「zat」の検索結果

Create 3D visuals with modeling, texturing, lighting, rendering, and optimization for web and product.

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。

Ship AI features to production — model selection, evals, latency/cost optimization, guardrails, monitoring, and iteration loops. Use when turning an LLM prototype into a reliable product feature.

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。

Marketing analytics and data-driven optimization for B2B SaaS campaigns. Use this skill when analyzing marketing performance, optimizing conversion rates, running A/B tests, conducting customer research, creating marketing dashboards, building attribution models, analyzing funnel metrics, or storytelling with data. Also triggers on: marketing ops, performance analytics, CRO, A/B testing, data storytelling, customer insights, tracking plan, event taxonomy, UTM taxonomy, GA4 audit, consent mode, instrumentation contract, sample size calculation, minimum detectable effect, test duration, not enough traffic to A/B test, statistical significance, Bayesian vs frequentist, sample ratio mismatch, experiment feasibility, martech stack, marketing tech stack audit, tool consolidation, build vs buy, vendor evaluation, shadow IT tools, ESP/CRM/platform migration, switching cost, cutover plan, suppression list migration, data portability, customer interviews, survey design, sampling frame, non-response bias, how many people should I interview, thematic saturation, voice of customer, jobs-to-be-done, buyer persona research, is this finding real, data enrichment, which enrichment provider should we buy, waterfall enrichment, contact data quality, match rate, our list data is bad, email verification, catch-all domain, accept-all, bounce rate from bad data, B2B data decay, how often should we re-verify contacts, ZoomInfo vs Apollo vs Clearbit evaluation, cost per usable record, where did this list come from, GDPR Article 14 notice, purchased list compliance, suppression screening, TAM list building, demand planning, marketing plan, how many leads do we need, what pipeline target should marketing carry, funnel model, top-down vs bottom-up plan, plan of record, annual marketing planning, quarterly planning, pipeline coverage we have to create, sales cycle lag, our leads cannot close this quarter, carry-in pipeline, scenario planning, conservative moderate aggressive forecast, stretch target, reforecast, re-forecast triggers, assumption register, capacity ceiling, addressable audience ceiling, marginal cost per lead, blended CPL is wrong, we missed plan and nobody knows why, AI policy for the marketing team, AI governance, AI acceptable use policy, which AI tools are we allowed to use, can I paste customer data into ChatGPT, shadow AI, AI use register, human review of AI output, when can we stop reviewing every AI draft, can the agent send on its own, the AI made a mistake now what, pull back AI autonomy, AI evals, our AI vendor changed the model, AI output went out wrong, prompt injection, can our AI read prospect replies safely, lethal trifecta, the AI leaked internal notes, turn off auto-generated ad assets, auto-applied recommendations, AI literacy training, EU AI Act Article 4, duplicate records in the CRM, dedupe before import, which value wins in a merge, CRM cleanup.

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。

Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who may accept the reward, how the introduction is made), designing a win/loss interview program, working out why we lose deals, designing GTM strategy, creating category positioning, planning analyst briefings, or deciding which country to expand into and how far to localize. Also use it for an early-stage startup where the founder is still doing the selling — running founder-led sales, setting up a design-partner program, judging whether you have product-market fit, deciding what not to do yet, deciding when to hire the first AE or first marketer, and moving upmarket to larger buyers. Also use it when your company has just acquired another (or is about to), to plan the marketing integration: what you may and may not do between signing and close, the first letter to the acquired customers, whether to keep, endorse, fold in or retire the acquired brand, merging the two marketing databases without mailing people who opted out, when to start cross-selling, and announcing a product sunset. Also use it to design a demand-generation campaign and the channel plan it runs on: one campaign with one job, the offer for buyers who are and are not in market, what each channel is for, the kill and scale rules set before launch, the follow-up sales agrees to, the yearly calendar of always-on programs and tentpole campaigns, and which channels to keep, test or stop. Also use it for brand marketing and demand creation — how much to spend on brand versus performance, what to measure when a brand campaign produces no conversion event, and how to answer "we cannot attribute it". Also triggers on: founder-led sales, founder-led GTM, design partners, design partner agreement, first customers, first 10 customers, do we have product-market fit, PMF, Sean Ellis test, very disappointed survey, pre-seed, seed stage, when to hire our first AE, first sales hire, first marketing hire, moving upmarket, going upmarket, enterprise readiness, first enterprise deal, what do enterprise buyers need before they sign, positioning, product launch, beta program, early access program, design partners, private preview, public preview, general availability, GA launch, when can we call it GA, can sales sell a beta feature, selling the roadmap, launch tier, competitive intelligence, messaging, customer advocacy, win/loss analysis, win/loss interviews, why we lose deals, closed-lost analysis, loss reason, close-reason field, competitive displacement, displace an incumbent, rip and replace, competitive takeout, switch from a competitor, win deals from a competitor, incumbent contract, renewal window, auto-renewal notice period, switching costs, EU Data Act, cloud switching rights, why do we lose to no decision, GTM, category design, ideal customer profile, ICP, what is our real ICP, who actually buys from us, refresh our ICP from closed-won deals, ICP refresh before planning, analyst briefing, G2 review, international expansion, market entry, expand into Europe, which country should we launch in next, localization, translate our site, in-country go-to-market, regional GTM, is cold email legal in Germany, brand marketing, brand awareness, brand vs performance, brand versus demand gen, demand creation, demand capture, 95-5 rule, out of market buyers, category entry points, distinctive brand assets, mental availability, brand tracking, brand health, brand lift, share of search, how do we measure brand, justify brand spend, brand budget. Also triggers on public-sector marketing: sell to government, government marketing, public sector go-to-market, federal marketing, state and local government, SLED, FedRAMP, FedRAMP marketing claims, can we say FedRAMP ready, GovRAMP, StateRAMP, VPAT, accessibility confor

