「bridge」の検索結果

Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines from JSONPath to JSONata. Use when the user is building, authoring, debugging, or migrating a Step Functions state machine or ASL definition, or orchestrating multi-step workflows with branching, retries, or human-approval callbacks, even if they don't say 'Step Functions.' Do NOT use for general Lambda function code, API Gateway, EventBridge wiring, or SAM/CDK application packaging.

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Guides general use of AWS messaging and streaming services. Covers Amazon SQS, Amazon SNS, Amazon EventBridge, Amazon MQ, Amazon Kinesis Data Streams, Amazon Data Firehose, Amazon Managed Service for Apache Flink, and Amazon Managed Streaming for Apache Kafka (MSK). Use when reasoning about messaging and streaming patterns. Also identifies which AWS service owns each customer communication channel: email (Amazon SES), and WhatsApp, SMS, MMS, RCS, voice and mobile push (the AWS End User Messaging family of services). Routes the request to the specialized skill for that channel. Defers to the channel's specialized skill when the user already named a specific channel. In general, use specific skills or documentation searches for detailed service-specific questions. Do NOT use for MSK or Managed Service for Apache Flink questions, prefer specific skills. Does not configure customer communication channels; defers to specific skills.

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Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (DisabledApiException), metered AMI/Container + IAM roles, where registration data lives (customer-profile table), legacy ProductCode + CustomerIdentifier, DuplicateRecord/CustomerNotSubscribed, bad LicenseArn. Also SCOPES adjacent asks — flat-rate/SaaS-Subscription "do I still meter", CCP included-units + overage, contract term/annual renewal, forecasting future bills/usage — with the right answer or a one-line redirect. Use for any BatchMeterUsage/ResolveCustomer or SaaS usage-billing question.

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Diagnose whether a Codex Desktop update changed codexhost Composer/CDP bindings, private Renderer DOM or React state, Host bridges, routing, the Codex usage submission gate, or injected UI. Use after an installed Codex update or when compatibility regresses and the affected surface is unknown.

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Grida Desktop Electron shell and release-impact work: BrowserWindow, preload, `window.grida`, menus, protocol/deep links, file associations, Forge, path-scoped bridge security, Electron-only UI bugs, and CDP / Playwright verification. Use for `desktop/`, `editor/app/desktop/**`, `editor/scaffolds/desktop/**`, `editor/lib/desktop/**`, `/desktop/*` CSP, GRIDA-SEC-004, and deciding whether linked-package or hosted-renderer changes require a native Desktop version bump or coordinated release. For implementing daemon/agent-tenant core behavior, use `agent-system` as well.

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DeFi attack pattern playbook. Use when analyzing flash loan attacks, price oracle manipulation, MEV sandwich attacks, governance exploits, bridge vulnerabilities, and token standard edge cases in decentralized finance protocols.

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Converts an audited medical research gap into a complete, structured, gap-traceable study design. Always use this skill whenever a user already has one or more candidate research gaps and wants to transform them into an executable biomedical research plan rather than re-run broad topic ideation. Covers six gap-to-design patterns (evidence-completion, mechanism-resolution, cell-state/context-mapping, translation-bridge, causality-upgrade, population/stage-specific) and always outputs one recommended primary protocol, a gap-to-design dependency map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and verified design-support literature rules. Never fabricate references. Preserve claim-evidence discipline and do not replace a topic-specific gap with a generic workflow.

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Identifies translationally meaningful paths for bioinformatics findings by mapping omics or computational discoveries to diagnosis, stratification, prognosis, treatment-response, monitoring, or target-nomination use cases, while auditing bridge evidence, assayability, and validation burden. Use this skill when a user wants to know whether a bioinformatics finding can be framed as a stronger translational topic without overclaiming clinical relevance. Always separate statistical signal from translational value, and never imply clinical utility, targetability, or validation depth without explicit evidence support.

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Map this token system to or from any external design system (Material Design 3, Apple HIG, Fluent, Carbon, Ant, shadcn/ui, Radix, Chakra, Mantine, Bootstrap…) — adopt their look, build on their stack, or migrate between systems. Use when the user mentions interop, migration, or a specific design-system/component-library bridge.

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Provides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridge overhead, FlashList, native modules, or debugging jank and frame drops.

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Half-hour television comedy craft (半小时情景喜剧/笑点力学/困境机器/多机位单机位格式) — merged from Evan S. Smith's Writing Television Sitcoms (premise-driven comedy in three levels, nine predicaments, six character mixes, setup/punchline mechanics, toppers, running gags, ten comedic nuances, format rules), Neil Landau's sitcom seven-step formula and comedy-room models, Richard Blum's act-length and set-count parameters, Phoebe Waller-Bridge's Fleabag scripts (direct address as a season-long device, six-episode skeleton), Pamela Douglas on dramedy, Kam Miller on complementary comic traits, and Jesse Armstrong on jokes carrying tragedy. Use when writing or fixing a sitcom episode or spec, raising joke density per page, designing a comic predicament that generates stories, choosing between multi-camera and single-camera format and page counts, structuring cold open/acts/tag, writing a half-hour pilot, running a comedy punch-up, or making a drama funny without shifting genre.

