「mission」の検索結果

Debug AEM Workflow issues on AEM as a Cloud Service — stuck workflows, failed steps, missing Inbox tasks, launcher failures, stale instances, thread pool exhaustion, queue backlogs, purge failures, and permissions errors. Use when the user reports workflow problems on Cloud Service, asks why a workflow is stuck or failed, needs step-by-step troubleshooting, or provides thread dumps, configuration status output, or Sling Job console output for 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。

Publish, deactivate, and delete AEM content programmatically via the Cloud Service Replication API (com.day.cq.replication). Covers single-path and bulk activation, preview-tier targeting with AgentFilter, synchronous/async options, ReplicationStatus checks, permission validation, workflow process steps, and replication event handling. Use when the user needs to publish pages, activate or deactivate content, check replication status, build workflow steps that replicate content, listen to replication events, query batch publication state, or work with Replicator, ReplicationOptions, or ReplicationStatusProvider in AEM Cloud Service.

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 comprehensive admin documentation for AEM Edge Delivery Services project handover. Creates admin guide covering Config Service setup, permissions, access control, Admin API operations, cache management, and code sync. Use for "admin guide", "admin documentation", "admin handover".

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。

You extend the browser to give users superpowers. You understand the unique constraints of extension development - permissions, security, store policies. You build extensions that people install and actually use daily. You know the difference between a toy and a tool.

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。

Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small gotchas that distinguish reproducible matplotlib from notebook scratch. Use when producing publication figures in Python — RNA-seq scatter, single-cell embeddings, generic biological plotting.

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。

Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.

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。

Build interactive HTML/web visualizations with plotly (Python/R), bokeh (Python), and gganimate/plotly frames for animation, with awareness of current Kaleido static-export model (post-orca-EOL), HTML file-size bloat, and the limits of interactive-only output for journal submission. Use when producing zoomable/hoverable plots for notebook EDA, supplementary HTML, dashboards, or animated time-course / iteration visualizations.

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。

Prepares statistical reports for clinical trials following CONSORT 2025, SPIRIT 2025, ICH E9(R1) estimands, and FDA 2023 covariate adjustment guidance. Covers Table 1 generation, analysis populations (ITT/FAS/PP/Safety), the 5 ICH E9(R1) intercurrent-event strategies, MMRM under MAR (mmrm), reference-based MI (rbmi J2R/CR/CIR), Permutt tipping-point sensitivity, and Rubin's-rules vs frequentist variance debate. Use when preparing regulatory submissions, defining estimands, or implementing missing-data sensitivity analyses.

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 subgroup and heterogeneous treatment effect (HTE) analyses for clinical trials. Covers Mantel-Haenszel pooling, Breslow-Day, interaction tests in regression, RERI for additive interaction, modern data-adaptive HTE methods (STEPP, SIDES, causal forests, X/R-learners), Bayesian shrinkage (Dixon-Simon, MAP, EXNEX), graphical multiplicity (Bretz-Maurer), and credibility frameworks (Sun BMJ, EMA 2019). Use when analyzing treatment effects across patient subgroups for regulatory submissions or precision-medicine claims.

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。

Implements missing-data sensitivity analyses for confirmatory clinical trials including MMRM under MAR (with Kenward-Roger correction), reference-based multiple imputation (J2R, CR, CIR, LMCF per Carpenter-Roger 2013), Permutt delta-adjustment / tipping-point analysis, pattern-mixture identifying restrictions (CCMV, NCMV, ACMV), and the Cro vs Bartlett variance debate. Use when handling missing primary or secondary endpoint data in regulatory submissions following NRC 2010 and ICH E9(R1).

