[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M7CSJWPRKE6H4P28F0J4JS3W":3,"skill-same:01M7CSJWPRKE6H4P28F0J4JS3W":106},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":19,"linkOnly":20,"markdownContent":21,"markdownBody":22,"frontMatter":23,"refName":27,"commitSha":28,"skillDirectory":29,"forksCount":30,"repositoryHtmlUrl":31,"repositoryHomepageUrl":32,"ownerHtmlUrl":33,"ownerBlogUrl":6,"ownerDescription":34,"updatedAt":35,"install":36,"resources":49},"01M7CSJWPRKE6H4P28F0J4JS3W","nemo-evaluator-plugin",null,"Use when working on the Evaluator plugin CLI, jobs, SDK-backed specs, metric types, or plugin-owned Evaluator skills.","YYC-Cube\u002FYYC3-Knowledge-Base","YYC-Cube","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235006543?v=4","01M79J2PH4SWD2X0825X6PN748","yyc3","01M79J2PHVK3F6ZBYT8K2SCZCW",1,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fskills\u002Fnemo-evaluator-plugin\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: nemo-evaluator-plugin\ndescription: Use when working on the Evaluator plugin CLI, jobs, SDK-backed specs, metric types, or plugin-owned Evaluator skills.\nmetadata:\n  owner: nemo-platform\n  maturity: active\nlicense: Apache-2.0\n---\n\n# Evaluator Plugin\n\nUse this skill for evaluation tasks against a running NeMo Platform server. The plugin-backed CLI interface is `nemo evaluator`; the legacy generated `nemo evaluation` API command group is not the target surface for new guidance.\n\n## CLI Interface\n\n### Prerequisites\n\n- all commands in this file assume that the shell's working dir is at the root of the Nvidia-NeMo\u002Fnemo-platform repo\n- activate the Python virtual environment before invoking the `nemo` CLI: `source .venv\u002Fbin\u002Factivate`\n\nCheck plugin status from the CLI:\n\n```bash\nnemo evaluator info\n```\n\n## Metric Types\n\n### Explore Available Metrics\n\nTo view available metric names, run:\n\n```bash\nnemo evaluator metric-types\n```\n\nTo view a specific metric schema, pass a metric name from the `metric_types` list above:\n\n```bash\nnemo evaluator metric-types \u003Cmetric-name>\n```\n\nInspect all the registered metric schema contracts:\n\n```bash\nnemo evaluator evaluate explain\n```\n\n> Note: use `nemo evaluator evaluate explain` as the source of truth for the current plugin input schema. It will return a large json schema response, so strongly prefer `nemo evaluator metric-types` when you only need metric names and corresponding schemas.\n\n## Evaluation Spec\n\nEvaluation spec is a payload that is provided to CLI as an input to execute evaluation.\n\nAt a high level, a spec describes:\n\n- `metrics`: bundled Evaluator SDK metric configurations\n- `dataset`: inline rows to evaluate or platform FilesetRef that contains the dataset\n- `params`: optional Evaluator SDK execution parameters\n- `target`: optional model or agent target for online evaluation\n\nSee the LLM-judge spec example at [assets\u002Fspecs\u002Fllm_as_judge.json](.\u002Fassets\u002Fspecs\u002Fllm_as_judge.json).\n\n### Metric Bundle Payloads\n\nThe checked-in [spec examples](.\u002Fassets\u002Fspecs) use bundled SDK metrics. The fields under `metrics[*].payload` are generated by `bundle_metric(metric, CloudpickleMetricBundlePackager())`.\n\nTo see the pattern for configuring a pre-defined SDK metric, for example `ExactMatchMetric`, and converting it into bundled metric JSON, inspect `build_metric_bundle_example()` in [generate_example_specs.py](.\u002Fscripts\u002Fgenerate_example_specs.py) and run:\n\n```bash\nuv run --frozen python skills\u002Fnemo-evaluator-plugin\u002Fscripts\u002Fgenerate_example_specs.py\n```\n\n## Run Evaluations\n\n### Run Using File Spec Reference\n\nWhen using the `nemo evaluator evaluate run` command, results are saved into local temporary directories and the link is printed to stdout.\nPrefer the `--spec-file` named argument over inline shell JSON because metric bundles include serialized payloads.