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Use when scoring a list of business or solution requirements against the *actual* capabilities of a specific Salesforce org so each row can be classified Standard / Configuration / Low-Code / Custom / Unfit, given an effort tier (S/M/L/XL), a risk tag, and an AppExchange suggestion when applicable. Trigger keywords: fit gap salesforce requirements, score requirements against salesforce capabilities, salesforce capability matrix, classify requirement as standard config custom, fit-gap effort tier, AppExchange alternative for requirement. NOT for requirements elicitation (use admin/requirements-gathering-for-sf). NOT for architecture decisions on the GAP rows (use architect/solution-design-patterns and standards/decision-trees/). NOT for license or edition selection (use architect/license-optimization-strategy and architect/org-edition-and-feature-licensing). NOT for OmniStudio-specific fit-gap (use architect/omnistudio-vs-standard-decision).

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。

Author the Salesforce Configuration Workbook — the structured, reviewable handoff document an admin uses to execute a feature across Objects/Fields, Page Layouts, Profiles/PSGs, Sharing, Validation, Automation, List Views, Reports, Integrations, and Data. Triggers: 'salesforce configuration workbook', 'admin handoff document', 'implementation workbook'. NOT for object design itself (use admin/custom-field-creation, admin/lookup-and-relationship-design, agents/object-designer/AGENT.md), NOT for permission set design (use admin/permission-set-architecture, agents/permission-set-architect/AGENT.md), NOT for Flow construction (use skills/flow/* and agents/flow-builder/AGENT.md), and NOT for the deployment manifest (use skills/devops/metadata-api-retrieve-deploy). More triggers: workbook row schema, recommended_agent, recommended_skills, row_id, source_req_id, RTM linkage block, not-in-scope-this-release, descope ledger, version-lock the workbook, check_workbook.py.

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 configuring or troubleshooting Salesforce CPQ contract creation, subscription management, amendment quotes, or renewal quotes. Trigger keywords: contract, amendment, renewal, subscription, co-termination, SBQQ__Subscription__c. NOT for designing the amendment/renewal architecture or swap pattern — use architect/subscription-management-architecture. NOT for amending or renewing contracts from Apex — use apex/cpq-api-and-automation. Also covers the standard Contract and Order objects underneath CPQ — Contract Status vs StatusCode, activation locking, EndDate auto-calculation, ContractSettings and OrderSettings, reduction orders, and renewal-reminder automation. Trigger keywords: Contract, ContractStatus, StatusCode, ActivatedDate, OwnerExpirationNotice, ContractTerm, EndDate, Order, OrderItem, reduction order, ContractSettings, OrderSettings, renewal reminder. NOT for Revenue Cloud or Subscription Management objects — use architect/revenue-cloud-architecture and architect/subscription-management-architecture.

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 decisions for when and what sounds to use in web apps, mobile apps, and desktop native apps — plus how to create them with AI. Covers UI sound vocabulary (confirms, alerts, transitions, errors), platform conventions (iOS, macOS, Material), creating sounds with AI tools (ElevenLabs, AudioCraft, Stable Audio), Web Audio API for procedural sounds, haptic-audio pairing, and the psychology of satisfying vs. annoying UI sounds. Activate on 'app sounds', 'UI sounds', 'notification sound', 'sound design app', 'earcons', 'sonic branding', 'interaction sounds', 'feedback sounds', 'app audio', 'satisfying sounds'. NOT for professional audio engineering (use sound-engineer), Windows 3.1 retro sounds specifically (use win31-audio-design), music composition (use sound-engineer).

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。

Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-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。

Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.

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。

Best practices for Remotion - Video creation in React. 29 domain-specific rules covering 3D, animations, audio, captions, charts, transitions, and more. Use when building video in React with Remotion — animations, audio, captions, charts, or transitions.

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。

既存コード・既存関数・既存モジュールの暗黙契約を抽出するスキル。 戻り値型、副作用、例外、前提条件、境界条件、環境依存挙動を確認し、 reuse前のリスクを可視化する。名前やコメントではなく実際の挙動から 契約を読み取り、不一致を分類し、再利用可否を判定する。 Use when reusing legacy code, verifying actual behavior of existing functions, or extracting implicit contracts before implementation. Covers: hidden contract, implicit contract, reuse risk, legacy behavior, 暗黙契約, 既存資産調査. Analyzes return types, side effects, exceptions, preconditions, boundary conditions, and environment-dependent behavior.

