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Agent Skill · 研究检索

docyrus-architect(多赛勒斯建筑师)

docyrus-architect 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

docyrus-architect 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 37,380。

总安装 1,746周安装 75GitHub Stars 13下载 612核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:docyrus-architect(多赛勒斯建筑师)
来源仓库:https://github.com/docyrus/agent-skills
仓库路径:skills/docyrus-architect
安装命令:
npx skills add https://github.com/docyrus/agent-skills --skill docyrus-architect
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/docyrus/agent-skills --skill docyrus-architect

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

docyrus-architect 提供 MCP 工具集,用于发现和管理 Docyrus 平台中的数据源与应用。它支持按名称、描述或应用 ID 搜索数据源,并获取字段元数据与枚举值信息。使用时需先调用 get_apps 定位租户应用,再通过 get_data_source_metadata 获取完整结构。

安装前应确认是否允许运行远程查询工具,并评估对生产环境数据访问的风险。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/docyrus-architect

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/docyrus/agent-skills --skill docyrus-architect;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

docyrus-architect 怎么安装?

在终端执行 npx skills add https://github.com/docyrus/agent-skills --skill docyrus-architect。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

docyrus-architect 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

docyrus-architect 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

docyrus-architect 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

docyrus-architect 用的人多吗?

公开数据是累计安装 1,746 次,近一周安装 75 次,下载 612 次,GitHub 13 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

docyrus-architect 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
docyrus-architect

多赛勒斯建筑师 · 本页

1,74613调用外部服务未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Docyrus Architect

Guide for using docyrus-architect MCP tools to manage and query data sources in Docyrus.

Tool Overview

Discovery Tools

  • get_apps — List tenant apps. Use before create_data_source to find the target tenantAppId.
  • get_data_source_list — Search data sources by name/description or app ID.
  • get_data_source_list_with_fields — Same as above but includes field names and types.
  • get_data_source_metadata — Get full metadata (fields with IDs, types, slugs, enums, relations) for a data source. Always call this before querying to discover field slugs and relation targets.
  • get_enums_by_field_id — Get enum options for select/status/tagSelect fields.
  • read_current_user / read_tenant_user — Get user info.

Data Source CRUD

  • create_data_source — Create a new data source (table). Default fields auto-created: id, autonumber_id, name, record_owner, created_on, created_by, last_modified_by, last_modified_on.
  • create_data_sources_batch — Create multiple data sources with fields and enum options in a single atomic transaction. Supports cross-referencing data sources within the batch by slug for field-relation types. Max 20 data sources per batch.
  • update_data_source — Update data source properties.
  • delete_data_source — Delete a data source and all its data.

Field Management

  • create_fields — Batch create fields. Set relationDataSourceId for field-relation types.
  • update_fields — Batch update fields. Non-CUSTOM fields get customization records.
  • delete_fields — Batch delete fields by ID.

Enum Management

  • create_enums — Create enum options for select/tagSelect/status fields. Pass fieldId for field-specific enums or enumSetId for shared enum sets.
  • update_enums — Update enum option name/slug/color/icon.
  • delete_enums — Delete enum options.

OpenAPI Spec

  • regenerate_openapi_spec — Regenerate and upload the tenant's OpenAPI spec after data source or field changes. Accepts optional dataSourceSlugs (string array) to limit scope; omit to include all data sources. Returns the publicUrl of the uploaded spec. Call this after any create_data_source, update_data_source, delete_data_source, create_fields, update_fields, or delete_fields operation to keep the spec in sync.

Query & Compute

  • query_data_source — Read data with filtering, sorting, aggregation, formulas, pivots, child queries. See references/data-source-query-guide.md for complete query syntax.
  • evaluate_jsonata — Test JSONata expressions. Use for validating computed field formulas.

Custom Queries

  • get_custom_queries — List non-archived custom queries for the tenant.
  • get_custom_query_by_id — Read full custom query definition (name, description, query, filters).
  • create_custom_query — Create a saved SQL template using Handlebars variables and optional filter definitions.
  • update_custom_query — Update selected fields of an existing custom query (partial update).
  • delete_custom_query — Soft-delete (archive) a custom query.
  • run_custom_query — Execute a saved custom query with runtime filters, pagination offset, and optional simulate mode.

Common Workflows

Create a Data Source with Fields and Enums

Single data source approach:

  1. Call get_apps to find the target app ID
  2. Call create_data_source with title (plural), name (singular), slug (singular snake_case)
  3. Call create_fields with all custom fields (default fields already exist)
  4. For select/tagSelect/status fields, call create_enums with the field ID from step 3
  5. Call regenerate_openapi_spec to update the OpenAPI spec

Batch approach (recommended for multiple data sources):

  1. Call get_apps to find the target app ID (optional, defaults to "Default Customizations App")
  2. Call create_data_sources_batch with an array of data source definitions (max 20)

- Each data source includes title, name, slug, and fields array - Fields can include inline enumOptions for select/status/tagSelect fields - Use slug references for relationDataSourceId to reference other data sources in the same batch - All data sources, fields, and enums are created in a single atomic transaction

  1. Call regenerate_openapi_spec to update the OpenAPI spec

Query Data

  1. Call get_data_source_metadata to discover field slugs, types, and relations
  2. Call query_data_source with appropriate columns, filters, and sorting
  3. For advanced queries (aggregations, formulas, pivots, child queries), read references/data-source-query-guide.md