\nExamples of various specs are provided in the [assets\u002Fspecs](.\u002Fassets\u002Fspecs\u002F) directory.\n\n#### Evaluate using `exact-match` metric\n\nSee the spec example at [assets\u002Fspecs\u002Fexact_match_metric.json](.\u002Fassets\u002Fspecs\u002Fexact_match_metric.json).\n\n```bash\nnemo evaluator evaluate run --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fexact_match_metric.json\n```\n\n#### Evaluate using a benchmark metric set\n\n```bash\nnemo evaluator evaluate run --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fexact_match_benchmark.json\n```\n\n#### Evaluate using `LLM-Judge` metric\n\nUses an LLM to score responses. See the spec example at [assets\u002Fspecs\u002Fllm_as_judge.json](.\u002Fassets\u002Fspecs\u002Fllm_as_judge.json).\n\n```bash\nnemo evaluator evaluate run --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fllm_as_judge.json\n```\n\n### Run Evaluation As A Durable Job\n\nUse the `nemo evaluator evaluate submit` command to create a durable evaluation job. The response of this command returns a job handler object instead of the evaluation result.\n\n```bash\nnemo evaluator evaluate submit \\\n  --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fexact_match_metric.json\n```\n\nThe submit response includes the generated job's `name` field, for example `nemo-evaluator-zlhn1ecd`. Wait for the job to complete, then list and download the job results.\n\n```bash\nnemo jobs get-status \u003Cjob-name>\nnemo jobs get \u003Cjob-name>\nnemo jobs results list \u003Cjob-name>\nnemo jobs results download aggregate-scores --job \u003Cjob-name> --output-file aggregate-scores.json\nnemo jobs results download row-scores --job \u003Cjob-name> --output-file row-scores.jsonl\n```\n\n## Python SDK Interface\n\nEvaluator Python SDK client is exposed as `evaluator` variable on `NeMoPlatform` instance:\n\n```python\nfrom nemo_platform import NeMoPlatform\n\nplatform_client = NeMoPlatform(base_url=\"http:\u002F\u002Flocalhost:8080\")\nstatus = platform_client.evaluator.plugin_status()\n```\n\nSee examples of using the plugin SDK interface in [plugin_sdk_examples.py](.\u002Fassets\u002Fexamples\u002Fplugin_sdk_examples.py).\n\n## Security\nMake sure not to print any secrets to stdout since this can be collected as logs\n\n## Additional Resources\n\nFor LLM-judge setup notes, see [LLM Judge Notes](references\u002Fllm-judge.md).\n\nFor evaluator API key auth, see [Evaluator API Auth](references\u002Fapi-auth.md).\n\nFor local and cluster troubleshooting, see [Evaluation Troubleshooting](references\u002Ftroubleshooting.md).\n","# Evaluator Plugin\n\nUse this skill for evaluation tasks against a running NeMo Platform server. The plugin-backed CLI interface is `nemo evaluator`; the legacy generated `nemo evaluation` API command group is not the target surface for new guidance.\n\n## CLI Interface\n\n### Prerequisites\n\n- all commands in this file assume that the shell's working dir is at the root of the Nvidia-NeMo\u002Fnemo-platform repo\n- activate the Python virtual environment before invoking the `nemo` CLI: `source .venv\u002Fbin\u002Factivate`\n\nCheck plugin status from the CLI:\n\n```bash\nnemo evaluator info\n```\n\n## Metric Types\n\n### Explore Available Metrics\n\nTo view available metric names, run:\n\n```bash\nnemo evaluator metric-types\n```\n\nTo view a specific metric schema, pass a metric name from the `metric_types` list above:\n\n```bash\nnemo evaluator metric-types \u003Cmetric-name>\n```\n\nInspect all the registered metric schema contracts:\n\n```bash\nnemo evaluator evaluate explain\n```\n\n> Note: use `nemo evaluator evaluate explain` as the source of truth for the current plugin input schema. It will return a large json schema response, so strongly prefer `nemo evaluator metric-types` when you only need metric names and corresponding schemas.\n\n## Evaluation Spec\n\nEvaluation spec is a payload that is provided to CLI as an input to execute evaluation.