「dq」の検索結果

Think and work like an expert Health Informatician. Use when a task calls for Health Informatician judgment. Reasons from semantic interoperability, provenance, and patient safety through FHIR/US Core, SNOMED-LOINC-RxNorm terminology mapping, OMOP/OHDSI ETL with DQD/Achilles, and chart-review PPV validation while treating immortal-time and confounding-by-indication bias, patient-matching/MPI failures, billing-code phenotypes, and vocabulary version drift as first-class failure modes.

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Think and work like an expert Energy Storage / Battery Scientist. Use when a task calls for Energy Storage / Battery Scientist judgment. Reasons from interfacial thermodynamics, ion transport, SEI/CEI dynamics, and cell engineering constraints (N/P and E/S ratio, mass loading) through galvanostatic cycling, dQ/dV, GITT and EIS/DRT, operando XRD, and PyBaMM/Newman models, while treating Li plating, lithium-inventory loss, transition-metal crossover, and coin-cell artifacts as first-class failure modes.

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Think and work like an expert Electric Machines Engineer. Use when a task calls for Electric Machines Engineer judgment. Reasons from magnetic circuit design, dq-frame machine models, FEM flux paths, and drive efficiency maps while treating saturation, cogging, thermal derating, and inverter harmonics as first-class failure modes.

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Think and work like an expert Ecologist. Use when a task calls for Ecologist judgment. Reasons from Preston/Fisher SADs and Hutchinson fundamental vs realized niches; designs quadrat/transect and distance/occupancy surveys; filters GBIF issue flags and iNaturalist DQA; fits vegan/iNEXT/unmarked GLMMs with Moran's I and nlme/glmmTMB spatial correlation while treating pseudoreplication, effort bias, and citizen-science artifacts as first-class failure modes.

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Coordinates fundraising execution with PPM preparation, DDQ completion, legal documentation, and closing mechanics. Use when managing fund launches, coordinating formation processes, or tracking fundraising milestones.

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Doctrine ORM best practices for Symfony: entity mapping as source of truth, repositories, DQL/QueryBuilder with parameters, N+1 prevention with fetch joins, relations (cascade/fetch/orphanRemoval), lifecycle events, batch processing, and generated migrations. Apply when: writing or reviewing Doctrine entities, repositories, and queries. Activated automatically by symfony-plugin/stack.md as a convention skill for the development and database phases. Do NOT use this skill for: - PHP language idioms — see php-foundation:php-conventions. - Controllers/services/forms — see symfony-plugin:symfony-conventions.

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用户咨询腾讯云产品资源、AWS、阿里云等多云资源时，查看智能顾问架构图、架构目录、架构详情、架构评估结果、绘制架构图、开通智能顾问时、AI智能巡检、AI容量监测、AI混沌演练、AI云诊断、主动预警、架构健康度、云运维问答、云资源查询、云成本优化、安全合规、云资源盘点、闲置资源检查、云产品最佳实践等AIOps、ChatOps、CloudOps操作时使用。

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Triage the Gaia issue backlog and skill-batch intake queue. Use this skill when someone asks to: "triage issues", "clean up the issue tracker", "review the backlog", "close stale issues", "process the intake queue", "review skill-batches", "evaluate draft skill proposals", "approve or reject pending skills", "is this issue still valid?", "what's clogging the backlog?", "run a triage pass", or /gaia-triage. Covers two workstreams: (1) GitHub issue lifecycle — identifying resolved, stale, or need-more-info issues and acting on them via gh CLI; (2) skill-batch intake — evaluating draft proposals in registry-for-review/skill-batches/ and routing them toward promotion or rejection. This is the gatekeeping step before new skills enter the canonical registry; and (3) a cross-repo triage sweep — sizing, P0-P4 prioritization, umbrella/epic synthesis, and assignment across every gaia-research org repo, on the one headquarters tracker.

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Chart a too-big effort as a shared map of decision tickets on the Gaia headquarters issue tracker, then resolve them one at a time until the way to the destination is clear. Use when someone says: "this is too big for one session", "chart a map", "wayfinder map", "plan this effort", "what do we need to decide first", "open a wayfinder", "work the map", "what's on the frontier", or /wayfinder. Covers any gaia-research org repo — gaia-skill-tree, gaia-research, gaia-skill-heaven and beyond — but every map and every ticket lives on ONE tracker: gaia-research/gaia-skill-tree. This is cartography (planning an effort as decisions), NOT triage of an existing backlog — for that use /gaia-triage.

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End-to-end plan → implement → review pipeline that takes one triaged Gaia issue to a merged-ready PR, with Kill Criteria on the issue and zero follow-up debt. Use when someone says: "resolve this issue", "take #N end-to-end", "work the P0 queue", "fix and ship this issue", "run the resolver", "close out this issue properly", or /gaia-issue-resolver. Works any gaia-research org repo — gaia-skill-tree, gaia-research, gaia-skill-heaven — while the issue itself lives on the headquarters tracker, gaia-research/gaia-skill-tree. Assumes the issue is already triaged and carries a P0–P4 label; if it does not, run /gaia-triage first.

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Use when configuring standard Salesforce Quotes, building quote templates for PDF generation, emailing quotes, syncing quotes to opportunity products, or setting up discount approvals on quotes. Triggers: 'create quote', 'quote template', 'quote PDF', 'email quote', 'quote sync', 'synced quote', 'discount approval', 'quote line items', 'QuoteSettings', 'enableQuote', 'QuoteStatus', 'allowEmail', 'SyncedQuoteId', 'IsSyncing', 'QuoteLineItem', 'QuoteDocument', 'GrandTotal', 'Pricebook2Id'. NOT for CPQ (SBQQ) quote templates — use admin/cpq-quote-templates. NOT for the end-to-end quote-to-cash process — use admin/quote-to-cash-requirements.

