[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6991PD7A24G94KD3S85VFZM":3,"skill-same:01M6991PD7A24G94KD3S85VFZM":80},{"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":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":47,"commitSha":48,"skillDirectory":49,"forksCount":50,"repositoryHtmlUrl":51,"repositoryHomepageUrl":6,"ownerHtmlUrl":52,"ownerBlogUrl":53,"ownerDescription":54,"updatedAt":55,"install":56,"resources":69},"01M6991PD7A24G94KD3S85VFZM","datalineage-summary",null,"Summarizes data lineage graphs on Google Cloud to help users debug data quality issues and understand data provenance for BigQuery and Cloud Storage. Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report. Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation. Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).","google\u002Fskills","google","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F1342004?v=4","01M698VYEFDM0VJBZDYYJ2T83S","Google","01M698WR0H76ENHE587T9EJT89",24122,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fdatalineage-summary\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,9],"summary","datalineage summary","impact analysis","analysis","blast-radius","when","debug","use","impact","Cloud Storage","issues","upstream","flows","editing","for","generic","as","lineage","impact-analysis","google cloud","2026-11-10 10:12:30",false,"---\nname: datalineage-summary\nmetadata:\n  version: \"1.0.3\"\n  category: BigDataAndAnalytics\ndescription: >-\n  Summarizes data lineage graphs on Google Cloud to help users debug data quality issues and understand data provenance for BigQuery and Cloud Storage.\n  Use when summarizing upstream and downstream data flows, and presenting complex lineage data as an intuitive Markdown report.\n  Don't use for generic BigQuery queries, editing lineage relationships, or downstream deprecation.\n  Don't use for downstream blast-radius impact analysis (use datalineage-bigquery-asset-impact-analysis skill instead).\n---\n\n# Data Lineage Summary\n\nThis skill guides the agent in investigating and summarizing the Data Lineage\ngraph for a specific focal asset (Table-Level Lineage) or specific fields\n(Column-Level Lineage). It provides an intuitive left-to-right walkthrough of\nhow data enters and leaves the asset, abstracting away complex node and link\ndetails into plain English.\n\n## Attribution\n\n**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you\nMUST read [Usage Attribution](references\u002Fattribution.md). For commands executed\ndirectly in the terminal (never in generated scripts, Terraform, or user code),\nprefix `gcloud` with\n`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION=\"agent-skills\u002F1.0 (skill:datalineage-summary)\"`\nand append `agent-skills\u002F1.0 (skill:datalineage-summary)` to `User-Agent` headers.\n\n## Prerequisites\n\nThis skill relies on the **data lineage (Knowledge Catalog) MCP Server** on\nGoogle Cloud for graph traversal. Ensure you can run `search_lineage` queries in\nboth upstream and downstream directions. For detailed connection configurations\nand tool schemas, refer to [MCP Usage](references\u002Fmcp-usage.md).\n\n## Workflow Logic\n\n### 1. Get Lineage\n\nFetch the lineage graph in both directions from the focal point (both upstream\nand downstream) by making *two separate calls* to the MCP tool: one with\n`\"direction\": \"UPSTREAM\"` and another with `\"direction\": \"DOWNSTREAM\"`.\n\n*   **Location Strategy**: You **MUST** use the `read_url` tool to fetch the\n    comprehensive list of locations dynamically from the provided\n    [Knowledge Catalog Locations](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Flocations.md.txt)\n    link. To ensure cross-regional lineage is not missed, always verify the\n    current list of Google Cloud regions using this link before populating the\n    `locations` array. You **MUST** populate the `locations` array with all\n    supported physical regions fetched from this link. You may optionally\n    additionally determine the asset's specific active region (using `bq show`\n    or `gcloud storage ls`).\n*   **Search Parameters**: Use `maxDepth = 10`, `maxResults = 5000` and\n    `maxProcessPerLink = 10` as robust defaults when calling `search_lineage`.