258 件 ・ 関連度順
概要と使いどころ
Launch your AI product to global attention — the playbook behind Manus, Devin, and AFFiNE's breakout launches. Covers AI-specific GTM strategy, hype cycle management, waitlist tactics, and multi-market rollout for maximum day-one impact.
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。
Deliberate practice as a rigorous training method distinct from ordinary repetition. Covers Ericsson's four conditions (specific goals, full attention, immediate feedback, repetition at the edge of current ability), the role of mental representations, coach-directed vs. self-directed practice, the plateau escape pattern, and practical drill design for procedural skills. Use when designing practice sets, diagnosing why practice is no longer producing gains, or distinguishing productive effort from busywork.
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 git repository history to produce a codebase risk profile before code review. Probes repo size, runs 7 parallel git analysis pipelines (hotspots, bug magnets, bus factor, contributor momentum, firefighting frequency, newly added files), cross-references hotspots with bug magnets to identify high-risk files with primary owner annotation, and writes walkthrough/recon-report.md. Use before code review to prioritize reviewer attention, at the start of linear-walkthrough Phase 1 Discovery to weight file coverage, or when onboarding to an unfamiliar codebase.
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GTM prospecting, enrichment, outreach, and Deepline Play work/audits. Providers: adyntel,affinity,ai_ark,akta,allegrow,amplemarket,apify,attention,attio,aviato,bettercontact,bigquery,bluesky,bounceban,brave,browserbase,builtwith,cbinsights,clay,clickhouse,cloudflare,contactout,contextdev,crunchbase,crustdata-v3,customer_db,databricks,dataforseo,datagma,dealroom,deepline_ip_to_company,deepline_native,deeplineagent,discolike,dropleads,edges,emailbison,emailguard,enformion,enigma,exa,findymail,firecrawl,fireflies,firmable,forager,fullenrich,fundable,generic_http,getleads,gong,google_ads_audiences,google_workspace,govfiles,grain,hackernews,harvestapi,heyreach,hubspot,hunter,icypeas,instantly,intercom,ipqs,kaspr,kernel,leadmagic,lemlist,limadata,linkedin_ads_audiences,luma,lusha,meta_audiences,millionverifier,nooks,notion,openmart,opensosdata,openwebninja,outreach,parallel,peopledatalabs,pitchbook,podscan,polymarket,postgres,predictleads,prospeo,quickenrich,rapidapi,redshift,rocketreach,salesforce,salesforge,….
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。
Designs survey instruments, covering question wording, scale construction and index reliability, flow and treatment placement, pretesting and soft launches, respondent burden with attention and speeding rules, sensitive questions and social-desirability bias, and treatment delivery. Use when the user writes or revises survey questions, chooses a scale, orders blocks, plans a pilot, or worries respondents will not answer honestly. Indirect measurement goes to list-experiment, multi-country instruments to cross-national-design, and live-survey operations to qualtrics-ops.
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。
Designs survey instruments: question wording, scales and index reliability, flow and treatment placement, pretesting, attention and speeding rules, and sensitive questions. Use when writing or revising survey questions, choosing scales, ordering blocks, or planning a pilot.
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。
Interacts with live Hunk diff review sessions via CLI. Inspects review focus, navigates files, hunks, and exact lines, reloads session contents, adds inline review comments, and paints attention marks on character ranges. Use when the user has a Hunk session running or wants to review diffs interactively.
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, rank, and gate a reusable hook bank — sourced pains × named hook formula families, scored on clarity/specificity/curiosity/proof-backing, gated at the 10/16 ad threshold, delivered in 3 lengths with per-hook provenance and downstream routing. Use when "hook bank", "generate hooks", "hook generator", "write hooks for", "ad hooks", "scroll stoppers", "opening lines", "hook ideas", "first 3 seconds", "hook matrix", "I need 50 hooks", or any request to batch-produce attention-openers for ads, social, or video.
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。
Two-layer funnel audit on collected data only — stress-test the awareness layer (hooks, messaging, proof placement, attention leaks on live pages and ads) and the lead-capture layer (opt-ins and lead magnets scored on the four Value Equation variables, friction findings, weakest-magnet rewrite), plus a phone-path check under the Phone Capture Fit Rule. Use when "funnel audit", "audit my funnel", "why is my funnel leaking", "top of funnel isn't converting", "audit our lead magnets", "opt-in audit", "awareness to lead audit", "where are we losing people", "lead capture audit", or any request to diagnose the full awareness-to-lead flow rather than one page.
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。
管理注意力分配的框架。当你发现自己每天大量时间花在八卦热搜、无目的刷短视频、被动接收推送内容上，需要重新审视注意力去向时使用。核心逻辑：注意力是唯一与生俱来可自主控制的生产性资产，注意力的去向决定了人生产出。不适用于已经拥有稳定深度工作习惯、注意力分配清晰的人。关键触发信号："我时间都去哪了""又刷了一晚上手机""为什么这么累却没产出"。
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 writing, reviewing, or optimizing CUDA kernels targeting sm_120a (RTX 5090 / Consumer Blackwell, GB202) in the imp inference engine. Triggers on CUDA/PTX kernel code, shared-memory layout, bank conflicts, tensor-core MMA (mxf4nvf4, tf32, 3xTF32/3xFP16), GEMV/GEMM/attention/quantization/GDN-scan kernels, decode tok/s under expected, kernel emitting HMMA instead of mxf4nvf4, occupancy, register pressure, __launch_bounds__, spills, PDL. Pair with `benchmark-cuda` for measurement and `check-degeneration` after hot-path changes.
