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omni-model-explorer全向模型浏览器

Agent Skill

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。

总安装

533

周安装

22

GitHub Stars

12

下载量

174
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: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

简介

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。

SKILL.md

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

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

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

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Snyk

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权限和风险

敏感数据

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安装前确认

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