\n    For example, a DOWNSTREAM call should be formatted like this (expanding the\n    `locations` array as needed):\n\n    ```json\n    {\n      \"parent\": \"projects\u002Fproject_id\u002Flocations\u002Fus\",\n      \"locations\": [\n        \"us\",\n        \"us-central1\",\n        \"us-east1\",\n        \"us-west1\",\n        \"europe-west1\",\n        \"asia-northeast1\"\n      ],\n      \"rootCriteria\": {\n        \"entities\": {\n          \"entities\": [\n            {\n              \"fullyQualifiedName\": \"bigquery:project.dataset.table\"\n            }\n          ]\n        }\n      },\n      \"direction\": \"DOWNSTREAM\",\n      \"limits\": {\n        \"maxDepth\": 10,\n        \"maxResults\": 5000,\n        \"maxProcessPerLink\": 10\n      }\n    }\n    ```\n\n    Ensure you make a similar call with `\"direction\": \"UPSTREAM\"` to fetch the\n    upstream lineage.\n\n*   **Column-Level Lineage (CLL)**: The `search_lineage` tool can find all\n    Column-Level Lineage (CLL) by configuring the `field` array. If Table-Level\n    Lineage (TLL) is requested, configure the call to get CLL links along with\n    the TLL links by exploiting the `\"*\"` wildcard. For example:\n\n    ```json\n    \"rootCriteria\": {\n      \"entities\": {\n        \"entities\": [\n          {\n            \"fullyQualifiedName\": \"bigquery:project.dataset.table\",\n            \"field\": [\n              \"*\"\n            ]\n          }\n        ]\n      }\n    }\n    ```\n\n    If evaluating a specific column, replace `\"*\"` with the specific column name\n    (e.g., `\"efficiency_score\"`).\n\n### 2. Summarize\n\nGenerate the summary using the prompt guidelines below.\n\n*   **Persona**: Act as an expert Data Lineage Analyst generating a concise,\n    easy-to-understand left-to-right walkthrough of the data flow.\n*   **Structure & Flow**: Start immediately with the summary text, structured as\n    follows:\n    *   **Overall Flow Type**: State the inferred workflow type and data domain\n        (e.g., \"This appears to be a Feature Engineering workflow...\").\n    *   **Systems Overview**: List the primary systems involved up front. If the\n        request is for Column-Level Lineage, you MUST explicitly declare that\n        the scope of the analysis is limited to the specified field up front.\n    *   **Upstream Lineage**: Use the exact bold header `**Upstream Lineage:**`.\n        Narrative must detail how data arrives at the focal asset, mentioning\n        key source systems, projects, and processing tasks (e.g., Spark on\n        Dataproc).\n    *   **Downstream Lineage**: Use the exact bold header `**Downstream\n        Lineage:**`. Detail where data goes from the focal asset to final\n        consumer systems.\n    *   **Analysis Metadata**: Display the parameters used for the API call to\n        provide transparency on the boundaries of the summary. The output must\n        contain:\n        *   **Locations Searched**: `{list_of_locations_queried}`\n        *   **Parent Location**: `{parent_path}`\n        *   **Depth Limit**: `{maxDepth}`\n        *   **Process per Link Limit**: `{maxProcessPerLink}`\n        *   **Tip for User**: A prompt suggesting they can ask to rerun with\n            expanded locations (if not all were used) or depth.\n*   **Granularity Constraints**:\n    *   Prioritize flows between Systems, Projects, and Datasets over individual\n        files\u002Ftables.\n    *   You MUST explicitly list specific asset names (e.g., source tables,\n        intermediate views, consumer tables) if there are fewer than 5. Do not\n        just summarize counts if there are fewer than 5; name them explicitly.\n        Otherwise, if 5 or more, aggregate them by count (e.g., \"5 Cloud\n        Storage buckets\").\n    *   Only mention counts for *ultimate sources*, *final consumers*, and\n        *total assets*.\n    *   Do not repeat project names redundantly for every dataset if only one\n        project is involved.\n*   **Tone**: Avoid jargon and generic phrases like \"There are distinct factual\n    points.\" Be direct and clear. The final output is Markdown.\n\n### 3. Return the Summary\n\nReturn the final summarized output back to the user.