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概要と使いどころ
Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh Codex reviewer with no prior context; base output is same-family provisional. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.
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 ML experiment results, compute statistics, generate comparison tables and insights. Use when user says "analyze results", "compare", or needs to interpret experimental 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。
Zero-context verification that every number, comparison, and scope claim in the paper matches raw result files. Uses a fresh cross-model reviewer with NO prior context to prevent confirmation bias. Use when user says "审查论文数据", "check paper claims", "verify numbers", "论文数字核对", or before submission to ensure paper-to-evidence fidelity.
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 a long-form Chinese interview-prep cheat sheet on a specific ML/LLM topic — formulas with derivations, from-scratch PyTorch code, comparison tables, and 25 高频面试题 (L1 必会 / L2 进阶 / L3 顶级 lab). Use when the user says '写面试 cheat sheet', '写一份 X 教程', '帮我准备 Y 面试题', '出一份 X 速查', or wants a 600-1000 line Chinese tutorial on a specific ML topic.
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。
Operate the KubeSphere network extension. Use when Codex needs to install, upgrade, configure, enable, disable, or inspect the `network` extension; manage Calico `IPPool` resources, namespace bindings, migrations, or network isolation flows; or consult the bundled network extension references in this skill.
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。
Research across Notion and synthesize into structured documentation; use when gathering info from multiple Notion sources to produce briefs, comparisons, or reports with citations.
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。
Maintain and validate OpenShell's build-only Windows MSVC lane for x64 and ARM64. Use when working on Windows compilation, `windows:*` mise tasks, unsupported Windows compute-driver contracts, or Windows build reports. This skill does not implement Docker, Kubernetes, Podman, VM, MXC driver, policy translation, MSI, service, or supervisor runtime support on Windows.
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 sandbox security policies from plain-language requirements and optional REST API documentation. Produces L4 or fine-grained L7 network policies and ordered network middleware configuration. Use for API access rules, middleware host selection, failure behavior, or built-in and operator-run middleware attachment. Trigger keywords - generate policy, create policy, update policy, change policy, sandbox policy, network policy, API policy, security policy, allow API, restrict API, network middleware, supervisor middleware.
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 an OpenShell sandbox returns policy_denied, mentions policy.local, or needs a narrow network policy proposal.
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 MNN tests / benchmarks on host or real devices. Covers two parallel tracks — (1) the regression / CI suite (static checks, host-side tests, on-device Android arm64 matrix via ./test.sh + test_stages.json) and (2) one-command iOS real-device LLM benchmarking (prefill/decode tok/s, branch comparison). Use when the user asks to run the tests, run CI, smoke-test a build, verify a change on a device, benchmark on-device (Android or iPhone/iPad), or add / select / retune a test stage.
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。
Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.
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 and publish a self-contained HTML page to Superset, then answer the comments readers pin to it. Use this instead of publishing a Claude artifact whenever the reader is a teammate: a page is listed in the org, every publish mints a version, and pinned comments come back to the agent. Use when the user asks to make or publish a page, turn a report, dashboard, chart, doc, or analysis into a shareable link, update or re-version a page already published, or work through comments left on one, including "make me a page for this", "publish this as a page", "share it as a link", "add a version", "address the comments on that page". Also use it unprompted to offer a page when you finish output a teammate will read: a change or PR walkthrough, a comparison, a report or digest, an incident writeup, or verification screenshots.
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。
Launch, restart, or troubleshoot the real AO Electron desktop app from this repository; run a checkout against isolated or real local AO data; combine PR branches for local UI review; and diagnose stale Electron processes, port conflicts, or preload bridge mismatches. Use whenever asked to run, open, show, or visually verify AO frontend changes in the actual desktop app rather than ao preview, dev:web, or mock 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。
Use when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.
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。
Parses error messages, traces execution flow through stack traces, correlates log entries to identify failure points, and applies systematic hypothesis-driven methodology to isolate and resolve bugs. Use when investigating errors, analyzing stack traces, finding root causes of unexpected behavior, troubleshooting crashes, or performing log analysis, error investigation, or root cause 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。
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X", "what model should I use for", "top models for [task]", "which model runs on my laptop/machine/device", "recommend a model for", "what LLM should I use for", "compare models for", "what's state of the art for", or any question about choosing an AI model for a specific use case. Always use this skill when the user wants model recommendations or comparisons, even if they don't explicitly mention HuggingFace or benchmarks.
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。
AI demos and GPU compute with Gradio Spaces and Hugging Face Spaces ZeroGPU. Use when writing or reviewing code that uses `@spaces.GPU`, configuring `python_version` or `requirements.txt` for a ZeroGPU Space, or handling ZeroGPU-specific code constraints — pickle-based process isolation, `gr.State` semantics across the worker boundary, no `torch.compile` (use AoTI instead), CUDA wheel-only builds (no `nvcc` at build or runtime), large vs xlarge sizing, and dynamic duration callables. Make sure to use this skill whenever the user mentions ZeroGPU, `@spaces.GPU`, or the `spaces` Python package, or hits ZeroGPU-specific code errors like `PicklingError` across the worker boundary, `illegal duration`, or `flash-attn` wheel-build failures — even when the user does not explicitly ask for ZeroGPU coding guidance. Trigger on `import spaces` or `@spaces.GPU` in 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。
Track validated Codex Security findings in Linear, Jira, GitHub issues, or draft GitHub security advisories. Supports issue batches, duplicate checks, and reviewed writes. Do not use for scans or 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。
Triage supplied or imported security findings against a repository using its security policy and static code evidence. Accepts scanner reports, advisories, GitHub findings, and Jira or Linear tickets. Do not use for discovery, duplicate triage, runtime validation, or 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。
Drive Omnigent the way a user does and prove a behavior with recorded evidence, using an isolated server, runner, and mock model plus a feature map of every user entry point. Load before reproducing a user-facing bug, before claiming a fix works, or when reviewing whether a change covered every surface (session vs. new-session composer, terminal strip vs. agent terminal, all twelve native harnesses). Covers the web UI, native harness terminals, and the CLI.
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 Omnigent CLI's setup/onboarding flow, terminal UI/UX, and critical user journeys in a completely isolated, reproducible loop. Drives the real `omnigent` binary through a PTY (pexpect) inside a throwaway OMNIGENT_CONFIG_HOME / OMNIGENT_DATA_DIR sandbox that never touches the user's real ~/.omnigent, captures ANSI-stripped frames for UX inspection, and proves a change is verifiable via a before→fix→after baseline diff. Load when developing or reviewing a CLI setup/onboarding/REPL/picker change (omnigent/cli.py, omnigent/onboarding/*, omnigent/repl/*, scripts/install_oss.sh), reproducing a cold-start/first-run UX bug, or confirming a fix actually lands. Several agents can run it concurrently on separate worktrees.
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。
Manage GSD workspaces — create, list, or remove isolated workspace environments
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 self-contained HTML visual explanations for systems, code changes, plans, data, and technical concepts. Use for diagrams, architecture overviews, diff or plan reviews, project recaps, comparison tables, slide decks, animated explainers, narrated MP4 videos, and other visual explanations.
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。
Professor's review queue — student output waits here for professor approval before going to clients or courts. Only active if "formal review queue" supervision style was chosen at setup; otherwise dormant. Use when the professor wants to see what's waiting for review, approve, edit-then-approve, or return an item.
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。