「tests」の検索結果

Review a named diff or PR for bugs, regressions, tests, and standards. Use when asked to review code or when a shipping skill needs a review receipt. Use when asked to apply this review's findings locally. Use ce-resolve-pr-feedback for feedback already left on a PR.

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。

Applies this repository's skill-authoring standard as a procedure. Use for any change to, or judgment about, a file under skills/** — a SKILL.md, a reference, a persona prompt, a bundled script's instructions: creating a skill, editing one, reviewing a skill change, or acting on review feedback (human or bot) about one. Not for src/, tests/, or scripts/ code.

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。

Document a solved problem as a durable repo learning. Use when verified work produced non-obvious reasoning absent from its final code, tests, or existing docs; avoid routine fixes whose artifacts already explain the lesson.

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。

Local OpenWork Electron browser automation with CDP. Use when driving a local Electron dev app, browser_list, browser_snapshot, browser_eval, composer automation, or local UI smoke tests.

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。

Automate browser interactions, test web pages and work with Playwright tests.

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。

Verify the OpenSEO MCP server end-to-end on a local dev server — protocol-level correctness against real DataForSEO, then a headless-agent consumer probe that tests tool ergonomics (descriptions, schemas, output size, errors, async flows) without the maintainer manually driving an MCP client. Use after adding or changing MCP tools, or when asked to check that the MCP "works" or "is ergonomic".

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。

Analyze retained NemoClaw CI timings for slow CLI tests, runner queues, or base-image publication.

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。

Triage, diagnose, debug, or fix failing or flaky NemoClaw E2E tests. Trace every assertion and downstream gate before a repair push or rerun. Excludes status-only and dispatch-only requests.

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 whenever you are about to create, push, open, update, or edit a pull request in the Handsontable monorepo – load this BEFORE running `gh pr create` or pushing a feature/docs/fix branch, not only when the user says "PR". Triggers: create/open/submit a PR, push the branch, commit and push, ship it, ready to review, update or fix a PR description, any PR URL, finishing work on a `feature/*`/`docs/*`/`fix/*` branch, or a completed ClickUp/DEV task ready to submit. Covers branch naming, pre-flight lint/tests, the PR-first then changelog flow, `gh auth` fallback, and filling the GitHub PR template.

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 adding or changing a demo the visual regression suite photographs - the Vite-based demo apps in examples/next/visual-tests/<framework>/demo/, the js Navigo router with one /<feature>-demo route per feature, the shared / grid that must stay identical across frameworks, and the sample-data patterns

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 asked to add before/after screenshots of a Lite UI change to a pull request, when a PR touching apps/lite/ui needs its visual change shown, or when extending the screenshot catalogue in apps/lite/e2e/tests/screenshots.spec.ts. Captures both sides locally against seeded fixtures, publishes the surfaces that changed, and posts them to the PR.

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。

Investigates Google Cloud networking issues by analyzing GCP logs, metrics, and diagnostics. Use when investigating dropped network traffic, packet drops, drop reasons, VPC Flow Logs (including Private Service Connect / PSC, serverless / App Engine Direct VPC, and cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics. Don't use for generic VM management or non-observability tasks.

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How to cut a Kortix production release — the versioning philosophy (when patch vs minor vs major) and the exact flow: promote the newest dev SHA with a green Tests run to staging, let the staging PR's checks be the gate, fix forward on dev until it is green, then run Promote to Production and deploy + verify prod. Load WHENEVER the user wants to release, promote, cut/ship a version, publish a release, bump the version, or asks why a promotion is stuck. Load it too whenever another skill or doc needs to describe the release/promotion flow — this file is the one place it is written out in full.

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The pull request loop for this repo: branch → commit → verify in your own box (local tests + local stack) → PR into main → demo video recorded with agent-browser on the local stack → `gh --attach` → self-merge → verify on dev. A PR into main runs no CI unless a person adds the `test` or `preview` label (one run each). Load when opening, updating, or finishing a pull request; when writing a PR body; when asking what CI runs where; when adding or explaining PR labels or the per-PR preview environment; or when attaching an image or video to a PR, issue, or comment.

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, audit, and improve harnesses that make AI coding agents reliable: AGENTS.md/CLAUDE.md instruction files, feature/state tracking, verification gates, scope boundaries, session handoff, memory persistence, context budgets, tool-permission safety, and multi-agent coordination. Use this whenever a coding agent is unreliable across sessions — forgets context, drifts out of scope, claims "done" before tests pass, or starts each session inconsistently — or when creating or assessing AGENTS.md, CLAUDE.md, feature_list.json, init.sh, progress.md, or session-handoff files. Reach for it even if the user never says the word "harness."