Turns one decision discussion (meeting transcript, chat thread, email chain or notes) into a DRAFT one-page decision memo: the decision as stated, status, options considered, evidence cited, dissent recorded verbatim, owner, effective date and review date, with UNKNOWN for anything the discussion did not settle. Use when the user asks to "write up the decision", "record what we decided", "capture the decision from this thread", "draft the decision memo" or "add this to the decision log". Do not use for full minutes or action items, use transcript-to-actions instead; for a technical design decision, use architecture-decision-record; for a paper seeking a decision not yet taken, use board-paper-skeleton. Drafts for human review; never approves, authorises or signs off.

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。

WooCommerce Subscriptions data model, switcher, and gifting reference for exact order type names, product type slugs, subscription meta keys, schedule/date keys, related-order relation meta, switch cart data, switch order data, switched item types/meta, proration hooks, and WCS Gifting recipient storage. Use when code reads or writes shop_subscription, subscription, variable-subscription, subscription_variation, _billing_period, _schedule_next_payment, _subscription_switch_data, _subscription_switch, subscription_switch, _switched_subscription_item_id, wcsg_gift_recipients_email, _recipient_user, _recipient_user_email_address, wcsg_recipient, or when an agent needs the full WooCommerce Subscriptions switcher/gifting flow.

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 review Action Scheduler jobs in WordPress plugins using Action Scheduler 3.9.x public APIs - async, single, recurring, and cron-expression actions; action_scheduler_init load timing; hook/args/group naming; unique and priority parameters; idempotent callbacks; chunked workloads; activation/deactivation cleanup; WooCommerce-bundled or standalone dependency usage; admin and WP-CLI debugging; queue runner limits; and safe operational troubleshooting. Use when a plugin schedules background jobs with as_enqueue_async_action, as_schedule_single_action, as_schedule_recurring_action, as_schedule_cron_action, as_get_scheduled_actions, or integrates with WooCommerce background queues.

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。

Configures the JetFormBuilder action events system — the named events (DEFAULT.PROCESS, DEFAULT.REQUIRED, GATEWAY.SUCCESS, GATEWAY.FAILED, BAD.REQUEST, ON.DYNAMIC_STATE, never) that decide WHEN a Form Action runs. Covers declaring supported / unsupported / required events on a custom action, the validation precedence inside Base_Event::is_valid_action(), the multi-event subscription model the action editor exposes, and how to register a brand-new event type via the 'jet-form-builder/event-types' filter using Base_Event, Base_Action_Event, or Base_Gateway_Event. Use when an action needs to run only on payment callbacks, only on validation failure, only on a specific conditional state, after another action's hidden flow, or when the plugin needs to define its own event class (e.g. for inbound webhooks). Triggers on mentions of "JFB events", "action events", "GATEWAY.SUCCESS", "DEFAULT.PROCESS", "supported_events", "unsupported_events", "get_required_events", "Base_Event", "Base_Gatewa...

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。

Create an Estuary derivation that joins two or more collections on a shared key, merging their fields into a single enriched collection. Use for data enrichment, denormalisation, building wide tables for BI, and real-time CDC joins. Derivations add complexity and cost — confirm the user wants a derivation before reaching for this (a destination-side SQL join or BI tool view is often simpler). Use when user says "join-collections derivation", "derivation to join two collections", "transformation to enrich with customer data", "derive a wide table", "lookup-join derivation", or "build a join derivation".

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。

Implement iOS authentication patterns including Sign in with Apple (ASAuthorizationAppleIDProvider, ASAuthorizationController, ASAuthorizationAppleIDCredential), credential state checking, identity token validation, ASWebAuthenticationSession for OAuth and third-party auth flows, ASAuthorizationPasswordProvider for AutoFill credential suggestions, and biometric authentication with LAContext. Use when implementing Sign in with Apple, handling Apple ID credentials, building OAuth login flows, integrating Password AutoFill, checking credential revocation state, or validating identity tokens server-side.

