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Agent Skill · 研究检索

omni-model-explorer(全向模型浏览器)

omni-model-explorer 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。

omni-model-explorer 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,权限为接触敏感数据;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 53,488。

总安装 533周安装 22GitHub Stars 12下载 174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:omni-model-explorer(全向模型浏览器)
来源仓库:https://github.com/exploreomni/omni-agent-skills
仓库路径:skills/omni-model-explorer
安装命令:
npx skills add https://github.com/exploreomni/omni-agent-skills --skill omni-model-explorer
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/exploreomni/omni-agent-skills --skill omni-model-explorer

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。

omni-model-explorer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中获取信息的场景。通过 npx skills add 命令安装,需结合原始 README 核验具体用法。

安装前建议确认权限范围、维护状态及是否触发联网或文件读写操作。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/omni-model-explorer

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/exploreomni/omni-agent-skills --skill omni-mod…;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

    它需要接触敏感数据,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

omni-model-explorer 怎么安装?

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

omni-model-explorer 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。

omni-model-explorer 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

omni-model-explorer 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。

omni-model-explorer 用的人多吗?

公开数据是累计安装 533 次,近一周安装 22 次,下载 174 次,GitHub 12 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。

omni-model-explorer 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
omni-model-explorer

全向模型浏览器 · 本页

53312接触敏感数据未明确通过

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

Omni Model Explorer

Explore and understand an Omni semantic model through the Omni CLI. This is the starting point — understand what exists before building, querying, or modifying anything.

Tip: Start with the Shared model — it contains the curated analytics layer.

Prerequisites

Configure the Omni CLI:

# Verify the Omni CLI is installed — if not, ask the user to install it
# See: https://github.com/exploreomni/cli#readme
command -v omni >/dev/null || echo "ERROR: Omni CLI is not installed."
# Show available profiles and select the appropriate one
omni config show
# If multiple profiles exist, ask the user which to use, then switch:
omni config use <profile-name>

API keys: Settings > API Keys (Organization Admin) or User Profile > Manage Account > Generate Token (Personal Access Token).

Discovering Commands

When unsure what operations or flags are available:

omni models --help              # List all model operations
omni models <operation> --help  # Show flags and positional args
Tip: Use -o json to force structured output for programmatic parsing, or -o human for readable tables. The default is auto (human in a TTY, JSON when piped).

Core Workflow

Explore top-down: List models → Pick a model → List topics → Inspect a topic → Explore views and fields.

Step 1: List Available Models

omni models list

Returns models with id, name, connectionId, and modelKind (SCHEMA or SHARED). Use the SHARED model — it contains the curated semantic layer.

To also see active branches on each model:

omni models list --include activeBranches

Each model in the response will include a branches array. Each branch has an id (UUID) and name — use the id as the branchId parameter in other API calls.

Step 2: List Topics in a Model

Topics are entry points for querying. Each topic defines a base view and the set of joined views available.

omni models list-topics <modelId>

Returns topic names, base views, labels, and descriptions.

Step 3: Inspect a Topic

Get full detail including all views, dimensions, measures, relationships, and AI context:

omni models get-topic <modelId> <topicName>

The response includes:

  • base_view_name — the primary table
  • views[] — all accessible views, each with dimensions[] and measures[]
  • relationships[] — how views join together
  • default_filters — filters applied by default
  • ai_context — instructions for Blobby (Omni's AI)

Step 4: Read the Model YAML

For the full semantic model definition:

# All YAML files
omni models yaml-get <modelId>

# Specific file
omni models yaml-get <modelId> --filename order_items.view

# Regex filter
omni models yaml-get <modelId> --filename '.*sales.*'

# From a branch (branchId is a UUID from the list models response)
omni models yaml-get <modelId> --branchid <branchId>

The mode parameter: combined (default) merges schema + shared model; extension shows only shared model customizations.

Model Architecture

Omni has three layers:

  1. Schema Model — auto-generated from your database (read-only)
  2. Shared Model — analytics engineer customizations (dimensions, measures, labels, topics, AI context)
  3. Workbook Model — per-dashboard customizations (ad-hoc, not shared)

When exploring, use the combined view to see everything available.

Key Concepts

Views correspond to database tables. Each has dimensions (groupable fields) and measures (aggregations).

Topics join views together into queryable units — curated starting points for analysis. A topic has a base view, joined views, default filters, and AI context.

Relationships define joins: join_from_view, join_to_view, on_sql, relationship_type (one_to_one, many_to_one, one_to_many, many_to_many), and join_type (always_left, inner, full_outer).

Field naming: view_name.field_name with bracket notation for date granularity: orders.created_at[week].

Exploration Patterns

"What data do we have about X?" — List topics → inspect the most relevant one → review views and fields.

"How do these tables relate?" — Inspect the topic's relationships[] — check join_from_view, join_to_view, on_sql, and relationship_type.

"What measures are available for Y?" — Inspect the topic containing view Y → review the measures[] array with aggregate_type and sql definitions.

Fallback: Expected View Missing from yaml-get

Use this pattern only when normal exploration comes up short — the user names a specific view and it's absent from the yaml-get or get-topic response, or a relationship references a view that doesn't appear. If yaml-get returned what you expected, skip this section.

Why it happens: yaml-get only returns views from currently-loaded schemas. If a schema is offloaded or inactive, its views won't show up. The get-schemas call surfaces *all* schemas the connection knows about — including offloaded and inactive ones — so it's the right next step before telling the user "not found."

Two-step recovery:

# 1. List every schema (loaded, offloaded, and inactive)
omni models get-schemas <modelId>
# → {"schemas": ["ANALYTICS", "PUBLIC", "STAGING", ...]}

# 2. If the target schema is in the list, load just that schema
omni models yaml-get <modelId> --includeschemas PUBLIC

If the schema isn't in the list at all, this isn't a lazy-load issue — the connection likely doesn't have access or the schema isn't synced. Check with a Connection Admin.

Rules for --includeschemas:

  • Accepts exactly one schema name per call — commas are rejected by the API. Load schemas one at a time if you need multiple.
  • When set, the response contains only views belonging to that schema. Relationships are preserved even when they reference views in other schemas.
  • To scope to a branch, add --branchid <id> to yaml-get or --branch-id <id> to get-schemas (the flag names differ per command — this matches the API's underlying casing).

Calculation Fields

Calculation fields in the model use a different format than regular dimensions/measures. The field key is calc_name and the expression property is sql_expression — not name/sql.

Field Impact Analysis

Assess the blast radius of a field migration or removal before pushing changes to dbt:

  1. Create a model branch with omni-model-builder where the field is removed or renamed
  2. Run the content validator against that branch:
omni models content-validator-get <modelId> --branch-id <branchId>

This returns all dashboards and tiles with broken references to the removed field.

  1. Search model YAML for additional references (run in parallel with step 2):
omni models yaml-get <modelId> --filename '.*'

Search the response for the field name to find references in other views, topics, and calculated fields.

  1. Report: Combine content-validator results (broken dashboards/tiles) with YAML search results (model references) into a structured blast-radius report.
Do NOT paginate documents and check queries individually — the content validator does this for you in one call.

Docs Reference

Related Skills

  • omni-model-builder — create or modify views, topics, and fields
  • omni-query — run queries against discovered fields
  • omni-ai-optimizer — inspect and improve AI context on topics

平台分布

Codex

34.26%
按下载量换算60

Claude

30.37%
按下载量换算53

Cursor

18.29%
按下载量换算32

Gemini CLI

8.27%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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