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Use for PUA/try-harder productivity coaching when the user expresses frustration, repeated failure, quality complaint, passive behavior, says retry/change approach/don't give up, asks for evidence/completion check/test before done, or wants Ding-style workplace reminders. Triggers include: try harder, stop giving up, figure it out, again??, why still failing, change approach, no evidence, run tests, done without proof, 换个方法, 再试试, 别摆烂, 别偷懒, 为什么还不行, 又错了, 证据呢, 没跑测试别说完成, 验收, 闭环, 自嗨, 置身钉外, 无招, 老板体感. Do not use for calm first-attempt requests.

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Field-tested methodology and concrete recipes for training and operating large-scale LLM/VLM/multi-modal models end to end - choosing and benchmarking accelerators, storage and network; SLURM/Kubernetes orchestration; maximizing training throughput and fitting models in memory; diagnosing and surviving training instabilities, NaN/Inf, and hardware/job failures; checkpointing and fault tolerance; inference performance and memory; debugging multi-node/ multi-GPU hangs; and writing/running tests. Use when the user is training or fine-tuning large models, hits low TFLOPS/MFU, OOM, slow dataloading, a loss spike/divergence, a NCCL/InfiniBand or multi-node hang, node/GPU failures, checkpoint or preemption problems, storage/network bottlenecks, or needs to pick GPUs/cloud/file-systems or size inference latency/throughput. Distilled from "Machine Learning Engineering", the latest version of which can be found at https://github.com/stas00/ml-engineering The latest SKILL.md version can be found at https://github.com/stas00/ml-engineering/blob/master/skills/ml-engineering/SKILL.md

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Persistent world-model harness that stress-tests ideas, strategies, and investments against 11 time horizons from 6 months to 50 years, each a deep analysis of geopolitics, tech, economics, society, and security, in Fast/Standard/Deep tiers. USE WHEN threat model, world model, test idea, future analysis, time horizon, stress test against future, long-term risk. NOT FOR single-shot idea attack (use RedTeam).

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Test LangBot WebUI and core product flows with an automated browser and backend logs. Use when validating the configured LangBot frontend, pipeline Debug Chat, model provider setup and test buttons, bot and knowledge-base UI flows, or troubleshooting failed LangBot end-to-end tests.

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Implement a verdaccio bug fix, feature, or refactor — establish the affected release lines, check whether existing configuration, package-access rules, plugins, or uplink options already solve it, put the change in the layer that owns it, reuse existing helpers, add tests and a changeset, and validate. Use when asked to implement a change in this repository.

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Pre-deployment security audit of Solidity smart contracts in a Foundry project. Combines static analysis (Slither, Aderyn), symbolic execution (Mythril), and property-based testing (forge fuzz + invariant tests with handlers) to catch reentrancy, access-control, oracle/price manipulation, and arithmetic bugs BEFORE deploying to an EVM chain. Also enforces key hygiene (no plaintext private keys, encrypted cast keystore) and a secure deploy workflow. Use when writing, reviewing, testing, or deploying Solidity/Foundry contracts, building a dApp, or working with forge/cast/anvil, MetaMask, or Web3/DeFi code.

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How to build desktop applications with GPUI Kit, the Rust framework published as the gpui-kit crate (GPUI plus gpui_kit::component, gpui_kit::base, gpui_kit::assets). Use when setting up a gpui-kit app, choosing or using a component (Button, Input, Select, Dialog, Sheet, Tabs, Sidebar, List, DataTable, Tree, Chart, etc.), handling component state, theming, or window overlays, and for GPUI mechanics: actions and keybindings, async tasks, contexts, custom elements, entities, events, focus, global state, layout and styling, ElementId, and tests including UI integration testing. Holds the normative Coding Guides: read them before any architecture, state-ownership, public API, naming, or testing decision. Pairs with the gpui-kit-design-guides skill for the Design Guides.

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。

Find and implement evidence-backed simplifications in the ego-lite repository. Use when reviewing the codebase for dead code, duplicated state or APIs, speculative abstractions, unnecessary compatibility layers, hand-written infrastructure, excessive tests or documentation, or when the user asks to reduce code size or maintenance complexity without hiding behavior changes.

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Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.

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。