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schema-discovery模式发现

Agent Skill

schema-discovery 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。

总安装

456

周安装

19

GitHub Stars

2

下载量

152
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:schema-discovery(模式发现)
来源仓库:https://github.com/lytics/agent-skills
仓库路径:skills/schema-discovery
安装命令:
npx skills add https://github.com/lytics/agent-skills --skill schema-discovery
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/lytics/agent-skills --skill schema-discovery

简介

用于查找、检索和筛选相关信息,支持根据关键词定位候选结果。

  • 适合在任务场景中快速获取线索或缩小搜索范围。
  • 可结合原始 README 核验实际用法,确保与预期场景匹配。
  • 安装前建议确认维护状态及是否依赖外部网络调用。
  • schema-discovery 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Schema Discovery

Purpose

Fetch and interpret the profile schema to find fields that match natural language descriptions. Used by other skills (especially audience-builder) to map user intent to actual schema fields.

Environment

Requires authenticated API access. See ../references/auth.md for credential resolution.

Inputs

  • Natural language description of the data concepts to find (e.g., "country", "purchase history", "email engagement")
  • Table name (default: user)

API Endpoints

List All Fields

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/schema/${TABLE:-user}/field" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Returns all fields with their types, descriptions, and merge operations.

Lightweight Field Names

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/schema/${TABLE:-user}/fieldnames" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Returns just field names -- use for quick inventory.

Field Info with Value Distributions

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/api/schema/${TABLE:-user}/fieldinfo" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Returns field info including value distributions and sample data.

Field Value Suggestions

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/api/schema/${TABLE:-user}/fieldsuggest/${FIELD}?q=${QUERY}" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Returns suggested values for a specific field matching the query substring. The q parameter is required -- it performs case-insensitive substring matching against field values.

Identity Configuration

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/schema/${TABLE:-user}/idconfig" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Available Streams

curl -s "${LYTICS_API_URL:-https://api.lytics.io}/v2/stream/names" \
  -H "Authorization: ${LYTICS_API_TOKEN}"

Behavior

Step 1: Fetch Field Inventory

Call the field names endpoint to get the complete list of available fields.

Step 2: Score Candidate Fields

For each concept in the user's description, score candidate fields by:

  1. Name match (highest priority): exact or substring match on field name
  2. Type compatibility: field type supports the intended operation (see ../references/field-types.md)
  3. Description match: field's ShortDesc or LongDesc matches

Step 3: Confirm with Value Distributions

For the top 2-3 candidates per concept, fetch field value suggestions to confirm:

  • The field contains the expected kind of data
  • Sample values match what the user described (e.g., "US" values in a country field)

Step 4: Return Field Mapping

Return a mapping of:

  • Concept -> chosen field name, field type, confidence level, sample values
  • Any ambiguities that need user input

Field Matching Heuristics

Common natural language to field name patterns:

  • "country" -> country, geo_country, country_code
  • "email" -> email, _e
  • "purchased/bought" -> products_purchased, purchase_categories, orders
  • "visited/browsed" -> urls_visited, pages_viewed, visit_count
  • "signed up/registered" -> created, signup_date, joined
  • "clicked" -> click_count, clicks
  • "score" -> scores.*, engagement_score

Error Handling

  • If no fields match a concept, report that clearly and suggest the user rephrase or check available fields
  • If multiple equally strong candidates exist, present them for user selection
  • If the table doesn't exist, report and suggest user as default

Dependencies

  • References: ../references/auth.md, ../references/api-client.md, ../references/field-types.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.57%
按下载量换算56

Claude

29.78%
按下载量换算45

Cursor

16.7%
按下载量换算25

Gemini CLI

9.66%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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