\n\n## External Documentation\n\n-   [Knowledge Catalog Data Lineage Documentation](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Fabout-data-lineage.md.txt)\n-   [Use the Data Lineage MCP server](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Fuse-lineage-mcp.md.txt)\n-   [Knowledge Catalog Data Lineage API Reference](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Freference\u002Fdata-lineage\u002Frest.md.txt)\n","# Data Lineage Summary\n\nThis skill guides the agent in investigating and summarizing the Data Lineage\ngraph for a specific focal asset (Table-Level Lineage) or specific fields\n(Column-Level Lineage). It provides an intuitive left-to-right walkthrough of\nhow data enters and leaves the asset, abstracting away complex node and link\ndetails into plain English.\n\n## Attribution\n\n**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you\nMUST read [Usage Attribution](references\u002Fattribution.md). For commands executed\ndirectly in the terminal (never in generated scripts, Terraform, or user code),\nprefix `gcloud` with\n`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION=\"agent-skills\u002F1.0 (skill:datalineage-summary)\"`\nand append `agent-skills\u002F1.0 (skill:datalineage-summary)` to `User-Agent` headers.\n\n## Prerequisites\n\nThis skill relies on the **data lineage (Knowledge Catalog) MCP Server** on\nGoogle Cloud for graph traversal. Ensure you can run `search_lineage` queries in\nboth upstream and downstream directions. For detailed connection configurations\nand tool schemas, refer to [MCP Usage](references\u002Fmcp-usage.md).\n\n## Workflow Logic\n\n### 1. Get Lineage\n\nFetch the lineage graph in both directions from the focal point (both upstream\nand downstream) by making *two separate calls* to the MCP tool: one with\n`\"direction\": \"UPSTREAM\"` and another with `\"direction\": \"DOWNSTREAM\"`.\n\n*   **Location Strategy**: You **MUST** use the `read_url` tool to fetch the\n    comprehensive list of locations dynamically from the provided\n    [Knowledge Catalog Locations](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Flocations.md.txt)\n    link. To ensure cross-regional lineage is not missed, always verify the\n    current list of Google Cloud regions using this link before populating the\n    `locations` array. You **MUST** populate the `locations` array with all\n    supported physical regions fetched from this link. You may optionally\n    additionally determine the asset's specific active region (using `bq show`\n    or `gcloud storage ls`).\n*   **Search Parameters**: Use `maxDepth = 10`, `maxResults = 5000` and\n    `maxProcessPerLink = 10` as robust defaults when calling `search_lineage`.\n    For example, a DOWNSTREAM call should be formatted like this (expanding the\n    `locations` array as needed):\n\n    ```json\n    {\n      \"parent\": \"projects\u002Fproject_id\u002Flocations\u002Fus\",\n      \"locations\": [\n        \"us\",\n        \"us-central1\",\n        \"us-east1\",\n        \"us-west1\",\n        \"europe-west1\",\n        \"asia-northeast1\"\n      ],\n      \"rootCriteria\": {\n        \"entities\": {\n          \"entities\": [\n            {\n              \"fullyQualifiedName\": \"bigquery:project.dataset.table\"\n            }\n          ]\n        }\n      },\n      \"direction\": \"DOWNSTREAM\",\n      \"limits\": {\n        \"maxDepth\": 10,\n        \"maxResults\": 5000,\n        \"maxProcessPerLink\": 10\n      }\n    }\n    ```\n\n    Ensure you make a similar call with `\"direction\": \"UPSTREAM\"` to fetch the\n    upstream lineage.\n\n*   **Column-Level Lineage (CLL)**: The `search_lineage` tool can find all\n    Column-Level Lineage (CLL) by configuring the `field` array. If Table-Level\n    Lineage (TLL) is requested, configure the call to get CLL links along with\n    the TLL links by exploiting the `\"*\"` wildcard. For example:\n\n    ```json\n    \"rootCriteria\": {\n      \"entities\": {\n        \"entities\": [\n          {\n            \"fullyQualifiedName\": \"bigquery:project.dataset.table\",\n            \"field\": [\n              \"*\"\n            ]\n          }\n        ]\n      }\n    }\n    ```\n\n    If evaluating a specific column, replace `\"*\"` with the specific column name\n    (e.g., `\"efficiency_score\"`).\n\n### 2. Summarize\n\nGenerate the summary using the prompt guidelines below.