「invoke」の検索結果

Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.

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Secure AI agents against prompt injection, tool abuse, and data exfiltration with defense-in-depth controls. Use when building, deploying, or hardening agentic AI systems that invoke tools, access data, or interact with production infrastructure.

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。

Clarify requirements before implementing. Do not use automatically, only when invoked explicitly.

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。

Transforms vague prompts into optimized Claude Code prompts. Adds verification, specific context, constraints, and proper phasing. Invoke with /best-practices.

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。

Calibrated interrogation of a fuzzy idea before it becomes a spec. Asks one question at a time, recommends an answer, and lands each answer in §G (goal) or §C (constraints) — unknowns parked as `?` items, never guessed. The cheapest place to kill a bad idea is before §T exists. Triggers when the user has a vague idea, says "grill me", "stress-test this", "challenge my plan", "interview me before I spec", or invokes /ck:grill. Defers the actual write to the spec skill.

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Gather external knowledge the spec needs and distill it into §R — the durable research log — so build grounds in facts instead of hallucinating library behavior. Each finding cites a source; unsourced claims are flagged, never written as fact. Triggers when a spec decision hinges on a library/API/best practice the agent is unsure of, when the user says "research this", "what's the best lib for…", "check current best practice", or invokes /ck:research. Defers the §R write to the spec skill.

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Optional design-improvement pass for when you have spare usage to drain. Finds the shallowest modules in the code the spec touches, researches a deeper design, and proposes refactors that shrink interfaces and hide decisions — behavior held constant, tests green before and after. Proposes §I/§V/§T edits, never silent rewrites. Triggers when the user says "deepen this", "improve the design", "this module feels shallow", "pull complexity down", "use spare budget on the codebase", or invokes /ck:deepen. Leans on the codebase-design skill's deep-module vocabulary when present.

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。

Adversarial senior review of the spec before any code is written. Constructs a skeptical reviewer whose authority comes from the codebase, §R research, and live best-practice — then tries to REFUTE the spec, not rubber-stamp it. Every finding cites evidence (file:line or source); unverifiable ones are flagged. Survivors harden §V; the run ends in an explicit go / no-go gate. Triggers before building anything high-blast-radius, when the user says "review the spec", "red-team this", "is this plan sound", "senior review", or invokes /ck:review.

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。

Read-only drift detector. Diffs SPEC.md against current code and reports violations grouped by severity. Writes nothing — suggests remedies via the spec or build skills but never invokes them. Triggers when the user asks to check drift, audit the spec, verify invariants, or ask whether code still matches the spec. Phrasings: "check drift", "audit the spec", "does the code still match §V", "check invariants", "spec vs code".

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Codify a successful workflow from the current conversation into a permanent project-local skill. After you discover (e.g.) a cold-email sequence that converts, an ad-creative format that beats baseline, or a content-pipeline cadence that compounds — /money-skillify writes it as a SKILL.md under the project's local skills directory so future sessions can re-invoke it without re-discovery. Use when the user says: 'this worked, save it', 'codify this', 'turn this into a skill', '把这个固化下来', '存成 skill'.

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Push the current working tree directly to a GitHub PR whose head lives on a **fork**, without creating a new branch and without pushing to `origin` (which is usually the upstream). Invoke when the user says things like "push straight to PR

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Format reference for Power BI Enhanced Report (PBIR) JSON schemas and patterns. Automatically invoke when the user asks about PBIR JSON structure, visual.json properties, PBIR expressions, objects vs visualContainerObjects, theme inheritance, conditional formatting patterns, extension measures, bookmarks, field references, filter formatting, query roles, PBIR page structure, report wallpaper, or any PBIR metadata format question.

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。

Execute arbitrary Python or PySpark code on Fabric Spark compute without creating a notebook artifact; ephemeral Livy sessions with full Delta table access. Automatically invoke when the user asks to "run PySpark in Fabric", "create a Livy session", "execute Python on Fabric compute", "run Spark without a notebook", "submit code to Fabric", "ephemeral Spark execution", "run ETL in Fabric".

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Query Fabric lakehouse and warehouse data using DuckDB, either locally or inside a Fabric notebook. Automatically invoke when the user mentions "DuckDB", "query Delta tables locally", or asks to "attach DuckDB to a lakehouse", "query OneLake data", "explore lakehouse data", "data freshness check", "validate data quality", "use DuckDB in Fabric".