Modify Existing Data Source

  1. Call get_data_source_metadata to see current fields
  2. Use create_fields / update_fields / delete_fields as needed
  3. For enum changes, use get_enums_by_field_id first, then create_enums / update_enums / delete_enums
  4. Call regenerate_openapi_spec to update the OpenAPI spec

Manage a Custom Query Lifecycle

  1. Call get_custom_queries to find an existing query or confirm naming
  2. Call create_custom_query with name, query, and optional description/filters
  3. Call get_custom_query_by_id to verify the saved template and filter definitions
  4. Use update_custom_query for targeted edits (rename, revise SQL template, update filter definitions)
  5. Use delete_custom_query only when archival is explicitly requested

Run and Debug a Custom Query

  1. Call get_custom_query_by_id first to inspect SQL template and available filter slugs
  2. Build runtime filters with rules[].field values that match the query's filter slugs
  3. Call run_custom_query with simulate: true for complex or untrusted queries to inspect plan output
  4. Call run_custom_query with simulate: false (or omitted) to fetch real data
  5. Use offset for pagination and expect a max of 50,000 rows per execution

Key Rules

Data Source Creation

  • title is plural (e.g., "Sales Orders"), name is singular (e.g., "Sales Order"), slug is singular snake_case (e.g., "sales_order")
  • Use defaultEditFormTarget: "tab" for complex forms, "side" for simple ones
  • Enable pluginActivityView for CRM-type data sources (leads, contacts, deals)
  • Enable pluginComments for collaborative data sources
  • Enable pluginFile when users need to attach files to records
  • Enable pluginDocyment when users need rich text documents per record

Field Types

  • field-relation requires relationDataSourceId — the ID (UUID) of the related data source, or in batch operations, the slug of another data source in the same batch
  • field-list is a virtual field showing child records (one-to-many) — not stored in DB
  • field-select / field-tagSelect / field-status need enum options:

- In create_fields: call create_enums after field creation - In create_data_sources_batch: include inline enumOptions array in the field definition

  • field-formula uses JSONata expressions — test with evaluate_jsonata first
  • field-inlineData stores array of objects, field-inlineForm stores single nested object
  • Field slug must be snake_case matching ^[a-z][a-z0-9_]*$
  • Enum option slug must be snake_case matching ^[a-z][a-z0-9_]*$ (auto-generated from name if not provided)

Batch Operations

  • create_data_sources_batch creates up to 20 data sources in a single transaction
  • Within a batch, reference other data sources using their slug for relationDataSourceId
  • For external data sources (created outside the batch), use the UUID for relationDataSourceId
  • Data source slugs must be unique within the batch (validation error otherwise)
  • Inline enum options are defined per-field using the enumOptions array
  • Each enum option in enumOptions can specify: name, slug, color, icon, sortOrder
  • If a batch operation fails, all changes are rolled back (atomic transaction)
  • Use batch operations when creating related data sources to avoid multiple API calls and ensure consistency

Querying

  • Use dataSourceId (UUID) to identify which data source to query
  • columns is a comma-separated string of field slugs, not an array
  • For aggregations, always use id field for count calculations
  • Relation expansion: relation_field(sub_field1, sub_field2) selects nested columns
  • Spread operator: ...relation_field(alias:sub_field) flattens into root object
  • Filter on related fields: rel_{{relation_slug}}/{{field_slug}}
  • Date filters have shortcut operators like today, this_month, last_30_days

query_data_source Required Parameters

All parameters are required in the MCP tool schema (most accept null):

  • dataSourceId: string (required, non-null)
  • columns: string | null
  • filters: object | null
  • filterKeyword: string | null
  • orderBy: array | null
  • limit: number | null (default: 1000)
  • offset: number | null
  • fullCount: boolean | null
  • recordId: string | null (fetch single record by ID)
  • calculations: array | null
  • distinctColumns: array | null
  • formulas: array | null
  • childQueries: array | null
  • pivot: object | null

Custom Query Rules

  • Treat custom query query content as a Handlebars SQL template, not static SQL.
  • Use built-in context variables in templates when relevant: TENANT_ID, TENANT_SCHEMA, USER_ID, USER_EMAIL, USER_FIRSTNAME, USER_LASTNAME, USER_FULLNAME.
  • Use {{filter FILTERS.<slug> <column_expression>}} for optional runtime filtering. If no runtime value is provided, the helper resolves to 1=1.
  • Keep filters definitions in create_custom_query / update_custom_query aligned with template usage:

- template usage: FILTERS.<slug> - runtime rule field: <slug> - filter definition slug: <slug>

  • Prefer simulate: true before running expensive queries to inspect EXPLAIN (ANALYZE, BUFFERS, FORMAT JSON) output.
  • Respect runtime limits on run_custom_query: 50,000 row cap, 15s timeout for normal execution, 30s timeout for simulate mode.
  • Use delete_custom_query as an archival action (soft delete), not permanent deletion.
  • For JSONB-backed simple data sources, access custom fields with (table_alias."data"->>'field-uuid')::type.

References

  • Data Source Query Guide — Up-to-date reference for query_data_source including columns, filters, orderBy, pagination, calculations, formulas, pivots, child queries, and operator details.
  • Formula Design Guide (LLM) — Up-to-date guide for designing formula payloads used in query requests.
  • Custom Query Guide — Full lifecycle and execution reference for get_custom_queries, get_custom_query_by_id, create_custom_query, update_custom_query, delete_custom_query, and run_custom_query.

平台分布

Codex

37.77%
按下载量换算231

Claude

28.96%
按下载量换算177

Cursor

17.92%
按下载量换算110

Gemini CLI

8.68%
按下载量换算53

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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