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How episodic television actually gets made by a group (编剧室与制作现实) — merged from Goldberg & Rabkin (pitch as audition, leave-behind, cracking the story, beat sheet, notes discipline, production rewrites), Pamela Douglas (John Wells's room, staff-from-hell mistakes, the seven-rung ladder, step deal, the 14-day draft), Neil Landau's showrunner interviews (Lindelof, Mazzara, Katims, Bays), Evan Smith on sitcom staffing and roundtables, Richard Blum (dated), Kam Miller, and first-hand accounts by David Chase, Jesse Armstrong, Lucy Prebble, Aaron Sorkin, Julian Fellowes and Phoebe Waller-Bridge. Use when joining or running a writers' room, breaking an episode with a group, writing a leave-behind, beat sheet or outline on deadline, pitching episode ideas to an existing series, writing a spec episode, taking or giving notes, rewriting because of money, actors or locations, choosing between a staffed room and a single-author process, or asking 什么是 showrunner／编剧室怎么运作／怎么接 note.

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Case studies of television series writing (剧集案例库) from primary texts; Sorkin's six West Wing teleplays (act-page tables, eight act-out types); Chase's five Sopranos scripts (the 35-beat A/B/C/D recipe, what a pilot refuses to explain); Fellowes's annotated Downton Abbey season two (19 storylines, 419 footnotes); Waller-Bridge's Fleabag Scriptures (the six-episode half-hour template); Calvisi's eight minute-by-minute pilot beat sheets (Breaking Bad, Mad Men, Game of Thrones and more); Landau's 47-series structure appendix; Miller's Hannibal and HTGAWM breakdowns; Goldberg & Rabkin's beat sheets; Sakamoto Yuji's We Made a Beautiful Bouquet (a feature) and Noh Hee-kyung's The Most Beautiful Goodbye. Use when you want a worked example of how an episode or pilot is built, need real act lengths, scene counts or storyline grids to imitate, are breaking a multi-thread ensemble episode, designing a bottle episode or a finale, writing a relationship or family drama, or ask 某一集是怎么写的 / 这部剧的结构表.

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AI DevKit · Connect the current agent session to an available Telegram channel bridge.

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AI DevKit · Connect the current agent session to an available Slack channel bridge.

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Plan, deploy, operate, and troubleshoot Azure Local (formerly Azure Stack HCI): sizing and prerequisites, Arc registration, lifecycle updates, workloads (Azure Local VMs, AKS on Azure Local, images, disks, logical networks), SDN and network security, and failure triage — starting read-only and confirming before risky changes. WHEN: Azure Local, Azure Stack HCI, Arc resource bridge, custom location, Azure Local VM, Arc VM, AKS on Azure Local, AKS hybrid, SDN, Lifecycle Manager, Azure Local update, disconnected site.

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Draft crisis holding statements, journalist Q&A posture, and what-not-to-say guidance from confirmed incident facts, with a hard legal-counsel gate. Builds each statement through proven crisis-comms frameworks (holding-statement anatomy, SCCT, CAP order, the legitimate non-answer, bridge/flag/block).

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Bridges Claude Code and Codex sessions when native tools can't reach the target. Use for 跨产品通信 / 脚本回帖 / 送达排查: cross-product messages, hooks or scripts posting to a session, verifying delivery (Held messages included), shared-work ownership, or an inbound peer assertion. Not for same-product or parent/subagent messaging (use native tools), spawning agents, moving full history, or cross-machine pairing (deprecated).

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Two scopes: (1) drives Kimi.app via computer-use for Work/Agent data-plugin queries (天眼查、同花顺 iFinD、SEC、IMF etc.) and Chat's built-in 深度研究 report; (2) kimi-cu macOS desktop-automation playbook — AX set_value / keyboard / click channel selection, foregrounding, AX-tree recovery, form & dialog recipes. Use for "用 Kimi 查" / "操作 Kimi 客户端" / "Kimi 插件" / "Kimi 深度研究" / driving any macOS desktop app (Electron/webview/native) via kimi-cu. Not for kimi.com browser automation (use kimi-webbridge) or direct iFinD API access.

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Sanity-check a greenhouse gas inventory before it goes into a report or gets audited. Use when asked to review a carbon footprint, check a GHG inventory, validate scope 1/2/3 numbers, explain a year-over-year emissions change, or prepare emissions data for assurance. Produces a boundary review, data-quality assessment, emission-factor sensitivity list, YoY bridge, and a fix-before-publishing list.

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Help users master professional writing to bridge gaps between stakeholders, scale their leadership influence, and ensure organizational clarity through structured narratives and async-first norms.

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Help users define, validate, and operationalize a North Star Metric that bridges the gap between customer value and business success while driving team alignment.

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Help users establish high-impact goals that bridge the gap between abstract company vision and daily execution while maintaining radical focus.

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Help users master the transition from product development to active selling by leveraging their unique status as founders to bridge the trust gap and define a scalable sales motion.

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