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Automatically invoke this skill whenever the user asks why a Fabric capacity is busy, throttled, at 90 or 100 percent, or what is consuming CUs; asks for current capacity utilization, carry forward or per-item CU usage; wants to query or repair the Microsoft Fabric Capacity Metrics app or its semantic model; or wants to start, pause or monitor a capacity from a script or status bar.

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Author, validate, and test Power Query M expressions in semantic model partitions. Automatically invoke when the user mentions "Power Query", "M code", "M expression", "partition expression", "query folding", or asks to "write Power Query", "fix Power Query", "test a partition", "preview partition data", "debug Power Query step", "optimize Power Query".

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。

Expert guidance for the Fabric CLI (`fab`) and the Fabric and Power BI REST APIs: workspaces, items, lakehouses, notebooks, pipelines, semantic models, reports, capacities, OneLake, deployment and admin. Also estimates the capacity units (CU) an operation will consume and its impact on the capacity before running it. Automatically invoke whenever the user mentions Fabric, Power BI Service, a Fabric or Power BI workspace, a capacity or F SKU, OneLake, `fab`, or asks to create, run, refresh, schedule, deploy or delete anything in Fabric, including preview items such as Plan, Ontology, Graph or Copilot.

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。

Friendly, jargon-free onboarding for people new to coding agents and Power BI agentic development. Invoke for setup, prerequisites, tool installation, terminal guidance, safety questions, or explanations of models, context, prompts, tools, and environments. Use setup mode for concise installation help, explain mode for guided learning, and improve-my-agent-setup for an existing setup audit.

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Audit and improve an entire agentic-development setup, including skills, context, memory, tools, models, permissions, hooks, workflow habits, and secrets hygiene. Invoke for setup reviews, workflow grading, Goblin Mode, or questions about what to improve. Supports shallow, deep, ultra, and yolo modes. Use domain-specific skills for a single model, report, or tenant.

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。

Automatically invoke this skill whenever the user asks about Fabric tenant settings or Power BI tenant settings or auditing tenant settings. You can use this skill if the user mentions "Fabric administration".

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, validate, publish, and test Power BI paginated reports in the RDL format. Automatically invoke when the user mentions "paginated report", "RDL", ".rdl", "Report Builder", "Power BI Report Builder", "SSRS report", "PBIRS", "Power BI Report Server", or asks to "create a paginated report", "build an invoice/statement report", "make a print-perfect report", "connect a paginated report to a semantic model", "edit an RDL file", "publish an .rdl", or "render a paginated report to PDF/Excel".

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。

TOM and ADOMD.NET guidance via PowerShell for connecting to Power BI Desktop's local Analysis Services instance. Covers model enumeration, DAX queries, metadata modification, annotations, calendar definitions, field parameters, query tracing, DAX library package management (daxlib.org), and the Desktop Bridge for reloading and screenshotting the report canvas. Automatically invoke when the user mentions "Power BI Desktop", "Analysis Services port", "TOM", "ADOMD", "daxlib", "DAX library", "DAX UDF package", or asks to "connect to PBI Desktop", "query PBI Desktop with DAX", "modify PBI Desktop model", "add a measure to PBI", "capture visual queries", "create a field parameter", "validate DAX", "intercept DAX queries", "install daxlib", "add DAX SVG", "add IBCS", "reload the report canvas", "screenshot a report page", "Desktop Bridge", or to work with the model and report in Power BI Desktop together.

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。

Direct TMDL file authoring and BIM-to-TMDL conversion for semantic models in PBIP projects. Automatically invoke when the user asks to "edit TMDL", "add a measure in TMDL", "TMDL syntax", "fix formatString", "fix summarizeBy", "TMDL indentation", "convert BIM to TMDL", "add a column description", "create a calculated column in TMDL", or mentions .tmdl file editing or BIM-to-TMDL migration.

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。

Step-by-step workflow for creating complete Power BI reports from scratch using pbir CLI. Covers model discovery, report creation, page layout, theme setup, visual placement, field binding, filtering, formatting, validation, and publishing. Automatically invoke when the user asks to "create a new report", "build a report from scratch", "make a dashboard", "set up a report with KPIs", "create an executive dashboard", "add pages and visuals to a new report".

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。