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。

Performs runtime mobile security exploration of iOS applications using Objection, a Frida-powered toolkit that enables security testers to interact with app internals without jailbreaking. Use when assessing iOS app security posture, bypassing client-side protections, dumping keychain items, inspecting filesystem storage, and evaluating runtime behavior. Activates for requests involving iOS security testing, Objection runtime analysis, Frida-based iOS assessment, or mobile runtime exploration.

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。

Windows アプリ開発 (DirectX / WinRT メディア) のグラフィックス・メディア API リファレンス。 Direct2D (ID2D1Factory, ID2D1DeviceContext, ID2D1Bitmap1, ID2D1Effect, ID2D1PathGeometry), DirectWrite (IDWriteFactory, IDWriteTextLayout, DWriteCore), Direct3D 11/12 (D3D11CreateDevice, DXGI SwapChain, HLSL, D3D12 PipelineState), Microsoft.UI.Composition (Compositor, Visual, ExpressionAnimation, InteractionTracker, MicaController), カメラ・画面キャプチャ (MediaCapture, MediaFrameReader, GraphicsCaptureSession, Windows Studio Effects)、音声・動画再生 (MediaPlayer, MediaPlaybackSession, AudioGraph, MediaTranscoder, AdaptiveMediaSource)。

Generate ideas that don't sound logical, then validate them with cheap behavioural experiments — Rory Sutherland's 'the opposite of a good idea can be a good idea' plus revealed-preference testing. Use when the obvious/logical solution is saturated and the user wants genuinely different options, asks 'what's a creative/unconventional angle', 'how do we stand out', 'should we run a test/experiment', 'how do we know what people actually want', or is about to trust a survey/focus group. Covers deliberate inversion of the obvious move, why stated preferences lie, and designing small reversible experiments that watch behaviour. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic. 日本語の相談（「競合と同じ案しか出ない」「アンケートは好評なのに売れない」「思い切った案を安く試したい」）にも使う。中文咨询（“只能想出和竞品一样的方案”“问卷好评却卖不动”）也适用。

Tests whether two genomic interval sets overlap (colocalize) more than expected by chance using a permutation test against a structured-genome null model. Covers bedtools fisher (analytic 2x2 screen), bedtools shuffle + jaccard permutation, GAT (isochore/GC-conditioned simulation with FDR), regioneR (flexible permutation, randomizeRegions vs circularRandomizeRegions, localZScore), LOLA (universe-relative Fisher against a region database), and GREAT/rGREAT (regulatory-domain binomial + hypergeometric for ontology-from-regions). Stresses the universe/background choice, matched background, blacklist exclusion, and multiple-testing control. Use when asking whether peaks/regions are enriched at enhancers/TFBS/features, scoring region-set colocalization or region-set enrichment, comparing CNV/SV concordance, or turning an overlap count into a defensible p-value.

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。

Assigns pathogen lineages (SARS-CoV-2 Pangolin via UShER mode; Nextclade clade + QC; pango-designation alias_key.json resolution) and tracks variant frequencies over time using Nextstrain (Augur + Auspice), wastewater deconvolution (Freyja, COJAC, alcov, lineagespot), lineage fitness modelling (Wenseleers / Bedford-Figgins multinomial logistic), and recombinant detection (3SEQ, RDP4, Bolotie). Covers Pangolin pangolin-data version pinning (mandatory for reproducibility), Nextclade dataset versioning (lineage-defining mutations change with dataset), Freyja barcode forward-only date constraint, ARTIC primer scheme version churn (V3 / V4 / V4.1 / V5.3.2 / Midnight 1200) with documented dropout regions, recombinant X-prefix Pango designation lag, GISAID vs INSDC dual-deposition tensions, and the Karthikeyan 2022 wastewater early-detection signal with explicit reproducibility caveats. Use when assigning Pango lineages and Nextclade clades to viral consensus sequences, building Nextstrain Augur surveillance pipelines, deconvolving wastewater pooled samples into lineage frequencies with Freyja, tracking lineage frequencies and growth advantages over time, pinning pangolin-data / Nextclade dataset versions for reproducibility, handling ARTIC primer dropouts (V4.1 amplicons 64 / 76 / 88-90), or running variant surveillance for SARS-CoV-2 / influenza / Mpox / RSV / H5N1 / measles.

