「runner」の検索結果

Review generated or changed test code against universal testing rules before it ships. Best used reactively after an agent writes, edits, generates, or refactors tests, before presenting, committing, or merging them. Use for pytest (test_*.py, *_test.py), PHPUnit/Pest (*Test.php), Jest/Vitest (*.test.ts, *.spec.js), Go (*_test.go), files under tests/, __tests__/, or spec/, and review requests like 'write tests for X', 'add tests', 'test this', 'review these tests', or PR diffs containing tests. Can also guide test writing when explicitly invoked before the work. This skill is the quality gate that prevents AI-generated test bloat. DO NOT USE for production or implementation code review (use clean-code-guard), CI or test-runner configuration, running or debugging tests, or general architecture discussion.

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。

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.

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 Euro NCAP test scenarios and variants using the ADT Euro NCAP support package. Use when creating NCAP seed scenarios, generating variants, translating between drivingScenario and RoadRunner, plotting scenario descriptors, computing NCAP scores, or exporting reports. Triggers on: ncapScenario, euroAssessment, getScenario, getScenarioDescriptor, generateVariants, ScenarioDescriptor, ScenarioDescriptorPlot, ncapScore, ncapReport, exportReport, configureVUT, assessmentTable, Euro NCAP, CCRs, CCRm, CCRb, CCFtap, CCCscp, CPNA, CPFA, CBNA, variant generation.

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 driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.

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, test, and deploy applications using GitHub Actions workflows. Create CI/CD pipelines, configure runners, manage secrets, and automate software delivery. Use when working with GitHub repositories, automating builds, running tests, or deploying applications.

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。

Scaffold a first eval suite for an agent: mine real failures into cases, write behavioural checks over traces, and generate the runner. Use when the user wants evals, regression tests for an agent, a golden set, or asks how to know a prompt/model change did not break things. Do NOT use for a single task's done-check (goal-test) or for auditing context (context-audit).

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。

Reference for the `odu` runner — how to invoke a full pipeline, a single recipe, or a platform-pinned node, and how to attach to a live run, from a project whose CI odu runs. Trigger when the user asks to "run CI", "run the pipeline", "re-run a check", to run named lanes or recipes (e.g. "run fmt and nix", "just the e2e lane", bare selectors like `fmt`/`nix`/`e2e`), or names a recipe by `<recipe>@<platform>`. This skill — not a repo's local `just ci` / `just <recipe>` — is how an odu-run request is served.

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, run, debug, and operate applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments that run inside a container with up to 8-hour lifetimes. Triggers on: Lambda MicroVMs, Firecracker isolation, snapshot-resumable compute, suspend/resume, sandboxed or untrusted code execution, AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, isolated security scanners, long-lived sessions, or port-listening servers (gRPC, WebSocket, custom TCP). For standard event-driven Lambda functions, use the aws-lambda skill instead.

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 resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless applications.

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。

Replace text in fillable PDF forms by updating form field values. This skill should be used when users need to update names, addresses, dates, or other text in PDF form fields.

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。

Image processing skill for cropping images to 50% from center and rotating them 90 degrees clockwise. This skill should be used when users request image cropping to center, image rotation, or both operations combined on image files.

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。

Score one piece via eval-runner on six dimensions with a fix list. Many pieces → eval-suite. "score this draft before it ships"

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。

Run the scored pre-publish gate via eval-runner.py: claims, brand voice, compliance, AI tells. "check this before we publish"

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 custom LLM evaluation pipelines using the OpenJudge framework. Covers selecting and configuring graders (LLM-based, function-based, agentic), running batch evaluations with GradingRunner, combining scores with aggregators, applying evaluation strategies (voting, average), auto-generating graders from data, and analyzing results (pairwise win rates, statistics, validation metrics). Use when the user wants to evaluate LLM outputs, compare multiple models, design scoring criteria, or build an automated evaluation system.

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 testing decision trees for GdUnit4: unit vs scene vs CI gates, headless runners, snapshots, and mock networks. Use when choosing test layers, wiring CI, or validating signals/physics without beginner assert catalogs. Keywords: GdUnit4, GdUnitTestSuite, headless CI, snapshot test, mock network, scene integration test, TDD.

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 blueprint for tower defense games (Bloons TD, Kingdom Rush, Fieldrunners) covering wave management, tower targeting logic, path algorithms, economy balance, and mazing mechanics. Use when building TD, lane defense, or tower placement strategy games. Keywords tower defense, wave spawner, pathfinding, targeting priority, mazing, NavigationServer baking.

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。

Crypto market scanner and single-token analyst - movers scans top winners/losers/trending or on-chain runners with pump-risk flags; single-token produces a verdict-first deep report for one token.

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。

Drive Circle Arc Studio from a headless runner. Start one Arc testnet turn, poll it on a later run, and notify when it finishes or needs an answer.

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。

Weekdays. Takes the one card the standup marked next and turns it into a reviewable change on a branch, never a deployment. It reads the project's own rules and docs first, makes the smallest change the card describes, runs that project's own gate, writes a change brief with the rollback in one line, and pushes the branch for the member to merge. It never merges, never deploys, never applies a migration, and never rotates a key.

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。

Monthly, file work only, no browser at all. Re-reads a month of real change outcomes and rewrites the file that decides what the fix runner may change without asking first. A class the member merged unchanged repeatedly widens by exactly one step. A class they edited, closed unmerged, or that regressed narrows immediately. It never touches the outer boundary, which no volume of evidence can widen.

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。

Weekdays, browser only when the card needs one. Takes the next ready cards off the launch board and does the work each one names: stages copy into the dashboard, fills a directory or press form and leaves it open in its tab, verifies a setup, packages a handoff, or researches its own next targets. It ticks its own card the moment it has verified the file that closes it. It submits only where you released the channel, sends only where you released the channel, spends only where you released it, and never touches a credential.

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。

Configure development tools, linting, formatting, and test runners for existing JavaScript projects. Use for ESLint, Prettier, Jest, or equivalent tool setup; defer application implementation and generic project scaffolding.

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。

Dart static analysis, linting, formatting, and code-generation standards. Use only for analysis_options.yaml, build_runner, dart format, DCM, lefthook, or analyze/format CI failures; defer Dart language, null-safety, Flutter tests, and generic CI questions.

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。

Angular CLI usage, code generation, build configuration, and bundle optimization. Use for Angular CLI/build tasks; defer standalone webpack configuration and generic test-runner setup.

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。