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概要と使いどころ
Use when the user uploads a screenshot of a hero section or landing page (or a URL/description of one) and wants a copy-paste-ready developer prompt to recreate it exactly in a tool like Lovable, Bolt, Replit, or Cursor. Produces prompts with exact hex colors, Tailwind classes, animation timing tuples, and component structure — not vague descriptions.
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。
타입·상태별로 반복되는 switch/if-else 분기를 다형성(인터페이스 + 구현 클래스)으로 치환. "switch를 다형성으로", "타입 분기를 클래스로", "strategy 패턴", "/replace-conditional-with-poly" 요청 시 사용. 단, null 분기만이면 /introduce-special-case, 조건식 가독성만이면 /decompose-conditional이 적합. /replace-conditional-with-poly [commit-ref]로 호출.
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。
임시 변수를 메서드 호출(query)로 치환하여 중복 제거·추출 용이성 확보. "임시 변수 메서드로", "temp 제거", "지역 변수를 쿼리로", "/replace-temp-with-query" 요청 시 사용. 단, 임시 변수가 서로 얽혀 치환 불가면 /extract-method-object가 적합. /replace-temp-with-query [commit-ref]로 호출.
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。
명령형 for/while 루프를 Stream API/Collection Pipeline으로 변환하여 데이터 흐름 의도 명확화. "스트림으로 바꿔", "루프를 파이프라인으로", "for문 stream", "/replace-loop-with-pipeline" 요청 시 사용. 단, 루프 안 로직이 컬렉션 클래스로 모여야 하면 /first-class-collection이 적합. /replace-loop-with-pipeline [commit-ref]로 호출.
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。
Find live third-party GitHub issues and discussions on topics where you have real hands-on experience and artifacts, then reply with that experience to build reputation. Use when asked to answer people about your work, find threads matching your expertise, or reply with evidence from your own setup.
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。
Ответы Антона в топики клуба СОСТАВ полным циклом: показать черновик ВМЕСТЕ с исходным диалогом (на что отвечаем) → Антон выбирает основной/запасной/свой текст → отправить в клуб ДОСЛОВНО через дверь sostav_reply_send.py на хабе (@[рабочий аккаунт],… Триггеры: '/sostav-reply', 'ответь в составе', 'отправь в состав', 'шли в состав', 'запость в топик состава', разбор утренней партии SostavDailyVoice из Saved
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。
Answer reviewers on your own pull requests in other people's repos: find threads where the ball is on your side, tell humans from bots, do exactly what was asked and reply with evidence. Use at the start of any GitHub session or on a new-review alert. Triggers: /pr-reply, /prr, answer the reviewers, who is waiting on us.
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。
Work the comments under published posts in one pass: list unanswered ones, reply only where a reply is genuinely expected (at most three per pass), name top commenters as warm-DM candidates, and prepare reply drafts on approval. Triggers: "/comments", "unanswered comments", "who is commenting".
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。
Sort an email backlog into reply, delegate, archive and ignore, and draft the replies. Nothing is sent without your GO. Use for "inbox zero", "sort my mail", "clear my email backlog", "draft replies to my mail".
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。
Unified chat inbox (Busabase App-in-Skill) aggregating WhatsApp, Discord, Slack, and Telegram messages into one place with a reply queue. Use when the user invokes $kelly-messenger or /kelly-messenger, wants a unified inbox, chat aggregation, to read WhatsApp/Discord/Slack/Telegram messages in one place, review unanswered conversations, queue or approve replies, run connector sync, or manage the outgoing reply queue.
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。
Personal App-in-Skill voice-of-customer desk (Busabase App-in-Skill) aggregating user feedback from support email, Discord/Slack communities, X replies, app-store reviews, surveys, and interviews into clustered feature requests and a roadmap decision queue. Use when the user invokes $kelly-feedback or /kelly-feedback, or mentions user feedback, voice of customer, feature requests, roadmap decisions, feedback clustering, feedback triage, request dedupe, changelog replies, decline replies, or reviewing what users are asking for.
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。
Detects and analyzes Bluetooth Low Energy (BLE) security attacks including sniffing, replay attacks, GATT enumeration abuse, and Man-in-the-Middle interception. Uses Ubertooth One and nRF52840 sniffers for packet capture, the bleak Python library for GATT service enumeration, and crackle for BLE encryption cracking. Use when assessing IoT device BLE security, monitoring for BLE-based attacks on wireless infrastructure, or performing authorized BLE penetration testing. Activates for requests involving BLE security assessment, Ubertooth sniffing, GATT enumeration, or BLE replay 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。
Finds the most informative session recording linked to an error tracking issue. Use when a user has an error tracking issue ID and wants to watch a replay showing what the user was doing when the error occurred. Ranks linked sessions by recency, activity score, and journey completeness, then summarizes the pre-error context. Replaces blind session picking from potentially hundreds of linked recordings.
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。
Guides agents through creating and safely sizing a Replay Vision scanner: choosing the scanner type (monitor/classifier/scorer/summarizer), shaping the RecordingsQuery that selects sessions, and — crucially — estimating observation volume and checking the org's monthly quota before creating, so a broad scanner doesn't exhaust the budget on its first scheduled sweep. TRIGGER when: user asks to create, set up, or configure a Replay Vision scanner, OR when you are about to call vision-scanners-create, OR when widening an existing scanner's query or sampling_rate via vision-scanners-update. DO NOT TRIGGER when: only reading scanners or observations, deleting a scanner, or running an existing scanner against a single session on demand (vision-scanners-scan-session).
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。
Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.
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。
Dereplicate a putative natural product and assign its chemical taxonomy. Use to answer "is [compound] a known natural product", "what microbe/organism produces [compound]", "what chemical class is [compound]", "dereplicate this metabolite (by formula/exact mass/InChIKey/SMILES)", or "classify this molecule into ChemOnt". Searches NPAtlas for known microbial natural products (producing organism + literature reference), assigns the ChemOnt kingdom→superclass→class→subclass hierarchy via ClassyFire, resolves systematic IUPAC names to structure via OPSIN, and cross-references identity in PubChem. NOT for general drug/compound identity or ADMET (use tooluniverse-chemical-compound-retrieval / tooluniverse-small-molecule-discovery) and NOT for metabolomics pathway/enrichment analysis (use tooluniverse-metabolomics skills).
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。
Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal 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。
Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.
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 the AEM 6.5 LTS Replication API for programmatic content activation, deactivation, and replication status management
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。
Configure AEM 6.5 LTS replication agents for content publishing, dispatcher cache flushing, and reverse replication
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。
Compares Hi-C contact maps between conditions across the right scale -- differential bin-pair contacts (multiHiCcompare, diffHic), differential A/B compartments (dcHiC), differential TAD boundaries (delta insulation), and differential loops (diffloop, DiffHiChIP) -- with distance-stratified between-sample normalization, replicate-aware NB-GLM FDR, HiCRep SCC reproducibility gating, and CNV correction for cancer/aneuploid samples. Use when comparing Hi-C between treatment and control, finding differential contacts/compartments/boundaries/loops, normalizing two maps of unequal depth, choosing a replicate-aware test, gating replicates with SCC, or correcting copy-number artifacts before a tumor-vs-normal 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。
Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.
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。
NanoClaw v2の操作と拡張 — ECCのゼロ依存関係セッション対応REPLで、claude -p上に構築。
Decide whether a request is scope creep — "is this in scope", "is this scope creep", "should I push back on this client request", "draft a boundary reply". Returns in-scope, creep or grey-zone with a suggested reply.
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。