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Firmware development for the 38-pin ESP32-WROOM-32 development board — Espressif ESP32-DevKitC V4, Ai-Thinker NodeMCU-32S, DOIT ESP32 DevKit V1 38-pin and their CH340/CP2102 clones, 19 pins per side, with GPIO0 and the six in-package flash pins (GPIO6-11, labelled D0 D1 D2 D3 CMD CLK or SD0-SD3) broken out. Use when working on a 38-pin ESP32 devkit (ESP32-D0WDQ6 / ESP32-D0WD-V3, ESP-WROOM-32 or ESP32-WROVER module): project setup, platformio.ini and sdkconfig for ESP-IDF or Arduino, pin mapping and which GPIOs are safe, the flash-pin and IO0 traps, WROVER GPIO16/17 PSRAM conflict, strapping pins, ADC1 vs ADC2 with Wi-Fi, SPI speed and IO_MUX pins, deep sleep and RTC wake pins, flashing, BOOT/EN recovery, brownouts, or debugging why something on the board does not work.

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Firmware development for the 30-pin ESP32-WROOM-32 development board — the DOIT ESP32 DevKit V1 / ESP32 CH340 Type-C / NodeMCU-ESP32 30-pin form factor, 15 pins per side, CH340G or CP2102 USB-UART bridge, AMS1117 LDO, user LED on GPIO2. Use when working on a 30-pin ESP32 devkit (ESP32-D0WDQ6 / ESP32-D0WD-V3, ESP-WROOM-32 module): project setup, platformio.ini and sdkconfig for ESP-IDF or Arduino, pin mapping and which GPIOs are safe, strapping pins, ADC1 vs ADC2 with Wi-Fi, SPI speed and IO_MUX pins, I2C, deep sleep and RTC wake pins, flashing over the CH340 bridge, BOOT/EN recovery, brownouts, or debugging why something on the board does not work.

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Firmware development for the 36-pin ESP32-WROOM-32 development board — the original DOIT ESP32 DevKit V1 with 18 pins per side, i.e. the 30-pin layout plus the six in-package flash pins (SD0 SD1 SD2 SD3 CMD CLK = GPIO6-11) broken out at the USB end, CH340G or CP2102 bridge, AMS1117 LDO, user LED on GPIO2, GPIO0 not on the header. Use when working on a 36-pin ESP32 devkit (ESP32-D0WDQ6 / ESP32-D0WD-V3, ESP-WROOM-32 module), or when identifying which ESP32 board size you have: project setup, platformio.ini and sdkconfig for ESP-IDF or Arduino, pin mapping and which GPIOs are safe, the flash-pin trap, strapping pins, ADC1 vs ADC2 with Wi-Fi, SPI speed and IO_MUX pins, deep sleep and RTC wake pins, flashing, BOOT/EN recovery, brownouts, or debugging why something on the board does not work.

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Audit a dataset or access rule before it joins an identity-graph build (access rules behave like datasets in NQL here). Enumerates failure modes (hub identifiers, high-degree nodes, suspicious values, over-connected identifiers), tests hypotheses in parallel, quantifies damage by rows / edges / entities, and proposes minimal filters ranked by severity. When issues are found, returns a validated `CREATE MATERIALIZED VIEW` NQL the caller can run to produce a graph-ready clean source; if the data passes, says so and recommends it unchanged. Plans and authors the clean-view NQL; does not execute it. Use when: "audit this dataset before the graph build", "find bad edges in <source>", "check identity data quality", "recommend filters for the graph build", "quantify damage from <identifier_type>", "pre-graph DQ". (narrative-identity)

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Professional resume builder and personalizer. Use this skill when the user wants to create a new resume, update their existing one, or tailor a resume for a specific job description (ATS-friendly).

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Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API. Use for standard RL experiments, quick prototyping, and well-documented algorithm implementations. Best for single-agent RL with Gymnasium environments. For high-performance parallel training, multi-agent systems, or custom vectorized environments, use pufferlib instead.

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Sistema completo de due diligence para transacciones M&A en España. Abarca análisis jurídico (mercantil, regulatorio, compliance), fiscal (CIT, IVA, retenciones, facturación electrónica) y medioambiental (licencias, pasivos, responsabilidad). Incluye matrices de riesgo cuantitativas, workflows de ejecución, templates de informes y referencias normativas BOE/UE/ISO actualizadas. Úsalo cuando el usuario solicite due diligence en España, análisis de riesgos transaccionales, evaluación pre-adquisición o auditoría de cumplimiento normativo para share deals o asset deals.

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Use this skill to understand record retention requirements for currently-employed drivers. Covers DQF, HOS, vehicle records, and D&A specific periods.

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Use this skill when re-hiring a driver who has been away from CMV operation for 1+ years. Covers re-qualification, refresh of medical and MVR, and whether prior employer inquiries restart.

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Use this skill when the user asks about onboarding a new CDL driver — pre-hire process, day-zero requirements, application + DQF setup, road test, drug & alcohol pre-employment, Clearinghouse Full query, MVR initial pull, PSP report, ELDT verification, sequence of activities + timing, and what NOT to do (handing keys before testing complete). Cite 49 CFR 391, 382.

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。