648 件 ・ 関連度順
概要と使いどころ
Use when tuning or profiling native code on Apple M-series Macs: unified memory, 16 KiB pages, Accelerate and Metal for matrix work, xctrace and leaks, Rosetta 2, or sysctl hardware queries.
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。
Menu engineering analysis — item placement, description quality, pricing psychology, upsell opportunities, photo presence, Kasavana matrix (Stars/Plowhorses/Puzzles/Dogs)
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。
Analyze Ascend NPU collective communication profiling data with a DB-first workflow. Use when the user provides `cluster_analysis_output/cluster_analysis.db`, rank-level `analysis.db`, rank-level `ascend_pytorch_profiler_{rank_id}.db`, together with `profiler_info.json`, and asks about HCCL or hcom communication cost, collective communication TOP ops, wait time, slow rank/straggler, Notify Wait, bandwidth, retry, relay, SDMA/RDMA/HCCS links, communication matrix, or Ascend communication fault patterns.
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。
Portfolio Analyzer — sector allocation analysis vs SPY benchmark, geographic exposure, correlation matrix, concentration risk (HHI), beta-weighted portfolio delta, dividend/income analysis, and prioritized rebalancing recommendations. Triggered by "trade portfolio" or "analyze my portfolio".
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。
제안서 디자인 에이전트. 승인된 proposal_script.md를 generate_제안서.py Python 코드로 변환합니다. slide_kit.py 함수 시그니처, VStack 레이아웃 계산, 7대 디자인 패턴, 겹침/넘침 방지, Dark-Light Rhythm을 적용합니다. 트리거: 디자인, 코드 생성, 레이아웃, VStack, slide_kit, 겹침, 넘침, COLS, GRID, FLOW, CHART, TABLE, HIGHLIGHT, KPIS, COMPARE, TIMELINE, PYRAMID, MATRIX, 그림자, 카드, Hero, Bento, Comparison
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 tests on BrowserStack. Use when user mentions "browserstack", "cross-browser", "cloud testing", "browser matrix", "test on safari", "test on firefox", or "browser 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。
Research your competitors and build an interactive battlecard. Outputs an HTML artifact with clickable competitor cards and a comparison matrix. Trigger with "competitive intel", "research competitors", "how do we compare to [competitor]", "battlecard for [competitor]", or "what's new with [competitor]".
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。
"Apply Ansoff Matrix to evaluate growth strategy options across market and product dimensions. Use this skill when the user needs to decide how to grow — through existing vs new markets and existing vs new products. Also use when the user asks 'how should we grow', 'should we launch a new product or expand to new markets', or 'what's our growth strategy'.".
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。
"Conduct SWOT analysis with TOWS matrix for strategic planning. Use this skill when the user needs to evaluate a company, product, or project by identifying strengths, weaknesses, opportunities, and threats, or wants to generate strategic options from internal and external factors. Also use when the user mentions competitive positioning, strategic assessment, or asks 'what are our advantages and risks', even without naming SWOT explicitly.".
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。
Generate project assessment markdown documents from JSON data with WHY/WHO/WHAT sections and GO/NO-GO decision matrix.
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。
Maakt regelrecht-scenario's vindbaar en hun norm-ketens leesbaar/geassert. Aan de invoerkant — vertaal een platte lijst leaf-parameters naar benoemde casus-assen + een herbruikbare persona-bibliotheek, met een reverse-lookup casus-matrix. Aan de uitvoerkant — maak de norm-keten zichtbaar via keten-checkpoints (assert elke knoop op het kritieke pad, niet alleen de endpoint) en golden-trace-snapshots + branch-coverage. Gebruik dit bij het schrijven of opschonen van scenario-/feature-files, het terugvinden of ontwerpen van een specifieke casus in een grote variabelenlijst, het reviewen van engine-traces, of het regressie-bestendig maken van cross-law-ketens zodat een ketenfout niet stil achter een correcte endpoint verdwijnt. Dossier-agnostisch; de regelrecht-methode is de vaste taal. Haakt aan op regelrecht-stelselanalyse (engine-tests / meta-check) en regelrecht-audit-products (testcase-scenario's).
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 structured vendor/tool evaluation matrices with weighted scoring, TCO analysis, and recommendation memos. Covers criteria definition, deal-breaker identification, and negotiation points. Use when selecting SaaS tools, evaluating technology vendors, or making build-vs-buy decisions.
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。
Conduct structured legal due diligence for M&A, joint ventures, or investment transactions. Cover all 9 workstreams — Corporate, Contracts, IP, Litigation, Regulatory, Employment, Tax, Environmental, and Data Privacy. Produce a risk matrix with deal-breaker flags and closing conditions. Use when evaluating a target or counterparty.
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。
Compare policies, procedures, onboarding files, or operating evidence against a named compliance framework such as AML/KYC, privacy, internal controls, or audit readiness. Use when a team needs a gap matrix, control checklist, remediation priorities, or evidence request list. Do not use when no target framework is specified or when formal legal or regulatory sign-off is 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。
Use when hunting self-hosted GitHub Actions runner vulnerabilities where fork pull requests can execute on privileged non-ephemeral runners. Trigger on: "self-hosted runner", "runs-on self-hosted", "fork PR workflow", "non-ephemeral runner", "first-time contributor approval", "runner images", "azure-builds runner", "outside collaborator approval", "runs-on matrix", "persistent runner", "Gato GitHub Attack Toolkit", "runner agent", self-hosted CI/CD runner abuse, "git config token", "workflow log deletion", runner C2.
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。
Test horizontal and vertical authorization bypass via session ID swapping between accounts, IDOR through parameter manipulation (invoice=, user=, menuitem=, EventID=), and special header injection (X-Original-URL, X-Rewrite-URL, X-Forwarded-For, X-Remote-IP, X-Client-IP with 127.0.0.1/localhost/RFC1918 values). Tools: Burp Suite with Autorize/AuthMatrix extensions, OWASP ZAP Access Control Testing add-on.