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。

Quantifies biodiversity from species abundance/incidence tables using Hill numbers (iNEXT) with coverage-based rarefaction-extrapolation (Chao & Jost 2012), asymptotic richness via Chao1/ACE/jackknife as a lower bound, Baselga turnover/nestedness partition with the Podani alternative as sensitivity check, mandatory Hellinger transformation before ordination (Legendre & Gallagher 2001), Faith PD and SES_MPD/SES_MNTD with explicit null-model choice, and Maire 2015 functional-diversity dimensionality optimization. Use when comparing diversity across sites with unequal sampling effort, picking the right richness estimator for singleton-heavy amplicon data, partitioning beta diversity into turnover vs nestedness, reporting Hill-number effective species counts rather than raw entropies, computing SES_MPD with explicit null-model justification, or deciding whether to apply standard metrics to compositional amplicon data. Not for clinical 16S microbiome diversity (see microbiome/diversity-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。

Infers person-to-person transmission from pathogen genomes using outbreaker2 (Campbell 2018), TransPhylo (Didelot 2017), phybreak (Klinkenberg 2017), BadTrIP (De Maio 2018), SCOTTI (De Maio 2016), BEASTLIER (Hall 2015), and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs / Walker 2013; MRSA <=15 / Coll 2017; C. difficile <=2 / Eyre 2013; Klebsiella <=21 / Snitkin 2012), models within-host diversity and transmission bottlenecks (Worby-Lipsitch-Hanage 2014; McCrone 2018; Sobel Leonard 2017; Lythgoe 2021 SARS-CoV-2), integrates contact-tracing data, distinguishes generation interval from serial interval (Britton & Scalia Tomba 2019; Ali 2020), attributes source via Bayesian source attribution (Mather 2013 DT104; islandR), and reconciles transmission-network reconstruction with epi metadata. Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB / chronic HIV.

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。

Resolve the architecture of focal oncogene amplifications — extrachromosomal DNA (ecDNA), breakage-fusion-bridge (BFB) cycles, homogeneously staining regions (HSR), and linear amplification — from whole-genome sequencing with AmpliconArchitect, the AmpliconSuite pipeline, and AmpliconClassifier. Covers copy-number seed selection, breakpoint-graph reconstruction, balanced-flow optimization, ecDNA classification, and the limits of depth-only amplification calls. Use when a focal amplification needs structural characterization, when distinguishing ecDNA from chromosomal amplification, suspecting ecDNA-driven oncogene amplification or therapy resistance, or selecting copy-number seeds for amplicon reconstruction.

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。

NotionページをPDFファイルに変換するスキル。Notion MCPでページ内容を取得し、見栄えのよいPDFとして出力する。ユーザーがNotionページのURL・ID・タイトルを指定してPDF化・PDF変換・PDF出力・印刷用出力を依頼した場合に使用する。「このNotionページをPDFにして」「NotionページをPDFに変換して」「Notionを保存したい」「このページを印刷したい」「ドキュメントをPDFで共有したい」といった表現で起動する。ユーザーの発言にNotionページのURLが含まれていてPDF化の意図がある場合は、明示的にPDFと言っていなくても積極的にこのスキルの使用を検討する。

Introduce the cross-section read interface boundary (I<Section>ServiceRead) for one section's service per memory/architecture/section-read-write-split.md. Audits the surface, evaluates which methods belong on the read interface, sets up the workspace, dispatches a subagent that introduces the interface and migrates non-section callers, opens a PR. Use when the user says 'read split for X', 'split <Section>Service', 'add I<Section>ServiceRead boundary', 'apply the section-read-write-split rule to <Section>', or any variation of carving the cross-section read surface out of a section's full service interface. Reference implementation is Teams (PR 678). Operates on one section per invocation.

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。