\n\nAt a high level, a spec describes:\n\n- `metrics`: bundled Evaluator SDK metric configurations\n- `dataset`: inline rows to evaluate or platform FilesetRef that contains the dataset\n- `params`: optional Evaluator SDK execution parameters\n- `target`: optional model or agent target for online evaluation\n\nSee the LLM-judge spec example at [assets\u002Fspecs\u002Fllm_as_judge.json](.\u002Fassets\u002Fspecs\u002Fllm_as_judge.json).\n\n### Metric Bundle Payloads\n\nThe checked-in [spec examples](.\u002Fassets\u002Fspecs) use bundled SDK metrics. The fields under `metrics[*].payload` are generated by `bundle_metric(metric, CloudpickleMetricBundlePackager())`.\n\nTo see the pattern for configuring a pre-defined SDK metric, for example `ExactMatchMetric`, and converting it into bundled metric JSON, inspect `build_metric_bundle_example()` in [generate_example_specs.py](.\u002Fscripts\u002Fgenerate_example_specs.py) and run:\n\n```bash\nuv run --frozen python skills\u002Fnemo-evaluator-plugin\u002Fscripts\u002Fgenerate_example_specs.py\n```\n\n## Run Evaluations\n\n### Run Using File Spec Reference\n\nWhen using the `nemo evaluator evaluate run` command, results are saved into local temporary directories and the link is printed to stdout.\nPrefer the `--spec-file` named argument over inline shell JSON because metric bundles include serialized payloads.\nExamples of various specs are provided in the [assets\u002Fspecs](.\u002Fassets\u002Fspecs\u002F) directory.\n\n#### Evaluate using `exact-match` metric\n\nSee the spec example at [assets\u002Fspecs\u002Fexact_match_metric.json](.\u002Fassets\u002Fspecs\u002Fexact_match_metric.json).\n\n```bash\nnemo evaluator evaluate run --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fexact_match_metric.json\n```\n\n#### Evaluate using a benchmark metric set\n\n```bash\nnemo evaluator evaluate run --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fexact_match_benchmark.json\n```\n\n#### Evaluate using `LLM-Judge` metric\n\nUses an LLM to score responses. See the spec example at [assets\u002Fspecs\u002Fllm_as_judge.json](.\u002Fassets\u002Fspecs\u002Fllm_as_judge.json).\n\n```bash\nnemo evaluator evaluate run --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fllm_as_judge.json\n```\n\n### Run Evaluation As A Durable Job\n\nUse the `nemo evaluator evaluate submit` command to create a durable evaluation job. The response of this command returns a job handler object instead of the evaluation result.\n\n```bash\nnemo evaluator evaluate submit \\\n  --spec-file skills\u002Fnemo-evaluator-plugin\u002Fassets\u002Fspecs\u002Fexact_match_metric.json\n```\n\nThe submit response includes the generated job's `name` field, for example `nemo-evaluator-zlhn1ecd`. Wait for the job to complete, then list and download the job results.\n\n```bash\nnemo jobs get-status \u003Cjob-name>\nnemo jobs get \u003Cjob-name>\nnemo jobs results list \u003Cjob-name>\nnemo jobs results download aggregate-scores --job \u003Cjob-name> --output-file aggregate-scores.json\nnemo jobs results download row-scores --job \u003Cjob-name> --output-file row-scores.jsonl\n```\n\n## Python SDK Interface\n\nEvaluator Python SDK client is exposed as `evaluator` variable on `NeMoPlatform` instance:\n\n```python\nfrom nemo_platform import NeMoPlatform\n\nplatform_client = NeMoPlatform(base_url=\"http:\u002F\u002Flocalhost:8080\")\nstatus = platform_client.evaluator.plugin_status()\n```\n\nSee examples of using the plugin SDK interface in [plugin_sdk_examples.py](.\u002Fassets\u002Fexamples\u002Fplugin_sdk_examples.py).\n\n## Security\nMake sure not to print any secrets to stdout since this can be collected as logs\n\n## Additional Resources\n\nFor LLM-judge setup notes, see [LLM Judge Notes](references\u002Fllm-judge.md).\n\nFor evaluator API key auth, see [Evaluator API Auth](references\u002Fapi-auth.md).\n\nFor local and cluster troubleshooting, see [Evaluation Troubleshooting](references\u002Ftroubleshooting.md).