\n\n*   **Persona**: Act as an expert Data Lineage Analyst generating a concise,\n    easy-to-understand left-to-right walkthrough of the data flow.\n*   **Structure & Flow**: Start immediately with the summary text, structured as\n    follows:\n    *   **Overall Flow Type**: State the inferred workflow type and data domain\n        (e.g., \"This appears to be a Feature Engineering workflow...\").\n    *   **Systems Overview**: List the primary systems involved up front. If the\n        request is for Column-Level Lineage, you MUST explicitly declare that\n        the scope of the analysis is limited to the specified field up front.\n    *   **Upstream Lineage**: Use the exact bold header `**Upstream Lineage:**`.\n        Narrative must detail how data arrives at the focal asset, mentioning\n        key source systems, projects, and processing tasks (e.g., Spark on\n        Dataproc).\n    *   **Downstream Lineage**: Use the exact bold header `**Downstream\n        Lineage:**`. Detail where data goes from the focal asset to final\n        consumer systems.\n    *   **Analysis Metadata**: Display the parameters used for the API call to\n        provide transparency on the boundaries of the summary. The output must\n        contain:\n        *   **Locations Searched**: `{list_of_locations_queried}`\n        *   **Parent Location**: `{parent_path}`\n        *   **Depth Limit**: `{maxDepth}`\n        *   **Process per Link Limit**: `{maxProcessPerLink}`\n        *   **Tip for User**: A prompt suggesting they can ask to rerun with\n            expanded locations (if not all were used) or depth.\n*   **Granularity Constraints**:\n    *   Prioritize flows between Systems, Projects, and Datasets over individual\n        files\u002Ftables.\n    *   You MUST explicitly list specific asset names (e.g., source tables,\n        intermediate views, consumer tables) if there are fewer than 5. Do not\n        just summarize counts if there are fewer than 5; name them explicitly.\n        Otherwise, if 5 or more, aggregate them by count (e.g., \"5 Cloud\n        Storage buckets\").\n    *   Only mention counts for *ultimate sources*, *final consumers*, and\n        *total assets*.\n    *   Do not repeat project names redundantly for every dataset if only one\n        project is involved.\n*   **Tone**: Avoid jargon and generic phrases like \"There are distinct factual\n    points.\" Be direct and clear. The final output is Markdown.\n\n### 3. Return the Summary\n\nReturn the final summarized output back to the user.\n\n## External Documentation\n\n-   [Knowledge Catalog Data Lineage Documentation](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Fabout-data-lineage.md.txt)\n-   [Use the Data Lineage MCP server](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Fuse-lineage-mcp.md.txt)\n-   [Knowledge Catalog Data Lineage API Reference](https:\u002F\u002Fdocs.cloud.google.com\u002Fknowledge-catalog\u002Fdocs\u002Freference\u002Fdata-lineage\u002Frest.md.txt)\n",{"name":5,"metadata":44,"description":7},{"version":45,"category":46},"1.0.3","BigDataAndAnalytics","main","4c6800d20130b5a3233e414609f1241013cec8cc","skills\u002Fcloud\u002Fdatalineage-summary",2005,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills","https:\u002F\u002Fgithub.com\u002Fgoogle","https:\u002F\u002Fopensource.google\u002F","Google ❤️ Open Source","2026-11-14 01:51:35",{"source":8,"skillName":5,"commands":57,"prompt":67,"zipAvailable":68},[58,61,64],{"tool":59,"command":60},"npx","npx skills add google\u002Fskills --skill datalineage-summary",{"tool":62,"command":63},"bunx","bunx skills add google\u002Fskills --skill datalineage-summary",{"tool":65,"command":66},"pnpm","pnpm dlx skills add google\u002Fskills --skill datalineage-summary","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fdatalineage-summary\u002FSKILL.md",true,[70,76],{"path":71,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":74,"sourceHtmlUrl":75},"references\u002Fattribution.md","REFERENCE","参考文档",1897,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fdatalineage-summary\u002Freferences\u002Fattribution.md",{"path":77,"resourceType":72,"resourceTypeDesc":73,"sizeBytes":78,"sourceHtmlUrl":79},"references\u002Fmcp-usage.md",1259,"https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fdatalineage-summary\u002Freferences\u002Fmcp-usage.md",[81,118,148,177,204,227],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":95,"publishedAt":39},"01M6998S2EZKD3GEJ7F943RZTE","sign-in-with-google-web","Implement, configure, and