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。
AI/LLM red-team assessment using the OWASP LLM Top 10 (2025) + OWASP AI Testing Guide (AITG v1, Nov 2025) frameworks, plus OWASP MCP Top 10 runtime testing for agentic/MCP targets. Tests prompt injection, jailbreaks, system prompt leakage, sensitive data extraction, excessive agency, improper output handling, model extraction, content bias, evasion, membership inference, MCP token exposure, MCP command injection, and more. Uses four tools in combination: FuzzyAI (single-turn jailbreak fuzzing), PyRIT (multi-turn orchestrated attacks), Garak (probe-based vulnerability scanning), and promptfoo (plugin-based red-team evaluation). Each tool covers different OWASP categories; running them together gives systematic coverage. Includes a conditional MCP reconnaissance phase and a post-access AI infrastructure phase (chained from /post-exploit). Produces: OWASP LLM Top 10 + AITG + MCP coverage matrix, findings per category, architecture diagram of the AI system, PoCs for confirmed exploits. Chains into /gh-export for issue filing.
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 hunts and detections to MITRE ATT&CK for coverage analysis: tagging hypotheses with techniques, building a coverage matrix from completed hunts, and identifying high-risk gaps to prioritize next. Activates for requests to map hunts to ATT&CK, build a coverage heatmap, or find detection gaps by technique.
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。
Diagnose and fix slow pyfixest regression GRIDS (many feols/fepois calls run sequentially) that stay slow despite demeaner_backend="cupy64" and an idle GPU. Use when: (1) a script looping dozens of pf.feols models on a 100k+ row panel takes ~1 min/model, (2) process inspection shows ~1-1.5 cores busy and nvidia-smi shows ~0% GPU utilization with a resident cupy context, (3) planning any worker prompt that will run a model grid (robustness variants x FE structures x domains). Root cause: per-model CPU-side single-threaded fixed costs (formulaic model-matrix build, interaction construction, singleton detection, cluster vcov) dominate wall time; GPU demeaning is a small slice. Fix: shard the model grid across OS processes and/or use pyfixest multiple-estimation syntax; mandate this IN THE WORKER PROMPT.
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。
Generates networking boilerplate adapted to the project's chosen networking package (NGO, Mirror, Photon). Use when setting up multiplayer systems, syncing state, writing RPCs, building lobbies, or designing an authority matrix. Triggers on requests like "add multiplayer", "sync player health", "create an RPC", "set up lobbies", "make this networked", "add co-op", "replicate this across clients", "spawn networked objects", "handle player disconnect", "create a matchmaking system", or any task involving network state synchronization, remote procedure calls, or client-server architecture. Always reads ProjectConfig.yaml -> networking before generating code. If networking is "none", do NOT generate networking code.
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。
Inject juice and game feel into gameplay code using the project's chosen middleware. Use when adding screen shake, tweens, particles, audio feedback, haptics, hitstop, or any form of "juice" to gameplay events. Triggers on requests like "add juice", "make this feel better", "add screen shake", "polish this feature", "add feedback to this action", "make the hit feel impactful", "add particles when", "screen shake on damage", "tween this", "add camera shake", "make this snappy", or any game feel, polish, or feedback work. Always reads ProjectConfig.yaml -> feel_tools and docs/GFD.md Feedback Matrix before generating code.
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。
Validates completeness and consistency of the project architecture against all GDDs. Builds a traceability matrix mapping every GDD technical requirement to ADRs, identifies coverage gaps, detects cross-ADR conflicts, verifies engine compatibility consistency across all decisions, and produces a PASS/CONCERNS/FAIL verdict. The architecture equivalent of /design-review.
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 planning or reviewing a frontend testing strategy, selecting the right test layer by risk, mapping coverage across static checks, unit tests, component tests, integration tests, E2E, Storybook/visual regression, a11y, security, performance, or CI gates. Do not use to write individual component/E2E tests or merely run existing validation commands; Chinese triggers include test strategy, test layering, test plan, coverage matrix.
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。
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire or the AI annex buyers now attach to it, executing sales sequences, coaching qualification, or deciding what the website's AI chat agent is allowed to say. Also triggers on: outbound, cold outreach, reply handling, reply classification, out-of-office replies, auto-replies counted as replies, our reply rate is inflated, prospect replied remove me, opt-out by reply, is this list ready to send, launch readiness, CRM segment outbound, we emailed a current customer, outbound hit an open opportunity, ownerless leads, prospects engaging our competitors, competitor connections, displacement list, is this personalization creepy, can we mention they visited our site, signal freshness, deal strategy, pipeline, battle card, objection handling, common objections, why do we keep hearing this objection, mine call transcripts for objections, objection register, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, AI security questionnaire, AI annex, AI vendor due diligence, the buyer is asking if we train on their data, do you train on customer data, which model do you use, model provider sub-processor, AI subprocessor disclosure, where does inference run, can the customer turn the AI feature off, AI-CAIQ, CSA AI Controls Matrix, ISO 42001, ISO/IEC 42001, NIST AI RMF, EU AI Act Article 50, are we a provider or a deployer, AI feature disclosure, our model vendor changed and nobody told the buyer, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss, website chatbot, chat widget, AI chat agent, AI SDR, inbound AI SDR, conversational marketing, live chat, what should our chatbot be allowed to say, our chatbot quoted the wrong price, the bot promised a discount, do we have to disclose it is AI, EU AI Act chatbot disclosure, chatbot handoff to sales, chat transcript review, prompt injection on our chatbot, Drift, Qualified, Intercom.
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。