Farnell, and element14 for electronic components — find parts by MPN or distributor part number, check pricing/stock, download datasheets, analyze specifications. One unified API covers all three storefronts (Newark for US, Farnell for UK/EU, element14 for APAC). Free API key, simple query-parameter auth, no OAuth. Datasheets download directly from farnell.com CDN with no bot protection. Sync and maintain a local datasheets directory for a KiCad project, or use batch MPN-list seeding (`--mpn-list`) for bulk workflows without a project. Use this skill when the user mentions Newark, Farnell, element14, needs parts from a non-US distributor, wants to compare pricing across regions, or needs datasheets from a source that doesn't require complex API auth. For package cross-reference tables and BOM workflow, see the `bom` 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。
Search Mouser Electronics for electronic components — secondary source for prototype orders. Find parts, check pricing/stock, download datasheets, analyze specifications. Use with KiCad for BOM creation and part selection. Also supports batch MPN-list seeding (`--mpn-list`) for bulk datasheet workflows without a KiCad project. Use this skill when the user specifically mentions Mouser, when DigiKey is out of stock or has worse pricing, when comparing prices across distributors, or when searching for parts that DigiKey doesn't carry. For package cross-reference tables and BOM workflow, see the `bom` 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。
**WORKFLOW SKILL** - Evaluate AI agent skills using structured benchmarks with YAML specs, fixture isolation, and pluggable validators. USE FOR: run waza, waza help, run eval, run benchmark, evaluate skill, test agent, generate eval suite, init eval, compare results, score agent, agent evaluation, skill testing, cross-model comparison. DO NOT USE FOR: improving skill frontmatter (use waza dev), creating new skills from scratch (use skill-creator), token counting or budget checks (use waza tokens). INVOKES: Copilot SDK executor, mock engine, code/regex validators. FOR SINGLE OPERATIONS: use waza run directly for a single benchmark.
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。
Standard collaboration patterns for all squad agents — worktree awareness, decisions, cross-agent communication
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 to build academic-style .docx output: journal / conference / thesis chapters carrying formal citation style (APA, Chicago, IEEE, MLA), numbered equations, figure & table cross-references, footnotes/endnotes, bibliography, or multi-column journal layout. Trigger on: 'research paper', 'journal paper', 'conference paper', 'manuscript', 'thesis', 'APA', 'MLA', 'Chicago', 'IEEE two-column', 'bibliography', 'hanging indent', 'citation style', 'abstract + keywords', 'equation numbering', 'cross-reference', paper with footnotes/endnotes. Output is a single .docx.
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。
Detect Cross-Site Scripting (XSS) vulnerabilities in a codebase using a three-phase approach: recon (find HTML/JS/DOM sink sites), batched verify (trace user input to sinks in parallel subagents, 3 sink sites each), and merge (consolidate batch results). Requires sast/architecture.md (run sast-analysis first). Outputs findings to sast/xss-results.md. Use when asked to find XSS or cross-site scripting bugs.
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。
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
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。
跨模型第二意见技能，融合 gstack 的 cross-model second opinion 能力。 当检测到高风险改动时，可选触发不同模型提供独立审查意见， 作为 multi-perspective-review 的可选叠加层。
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。
Maps intelligence for local SEO — geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification (Google/Bing/Apple/OSM), competitor radius mapping, and LocalBusiness schema generation from API data. Three-tier capability: free (Overpass + Geoapify), DataForSEO (full intelligence), DataForSEO + Google (maximum coverage). Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", "maps analysis", "local rank tracking", "Share of Local Voice", or "SoLV".
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。
Maps intelligence for local SEO: geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification, competitor radius mapping, and LocalBusiness schema generation. Three tiers: free (Overpass + Geoapify), DataForSEO, and DataForSEO + Google. Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", or "SoLV".
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。
Audit whether prior learnings actually fired, then install mechanisms for this run's recurrences. No finding without an install path and a firing test. Triggers: retrospective, reflect, what did we learn, patterns, post-mortem, why does this keep happening.
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。
Safely validate, publish, and track a local SKILL.md directory across GitHub, Awesome Codex Plugins, HOL Registry, skills.sh, SkillsMP, LobeHub, ClawHub, and Cursor Directory. Use when the user asks to publish, update, register, or synchronize an agent skill across marketplaces.
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 Mouser Electronics for electronic components — secondary source for prototype orders. Find parts, check pricing/stock, download datasheets, analyze specifications. Use with KiCad for BOM creation and part selection. Also supports batch MPN-list seeding (`--mpn-list`) for bulk datasheet workflows without a KiCad project. Use this skill when the user specifically mentions Mouser, when DigiKey is out of stock or has worse pricing, when comparing prices across distributors, or when searching for parts that DigiKey doesn't carry. For package cross-reference tables and BOM workflow, see the `bom` 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。
Search Newark, Farnell, and element14 for electronic components — find parts by MPN or distributor part number, check pricing/stock, download datasheets, analyze specifications. One unified API covers all three storefronts (Newark for US, Farnell for UK/EU, element14 for APAC). Free API key, simple query-parameter auth, no OAuth. Datasheets download directly from farnell.com CDN with no bot protection. Sync and maintain a local datasheets directory for a KiCad project, or use batch MPN-list seeding (`--mpn-list`) for bulk workflows without a project. Use this skill when the user mentions Newark, Farnell, element14, needs parts from a non-US distributor, wants to compare pricing across regions, or needs datasheets from a source that doesn't require complex API auth. For package cross-reference tables and BOM workflow, see the `bom` 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。
Use when drafting or polishing an American Anthropologist (AA) manuscript so it reads across all four fields, follows AA house style (Chicago author-date; free-format submission accepted), fits the section word caps (Research Articles ≤ 8,000 words; abstract 200 words), and uses inclusive, care-ful language. Tightens prose and format; it does not invent content.
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 when polishing the prose of an Advanced Materials manuscript for Wiley house style, concision, precise materials nomenclature and units, and readability across materials subfields. Polishes language; does not restructure the advance or manage the length budget.
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 when polishing the prose of an Accounting, Organizations and Society (AOS) manuscript — sustained argumentative writing that carries theory and evidence together, a self-contained abstract, disciplined length despite the absence of a hard cap, and full anonymization for double-anonymized review. Polishes prose; it does not run the submission preflight (aos-submission).
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 when positioning an AAMAS submission against multiagent, game-theory, and reinforcement-learning literature spread across AAMAS, AAAI, IJCAI, NeurIPS, ICML, EC, and JAAMAS, including arXiv and workshop versions, concurrent submissions, prior conference versions, and the cross-community citation coverage AAMAS reviewers expect.
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 personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.
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。