secure Sign In With Google (SiwG) using Google Identity Services (GIS \u002F `https:\u002F\u002Faccounts.google.com\u002Fgsi\u002Fclient`) across web architectures. Use when creating Google sign-in buttons, implementing Google One Tap with FedCM, integrating GIS in React\u002FNext.js\u002FAngular\u002FHTML, verifying ID tokens on backend runtimes (Python\u002FNode.js\u002FGo\u002FJava), enforcing Google Workspace domain restrictions (`hd`), securing client-side ID tokens via WebCrypto nonces or encrypted IndexedDB, embedding in cross-origin iframes via the Intermediate Iframe API (`https:\u002F\u002Faccounts.google.com\u002Fgsi\u002Fintermediate`), configuring Content Security Policy (CSP), COOP, and Permissions Policy (`identity-credentials-get`) headers, or handling sign-out and revocation. Don't use for legacy Google Sign-In (`gapi.auth2`), Google Cloud IAM service accounts, or Android\u002FiOS native Credential Manager.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fidentity\u002Fsign-in-with-google-web\u002FSKILL.md",[87,92],{"categoryNo":88,"categoryName":89,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000010","后端与接口",[9,96,97,98,99,100,101,102,103,38,104,105,106,107,108,109,110,111,112,113,114,115,116,117],"sign in with google web","sign","with","web","android","go","security","google workspace","implement","policy","python","implementing","react","iam","permissions","buttons","secure","manager","identity","architectures","domain","runtimes",{"skillNo":119,"name":120,"nameZh":6,"description":121,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":122,"categories":123,"keywords":133,"publishedAt":39},"01M6998PHPDCAD684VW5WRG83D","dpop-adoption","Implement and debug OAuth 2.0 DPoP (RFC 9449) refresh token sender-constraining for WebCrypto, Node.js ES6, and browser runtimes integrating with Google's OAuth platform. Use when configuring non-extractable asymmetric key pairs (P-256), generating DPoP Proof JWTs for authorization code exchange and token refresh, or handling 400 use_dpop_nonce challenge retry loops at oauth2.googleapis.com\u002Ftoken. Don't use for unconstrained OAuth 2.0 flows (where refresh tokens are not bound to a client key pair), or for Google Cloud IAM \u002F service account authentication.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fidentity\u002Fdpop-adoption\u002FSKILL.md",[124,125,128],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":126,"categoryName":127,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[134,135,9,38,136,137,138,31,139,140,109,141,142,143,144,145,146,114,117,147,24],"dpop adoption","adoption","es6","retry","authentication","challenge","code","browser","loops","at","node","token","pair","platform",{"skillNo":149,"name":150,"nameZh":6,"description":151,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":152,"categories":153,"keywords":160,"publishedAt":39},"01M6998M72TC73EEAQH4XC7EXW","retrieving-developer-knowledge","Searches, retrieves, and synthesizes official Google developer documentation across Google Cloud, AI\u002FGemini, Android, Chrome, Web, Flutter, Go, Firebase, and other Google developer platforms. Integrates with the Developer Knowledge MCP server (search_documents, get_documents, answer_query) or the Developer Knowledge REST API fallback. Use when searching for gcloud CLI commands, API syntax, IAM permissions, official documentation, architectural comparisons, or product choice overviews. Don't use for local filesystem lookups or non-Google documentation.