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概要と使いどころ
Use when analyzing pcap or pcapng files, triaging network captures, labeling IPs with evidence, generating PNG charts, or writing packet analysis reports. Keywords: pcap, pcapng, tshark, Wireshark, scapy, DNS, TLS SNI, RDAP, graph, matplotlib, gnuplot, packet capture.
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。
"Optimize multilingual product listings for international e-commerce including SEO localization, machine translation workflows, and cultural adaptation. Use this skill when the user needs to create product listings in multiple languages, optimize for local search, or adapt marketing content for different markets — even if they say 'translate our listings', 'optimize for local SEO', 'adapt for the Japanese market', or 'our translated listings don't convert'.".
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。
Audio Unit v2 adapter work for Pulp — picking the right AU component type (aufx/aumf/aumi/aumu) and its matching entry macro, wiring MIDI input and output (including the aumi MIDI-processor adapter), sharing the base-class-free adapter surface, and avoiding the DAW-side component cache that silently masks repackaging.
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。
Full-funnel paid advertising operations for B2B SaaS. Use this skill for PPC strategy, Google Ads optimization, LinkedIn Ads, social media advertising, programmatic buying, creative strategy, attribution modeling, budget allocation, budget pacing and planned-vs-delivered reconciliation, audience overlap and campaign self-competition audits, suppression lists, ROAS improvement, media spend optimization, and the media no auction sells — newsletter and podcast sponsorships, community and industry-publication placements, paid review-site listings on G2 and Capterra, and pay-per-lead content syndication. It also covers buying on the AI answer surface — ads inside Google AI Overviews and AI Mode that existing Search, Shopping and Performance Max campaigns already serve into with no opt-out, no placement targeting and no segmented reporting, and ChatGPT Ads and Microsoft Copilot as separate opt-in platforms with their own plan-tier reach limits, no negative keywords, and a landing-page crawler gate. It also owns the conversion signal the bidding algorithms learn from — CRM pipeline stages (SQL, opportunity, closed-won) sent back to Google Ads, LinkedIn, Meta and Microsoft Ads through offline conversion import, enhanced conversions for leads, the Google Data Manager API and the LinkedIn Conversions API, with click-ID capture, stage values, dedupe, EEA consent signals and retractions. It also gates connected TV (CTV) and streaming video for B2B — whether a reach medium belongs in the plan, how a vendor ties a TV household to a target account (member data, IP-to-account graph or contextual), the server-side ad insertion (SSAI) fraud questions, Programmatic Guaranteed deals, and a holdout lift test because CTV has no click. It also runs person-led paid social — LinkedIn Thought Leader Ads and Meta partnership ads that put spend behind an employee's or creator's post — on a paid-usage term, an in-post disclosure check and an end-date register, because the platform approval carries no term. Also triggers on: CTV, connected TV, OTT, streaming TV ads, should we run CTV, LinkedIn CTV, B2B CTV, account-based CTV, SSAI fraud, thought leader ads, boost an employee's post, sponsor a creator's post, partnership ads, whitelisting, creator usage rights, PPC, Google Ads, LinkedIn Ads, social ads, programmatic, ad creative, attribution, media budget, paid campaigns, ROAS, CPA, ad spend, newsletter sponsorship, podcast sponsorship, community sponsorship, sponsor a newsletter, content syndication, pay-per-lead, cost per lead vendor, media kit, rate card, insertion order, direct buy, publisher partnership, make-good, G2 paid listing, Capterra ads, review site advertising, sponsorship ROI, budget pacing, we underspent our budget, are our campaigns competing with each other, audience overlap, self-competition, campaign cannibalization, suppression list, exclusion list, ad frequency across channels, how many ad accounts do we have, ads in AI Overviews, AI Mode ads, ChatGPT Ads, OpenAI Ads Manager, Copilot ads, conversational ads, should we advertise on ChatGPT, can we buy our way into the AI answer, our ads are showing in AI Overviews and we cannot report on it, context hints, OAI-AdsBot, our ad landing page fails review, robots.txt is blocking our ads, our paid leads are junk, Google Ads is optimizing for the wrong leads, offline conversion import, OCI, enhanced conversions for leads, send CRM stages back to Google Ads, upload SQLs to LinkedIn, LinkedIn Conversions API, LinkedIn CAPI, Meta conversion leads, CRM to ad platform, gclid, li_fat_id, msclkid, value-based bidding, optimize for pipeline not form fills, low match rate, conversion lag.
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。
Short alias for universal-web-adaptation. Use this when adapting an unfamiliar public website generically before creating any site-specific rules.
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 audit CLI adapter projects (like opencli) for missing output fields, then batch-generate fixes and submit PRs. Turns AI agents into adapter quality reviewers.
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。
Adapt and convert AI prompts between different models and platforms. Translates between Midjourney, Flux, Leonardo AI, DALL-E, Sora, Imagen, Stable Diffusion, Adobe Firefly, Ideogram, and more. Handles syntax differences, parameter mapping, and model-specific optimizations. Use when user says "adapt prompt", "convert prompt", "translate prompt", "port to flux", "midjourney to dall-e", or "change model".
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 when configuring Salesforce B2B or D2C Commerce checkout: payment methods, shipping/tax integration, guest checkout, order summary setup, and CartCheckoutSession state orchestration. Trigger keywords: checkout flow, payment adapter, shipping tax integration, guest checkout, order summary, CartCheckoutSession, Managed Checkout, Commerce checkout flow. NOT for deciding the checkout design before build (LWR vs Aura) — use admin/commerce-checkout-flow-design. NOT for writing the CommercePayments adapter class — use apex/commerce-payment-integration.