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。

Email marketing operations and automation for B2B SaaS. Use this skill for newsletter strategy, email automation sequences, lifecycle campaigns, nurture workflows, onboarding sequences, deliverability optimization, email copywriting, lead scoring, marketing automation platform setup, and cold-email sending infrastructure — secondary sending domains, SPF/DKIM/DMARC, and domain warmup — plus the contact budget: a cross-channel frequency cap across every sender (marketing, sales sequences, customer success, in-app). Also triggers on: email, newsletter, drip campaign, lifecycle, nurture, onboarding sequence, deliverability, email automation, lead scoring, marketing automation, our emails are going to spam, SPF, DKIM, DMARC, sender reputation, sending domain, cold email domains, domain warmup, mailbox setup, blacklist, bounce rate, BIMI, brand logo in inbox, VMC, Verified Mark Certificate, Common Mark Certificate, transactional email, password reset emails going to spam, DMARCbis, RFC 9989, DMARC pct tag, DMARC t=y test mode, DMARC rollout, move DMARC to reject, frequency cap, email fatigue, customers get too many emails, too many messages, sales and marketing both emailing the same person, communication limits, send frequency safeguard, global frequency capping, quiet period, message precedence.

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 effective MCP server instructions for tool compaction support. Use when creating or updating the `instructions` parameter in MaaSProtectedFastMCP server initialization. Helps LLMs understand when to search for tools, workflow patterns, and cross-feature relationships.

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 provides unified expert-level guidance for terminal implementation in VS Code extensions. Covers xterm.js API and addons, VS Code terminal architecture, PTY integration, session persistence, input handling (keyboard/IME/mouse), shell integration with OSC sequences, and performance optimization. Use when implementing any terminal-related 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。

Reverse engineers binaries using radare2/rizin interactively, covering analysis initialization, navigation, disassembly and graph views, patching, and the visual mode workflow. Activates for requests to reverse a binary with radare2 or rizin, learn r2 commands, or navigate and disassemble a sample in r2.

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。

Converts a successful threat hunt into a durable detection by extracting the discriminating logic, defining data sources and thresholds, and emitting a Sigma rule plus a test and tuning plan. Activates for requests to operationalize a hunt, turn a finding into a detection rule, or productionize hunt logic as a Sigma detection.

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。

Set up GEPA prompt optimization for an ORC workflow

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。

Pulp musical/media time primitives, exact beat divisions, tempo and meter maps, transport-range grid projection, inline and order-preserving groove projection, coordinate randomness, streaming cursors, and quantization arithmetic.

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 and maintain browser demos of Pulp audio plugins (both web ABIs — WAM and WCLAP) from one declarative config, so every demo mounts the SAME shared player and the two ABIs stay in lockstep. Invoke it whenever you publish/update a browser demo of a Pulp plugin, add a plugin to a demo gallery, stand up a new gallery, or touch demo pages/hosting. It runs a deterministic generator (config → stamped WAM+WCLAP site + owned-files manifest) and a blocking validator (config schema, cross-origin-isolation coverage, OG metadata, regeneration ownership). Customization is declarative config in <repo>/.pulp-web-demo/config.json (schema bundled) plus at most two typed module seams; the shared player (pinned @danielraffel/web-player) holds all UX behavior and is never vendored. Works in Claude and Codex.

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 the user asks to analyze, consult, setup, manage, configure, or design a Volcengine Landing Zone, including organization, accounts, finance, identity, cloudtrail, or network infrastructure, or to deploy a solution/blueprint.

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。

Full project initialization wizard from ProjectConfig, including folders, packages, Git, and MCP setup. Use when setting up a new Unity project from scratch, creating the folder structure, or bootstrapping infrastructure. Triggers on requests like "set up a new project", "create folder structure", "initialize the project", or "/uw-cmd-setup-project". Reads ProjectConfig.yaml for all 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。

Unity Test Framework patterns for EditMode and PlayMode tests including async testing, mocking, and test organization.

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。

Structured performance profiling workflow. Identifies bottlenecks, measures against budgets, and generates optimization recommendations with priority rankings.

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。

Read all open bugs in production/qa/bugs/, re-evaluate priority vs. severity, assign to sprints, surface systemic trends, and produce a triage report. Run at sprint start or when the bug count grows enough to need re-prioritization.

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。

MemoryPack high-performance binary serialization for Unity including custom formatters, versioning, and performance 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。

Unity 6 performance profiling and optimization guide. Use when profiling, optimizing frame rate, reducing memory usage, debugging performance bottlenecks, or using the Profiler, Memory Profiler, or Frame Debugger. Based on Unity 6.3 LTS documentation.

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。

Unity lifecycle and execution order correctness patterns. Catches common mistakes with initialization ordering, destruction timing, fake-null, disabled components, editor vs runtime init, DontDestroyOnLoad, and async destruction. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS documentation.

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。

Unity 6 multiplayer and networking guide. Use when building multiplayer games, working with Netcode for GameObjects, NetworkManager, NetworkObject, NetworkBehaviour, RPCs (ServerRpc, ClientRpc), NetworkVariables, or Unity multiplayer services (Relay, Lobby). Covers client-server architecture, state synchronization, and scene management. Based on Unity 6.3 LTS documentation.

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。