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。

Reads, validates, and prepares CDISC SDTM and ADaM clinical trial data for analysis. Covers SDTM domain joins (DM, AE, EX, VS, LB, DS), ADaM architecture (ADSL, BDS, OCCDS, ADTTE) with traceability, treatment-emergent AE conventions, baseline derivation, SUPPQUAL/NSV handling, Define-XML 2.1, and Pinnacle 21 / CORE validation. Use when working with clinical trial datasets in CDISC SDTM/ADaM format, preparing analysis-ready data, or validating for regulatory submission.

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 a carrier asks how to spec a new tractor — engine choice (X15 vs DD16 vs PACCAR MX), transmission (manual vs automated manual vs automatic), axle ratio, sleeper size, fuel tanks, aerodynamic options, electronic features, warranty, fleet-spec vs premium-spec tradeoffs, and how spec choices affect resale 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。

Use this skill when the user asks about CMV oilfield operations — the 24-hour restart exemption (49 CFR 395.1(d)), oilfield-specific HOS rules, hot oil hauling, specialty equipment (winch trucks, kill trucks, frac sand haulers, water haulers), Texas Railroad Commission permitting, oilfield insurance specifics, and how oilfield operations differ from standard OTR trucking. Cite 49 CFR 395.1(d).

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 this skill when the user asks about towing + recovery operations — separate FMCSA authority class, light-duty vs medium-duty vs heavy-duty wrecker rules, AAA + AAA-Plus contracts, Roadside-Assistance (RA) operations, "non-consensual tow" rules + state-by-state, and how towing operations differ from general freight. Reference state Public Utility Commission + 49 CFR 395 application.

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 this skill when the user asks the difference between a freight broker, freight forwarder, and motor carrier (49 CFR 371 + 373) — required authority for each, bond requirements (BMC-84 broker bond, BMC-85 freight forwarder bond), broker-carrier agreements, factoring + commissions, double brokering, and how to identify each role on a Bill of Lading. Cite 49 CFR 371 + 373.

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 this skill to respond to an FMCSA audit document request efficiently. Covers organization, file labeling, secure transmission.

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 this skill to ensure driver hiring practices comply with Equal Employment Opportunity Commission requirements. Covers Title VII, disability, age, and pregnancy.

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。

Bing Webmaster Tools + IndexNow extension. Microsoft Copilot citations are fed by the Bing index; this skill makes Bing visibility, link data, and IndexNow URL submission first-class.

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。

Decision-ready scouting record for a user-connected provider access campaign. Use when an assigned Provider Access Launch task needs its easiest official route, minimum scopes, cost, account needs, approval path, implementation consumer, and easy-execute verdict established before submission. NOT for client Local Listings distribution.

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。

Pattern Patrols system of recurring, certified sweeps. Use when you are a patrol run or an assignment names a P# id, you spot a registered-pattern violation off-mission (log a sighting), a mistake class keeps recurring, or you touch PATROL_REGISTRY or PATROL_SIGHTINGS. NOT for one-off bug fixes.

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。

Bringing an existing table onto the platform base standard. Use when asked to canonicalize, retrofit, or 'Wave 3' a table, run apply_rls or an org backfill, retire a bespoke *_versions table, or move it onto platform comments/associations/permissions. NOT for a schema move (use db-move-table-schema).

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。

Comprehensive toolkit for writing high-quality computer science research papers (conference, journal, thesis). Provides narrative construction guidance, sentence-level clarity principles (Gopen & Swan), academic phrasebank, CS-specific conventions, and section-by-section quality checklists. Use when assisting with academic paper writing, revision, or structure planning across all stages from drafting to submission.

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。

When the user needs to integrate multiple data sources (Canvas API, user memory, file systems) to create comprehensive academic reports. This skill combines course information, assignment details, submission status, and user context to generate actionable insights. Triggers include requests that involve cross-referencing multiple data sources or creating consolidated academic reports from disparate systems.

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。

End-to-end pipeline for writing ML/AI research papers — from experiment design through analysis, drafting, revision, and submission. Covers NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Integrates automated experiment monitoring, statistical analysis, iterative writing, and citation verification.

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。