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。
Task and Event objects: polymorphic WhatId/WhoId, Activity object model, ActivityHistory vs OpenActivity, activity timeline customization, bulk task creation, Einstein Activity Capture boundaries. NOT for turning on EAC or calendar sync — use admin/einstein-activity-capture-setup. NOT for Email-to-Case — use admin/case-management-setup. Covers ActivitiesSettings metadata, enableActivities, shared Task/Event custom fields and FLS, TaskStatus value sets, Shared Activities and TaskRelation/EventRelation, recurring and child activities, and partial-success bulk DML on Task.
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。
Run a self-retrospective on a SKMTC-related session — generator authoring, CLI configuration, debugging, or any sustained interaction involving `@skmtc/core`, `@skmtc/cli`, or `@skmtc/gen-*` packages. Captures three distinct outputs: (1) friction entries (mistakes, surprises, overridden defaults, multi-cycle struggles), (2) a "knowledge acquired" block recording facts the agent learned during the session that weren't in its training — the primary signal for doc gaps — and (3) a closing priority list ranking the top 2-3 findings for docs/skills triage. Wins are logged only when they identify a pattern worth codifying that isn't already in a skill. Use this skill when the user asks to "retro", "skmtc retro", "log friction", "reflect on this session", "what did we learn", "run a retrospective", or after substantive SKMTC work (generator authoring, multi-step debugging, non-trivial CLI configuration) where capturing observations would help improve skills, docs, or SKMTC itself. Distinct from the `skmtc-cli` and `skmtc-generator` skills — those guide *doing* the work; this skill captures observations *about* the work. Do not invoke this skill during ordinary work; it is end-of- session (or mid-session-checkpoint) 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。
Design and implement adaptive testing systems using Item Response Theory (IRT). Use when working with computerized adaptive tests (CAT), psychometric assessment, ability estimation, question calibration, test design, or IRT models (1PL/2PL/3PL). Covers test algorithms, stopping rules, item selection strategies, and practical implementation patterns for K-12, certification, placement, and diagnostic assessments.
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。
A continuously adaptive skill suite that empowers Clawdbot to act as a versatile coder, business analyst, project manager, web developer, data analyst, and NAS metadata scraper. It intelligently discovers free resources, adapts to user context, and ensures reliable, proven guidance across multiple domains.
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。
Schedule and manage social media posts across Instagram, X (Twitter), Bluesky, TikTok, Threads, LinkedIn, Facebook, Pinterest, and YouTube using the AdaptlyPost API. Use when the user wants to schedule social media posts, manage social media content, upload media for social posting, list connected social accounts, check post status, cross-post content to multiple platforms, or automate their social media workflow. AdaptlyPost is a SaaS tool — no self-hosting required.
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。
NPU 图批量下发能力（aclgraph / aclgraph_ex 家族）的开发与调优。覆盖 mindiesd 的 aclgraph_backend：NPUGraph 静态 capture、全局 graph pool、 lazy capture、专用 copy stream + event 管线、shape/dtype 校验、max_entries 驱逐。 当用户需要减少 host launch 开销、静态 shape 大 batch 场景加速、 或排查 NPUGraph replay 输入不匹配问题时使用此 skill。 即使用户只提"批量下发""graph capture""图捕获"而未说 aclgraph，也应触发； pattern/Inductor 融合（default 后端）见 pattern-dev，算子本体见 operator-dev， 本技能只覆盖图批量下发。由 dev-workflow 的编译开发阶段与 model-auto-optimization 的 图下发场景指引加载。
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-level climate engineering covering carbon capture and storage, direct air capture, solar geoengineering, enhanced weathering, and carbon accounting.
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。
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
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。
Ajuste fino com eficiência de parâmetros para LLMs usando LoRA, QLoRA e 25+ métodos. Use ao fazer fine-tuning de modelos grandes (7B-70B) com memória GPU limitada, quando precisa treinar <1% dos parâmetros com perda mínima de precisão, ou para serviços multi-adapter. Biblioteca oficial do HuggingFace integrada ao ecossistema transformers.
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 an agent needs to drive a real Chrome window via opencli — inspect a page, fill forms, click through logged-in flows, or extract data ad-hoc. Covers the selector-first target contract, compound form fields, stale-ref handling, network capture, and the agent-native envelopes the CLI returns. Not for writing adapters — see opencli-adapter-author for that.
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 any URL and convert to markdown using baoyu-fetch CLI (Chrome CDP with site-specific adapters). Built-in adapters for X/Twitter, YouTube transcripts, Hacker News threads, and generic pages via Defuddle. Handles login/CAPTCHA via interaction wait modes. Use when user wants to save a webpage as markdown.
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。
Capture a POC's signed-off behaviour into its spec ledger (`<poc>/spec.json`) — the structured, walkable behaviour contract graduation freezes as authoritative. Run at the moment a behaviour gets signed off ("ok, this works"), while it's fresh — the same trigger as the HANDOFF.md update, but capturing the *behaviour as a testable entry* rather than the *decision as prose*. Use when a POC behaviour is approved, or asked to "capture this spec", "write the spec entry", "log this to the ledger".
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。
governance出力adapterの利用可能性を確認したいとき、入出力契約と代替経路を安全に特定したいときに使う。
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
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。
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
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。
Map advanced persistent threat (APT) group tactics, techniques, and procedures (TTPs) to the MITRE ATT&CK framework using the ATT&CK Navigator and attackcti Python library. The analyst queries STIX/TAXII data for group-technique associations, generates Navigator layer files for visualization, and compares defensive coverage against adversary profiles. Activates for requests involving APT TTP mapping, ATT&CK Navigator layers, threat actor profiling, or MITRE technique coverage analysis.
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。