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fdevelopers\u002Fretrieving-developer-knowledge\u002FSKILL.md",[154,155,158,159],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":156,"categoryName":157,"taxonomyType":90,"taxonomyTypeDesc":91},"01JBSEEDCAT000000000000021","资料检索与研究",{"categoryNo":126,"categoryName":127,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},[161,162,163,164,38,165,166,167,168,169,170,171,172,24,173,174,175,109,176,110],"retrieving developer knowledge","knowledge","developer","MCP","mcp server","official","developer documentation","get","search","local","choice","documents","query","api","across","documentation",{"skillNo":178,"name":179,"nameZh":6,"description":180,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":181,"categories":182,"keywords":183,"publishedAt":39},"01M6998J2CZEXS9BES9S3WWFKC","migrate-to-rust","Clones, analyzes, plans, and migrates legacy codebases (C++, Fortran, Java, Python, C, Shell) from a GitHub URL or local directory to a modern, high-performance, deterministic, 100% Safe Rust architecture, tracking live telemetry across every task bucket, test failure\u002Ffix cycle, and Profile-Guided Optimization (PGO) stage, and producing a first-person AI storytelling report and interactive HTML infographic. Use when migrating a GitHub repository or local codebase to Rust, porting legacy C++, Fortran, Python, or Java workloads to memory-safe Rust, designing Struct-of-Arrays (SoA) or SIMD Rust architectures, or optimizing Rust ports with LLVM PGO. Don't use for unrelated non-Rust refactoring or single-line syntax questions.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fdevelopers\u002Fmigrate-to-rust\u002FSKILL.md",[],[184,185,186,187,188,189,190,191,106,192,193,194,195,196,197,170,198,199,200,24,201,202,175,203],"migrate to rust","rust","migrate","github","memory","performance","directory","safe","ports","llvm","soa","cycle","porting","fix","arrays","infographic","high-performance","URL","architecture","unrelated",{"skillNo":205,"name":206,"nameZh":6,"description":207,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":208,"categories":209,"keywords":213,"publishedAt":39},"01M6998GCC3K29WZ82KXMB9E02","finding-google-skills","Google platform decision and setup guidance, loaded on demand from Google's skill catalog. Use when a developer is choosing or setting up part of their stack, such as where to run a service, a database, storage, messaging, authentication, analytics, ads, or AI model serving, and a Google product is a reasonable candidate - whether or not a vendor is named - or when a request names a Google product or API. Brings in the matching Google skill so the answer can weigh Google options, their trade-offs, and when they are not the right fit. Skip when the stack is already settled on another provider and no Google product is named, or the task involves no platform choice.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fdevelopers\u002Ffinding-google-skills\u002FSKILL.md",[210,211,212],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":126,"categoryName":127,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":129,"categoryName":130,"taxonomyType":131,"taxonomyTypeDesc":132},[9,214,215,35,216,147,217,218,219,220,221,138,222,223,224,171,26,225,24,226,174],"finding google skills","storage","messaging","model","trade-offs","provider","answer","fit","catalog","up","decision","database","candidate",{"skillNo":228,"name":229,"nameZh":6,"description":230,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":231,"categories":232,"keywords":235,"publishedAt":39},"01M6998DWNHTH0BS6W1CY8ZXMP","workload-manager-basics","Use this skill to manage Google Cloud Workload Manager evaluations, rules, scanned resources, and validation results by using public client libraries and the REST API. Use when you need to inspect workload best-practice rules, create and run evaluations for Google Cloud general best practices, SAP, SQL Server, or custom organizational rules, review violations, export results to BigQuery, or automate Workload Manager through client libraries because no service-specific public CLI or MCP server is available. Don't use for general Google Compute Engine instance management, VPC configuration, or standard IAM auditing.","https:\u002F\u002Fgithub.com\u002Fgoogle\u002Fskills\u002Fblob\u002Fmain\u002Fskills\u002Fcloud\u002Fworkload-manager-basics\u002FSKILL.md",[233,234],{"categoryNo":93,"categoryName":94,"taxonomyType":90,"taxonomyTypeDesc":91},{"categoryNo":126,"categoryName":127,"taxonomyType":90,"taxonomyTypeDesc":91},[236,237,113,238,9,164,239,38,165,240,241,242,243,24,244,174,109,245,246,247,248],"workload manager basics","workload","basics","cli","review","vpc","resources","inspect","you","create","libraries","server","run"]