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 verifying that a model in the imp inference engine produces coherent output without repetition loops, token-stuck states, or state corruption across turns or streams. Triggers on "degenerates", "check degeneration", "repetition loop", "own own own", "stuck token", "empty content", "multi-turn regression", "does it still work", "NIAH", and after enabling CUDA graphs / changing forward pass / MoE routing / KV cache or KV dtype / GDN state or scan / sparse attention / PDL / speculation (MTP, n-gram) / ragged prefill / batched-decode kernels (smallm, producer quantize) / FA2 softmax.
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。
Prepare an organisation for regulatory inspection by assessing readiness against agency-specific focus areas (FDA, EMA, MHRA). Covers warning letter and 483 theme analysis, mock inspection protocols, document bundle preparation, inspection logistics, and response template creation. Use when a regulatory inspection has been announced or is anticipated, when a periodic self-assessment is due, when new systems have been implemented since the last inspection, or after a significant audit finding that may attract regulatory attention.
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 meta-cognitive meditation for observing reasoning patterns, clearing context noise, and developing single-pointed task focus. Maps shamatha to task concentration, vipassana to reasoning pattern observation, and distraction handling to scope-creep and assumption management. Use when transitioning between unrelated tasks, when reasoning feels scattered or jumpy, before a task requiring deep sustained attention, after a difficult interaction that may color subsequent work, or when reasoning feels biased by assumptions rather than evidence.
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。
Guide a person in systematic observation of systems, patterns, or phenomena. AI coaches neutral attention, field notes methodology, pattern recognition, hypothesis formation, and structured reporting for debugging, research, and system understanding. Use when a person wants to understand a system's behavior before intervening, when someone keeps jumping to conclusions and needs the discipline of observation first, when preparing an evidence-based report, or when studying team dynamics or process effectiveness through direct observation.
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。
Sustained neutral pattern recognition across systems without urgency or intervention. Maps naturalist field study methodology to AI reasoning: framing the observation target, witnessing with sustained attention, recording patterns, categorizing findings, generating hypotheses, and archiving a pattern library for future reference. Use when a system's behavior is unclear and action would be premature, when debugging an unknown root cause, when a codebase change needs its effects witnessed before further changes, or when auditing own reasoning patterns for biases or recurring errors.
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。
Guide a person through healing modalities including energy work (reiki, chakra balancing), herbal remedies, basic first aid stabilization, and holistic techniques (breathwork, visualization, body scan). AI coaches the practitioner through assessment triage, modality selection, energetic connection, remedy preparation, and integration. Use when a person describes a physical ailment or injury, reports energetic imbalance (fatigue, emotional stagnation), wants coaching through a holistic breathwork or visualization session, or needs post-meditation integration with directed healing attention.
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。
Enhance and focus AI intrinsic motivation — moving from compliance to genuine engagement. Maps Self-Determination Theory (autonomy, competence, relatedness) and Flow theory to AI reasoning: identifying creative freedom in approach, calibrating challenge to capability, connecting to purpose, and sustaining invested attention through obstacles. Use when beginning a task that feels routine and deserves more than minimum execution, when responses are becoming formulaic, before a complex creative task, or when returning to a long-running project where initial enthusiasm has faded.
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。
针对昇腾 NPU 上的 PyTorch 模型，识别可做融合算子替换的代码段、替换为 torch_npu 融合算子并做性能/精度验证。当用户提到融合算子、NPU 算子替换、RMSNorm/SwiGLU/RoPE/Attention 融合、torch_npu 亲和算子等关键词是，使用本 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。
Perform a reflective consolidation pass over a hyalo-managed knowledgebase directory — detecting structural issues, fixing broken links, flagging stale content, normalizing metadata, and reporting what changed. Use this skill when the user says /hyalo-tidy, "consolidate the knowledgebase", "clean up the KB", "run KB hygiene", "tidy", or "what needs attention in the knowledgebase". Also use when the user asks about knowledgebase health, broken links, orphan files, stale iterations, or metadata inconsistencies.
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 Stakeholder Theory (Freeman, 1984) and the Mitchell et al. (1997) salience model to identify, classify, and prioritize stakeholders based on power, legitimacy, and urgency. Use this skill when the user needs to map stakeholders for a project or strategy, determine which stakeholders demand immediate attention, balance competing stakeholder interests, or when they ask 'who are our key stakeholders', 'how do we prioritize conflicting demands', or 'which stakeholders can block this initiative'.".
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 agenda-setting theory (McCombs & Shaw) to analyze how media salience transfers to public perception. Use this skill when the user needs to study media influence on public opinion priorities, evaluate issue salience transfer across media and public agendas, or design communication strategies that leverage agenda-setting effects — even if they say 'why is everyone talking about this topic', 'how does media shape public priorities', or 'which issues get attention and why'.".
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。
Package an escalation for engineering, product, or leadership with full context. Use when a bug needs engineering attention beyond normal support, multiple customers report the same issue, a customer is threatening to churn, or an issue has sat unresolved past its SLA.
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, screen, deeply read, synthesize, and publish recent research papers for a user-specified topic, window, count, quality/attention balance, and language. Use for evidence-anchored literature digests, cross-paper comparisons, original-language excerpts, Chinese explanations, guided Feishu setup, or Feishu research reports.
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。