\n",{"name":5,"license":15,"metadata":24,"description":7},{"owner":25,"maturity":26},"nemo-platform","active","main","87afe6ce96220accf50a345dea46784c8c9f210e","YYC3-Skills-技能包\u002FYYC3-Skills-技能包-skills\u002Fskills\u002Fnemo-evaluator-plugin",0,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base","https:\u002F\u002Fkb.yyc3.top\u002F","https:\u002F\u002Fgithub.com\u002FYYC-Cube","万象归元于云枢 | 深栈智启新纪元","2026-11-10 10:37:32",{"source":8,"skillName":5,"commands":37,"prompt":47,"zipAvailable":48},[38,41,44],{"tool":39,"command":40},"npx","npx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill nemo-evaluator-plugin",{"tool":42,"command":43},"bunx","bunx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill 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Triggers include \"Vercel Sandbox browser\", \"microVM Chrome\", \"agent-browser in sandbox\", \"browser automation on Vercel\", or any task requiring Chrome in a Vercel Sandbox.","MIT","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fvercel-sandbox\u002FSKILL.md",[],[],{"skillNo":116,"name":117,"nameZh":6,"description":118,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":119,"categories":120,"keywords":121,"publishedAt":19},"01M7CTD8D2BNJY54S65M47HEJA","slack","Interact with Slack workspaces using browser automation. Use when the user needs to check unread channels, navigate Slack, send messages, extract data, find information, search conversations, or automate any Slack task. Triggers include \"check my Slack\", \"what channels have unreads\", \"send a message to\", \"search Slack for\", \"extract from Slack\", \"find who said\", or any task requiring programmatic Slack interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fslack\u002FSKILL.md",[],[],{"skillNo":123,"name":124,"nameZh":6,"description":125,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":126,"categories":127,"keywords":128,"publishedAt":19},"01M7CTCSSB8ZP3Q58C3YZDZK1W","electron","Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include \"automate Slack app\", \"control VS Code\", \"interact with Discord app\", \"test this Electron app\", \"connect to desktop app\", or any task requiring automation of a native Electron application.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Felectron\u002FSKILL.md",[],[],{"skillNo":130,"name":131,"nameZh":6,"description":132,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":133,"categories":134,"keywords":135,"publishedAt":19},"01M7CTCBJY76688V4DCZGWFHGQ","dogfood","Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to \"dogfood\", \"QA\", \"exploratory test\", \"find issues\", \"bug hunt\", \"test this app\u002Fsite\u002Fplatform\", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fdogfood\u002FSKILL.md",[],[],{"skillNo":137,"name":138,"nameZh":6,"description":139,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":140,"categories":141,"keywords":142,"publishedAt":19},"01M7CTC4H0FFGVEAQR9PA4GA1A","agent-browser","Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to \"open a website\", \"fill out a form\", \"click a button\", \"take a screenshot\", \"scrape data from a page\", \"test this web app\", \"login to a site\", \"automate browser actions\", or any task requiring programmatic web interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fagent-browser\u002FSKILL.md",[],[],{"skillNo":144,"name":145,"nameZh":6,"description":146,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":111,"licenseFileUrl":6,"sourceHtmlUrl":147,"categories":148,"keywords":149,"publishedAt":19},"01M7CTBKVFYBG78FDSABSDJTTQ","shadcn","Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn\u002Fui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for \"shadcn init\", \"create an app with --preset\", \"switch to --preset\", and for building a design system or applying a DESIGN.md or brand spec to shadcn\u002Fui.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-UI-界面组件\u002FYYC3-UI-界面组件-ui\u002Fskills\u002Fshadcn\u002FSKILL.md",[],[]]