bi-semantic-layer-guide

bi-semantic-layer-guide is a skill for Claude Code, Codex from agentscope-ai/QwenPaw-Data. It costs 58 tokens per session (715 once invoked), scanned A, original, Apache-2.0.

A usage guide for a semantic layer, a shared service that defines business metrics, dimensions, and datasets in consistent terms.

In plain words
What is it for?
Finding metric definitions, checking which dimensions can be used for breakdowns, reviewing metric hierarchies and values, and locating the datasets and columns behind a metric.
Why use it?
It helps prevent conflicting definitions and unclear business meaning when analysing data.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Finding metric definitions, checking which dimensions can be used for breakdowns, reviewing metric hierarchies and values, and locating the datasets and columns behind a metric.

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Install with agentmods
npx agentmods add skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add agentscope-ai/QwenPaw-Data --skill bi-semantic-layer-guide
Clone the repo
git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bi-semantic-layer-guide

README.md
[![agentmods](https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide/github.svg)](https://agentmods.dev/skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide)
Your own site
<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for bi-semantic-layer-guide

Your own site · 80×15
<a href="https://agentmods.dev/skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide"><img src="https://agentmods.dev/badge/skills/agentscope-ai/qwenpaw-data/bi-semantic-layer-guide.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 715 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00058 $0.00715
Opus 5 $0.00029 $0.00358
Sonnet 5 $0.00012 $0.00143
Haiku 4.5 $0.00006 $0.00072

Measured 10d ago against content hash d6a70b0a0a05, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

bi-semantic-layer-guide scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

packages/qwenpaw-data-skills/skills/runtime/bi-semantic-layer-guide/SKILL.md · 58 lines

What it actually says

bi-semantic-layer-guide

概述

语义层是统一管理业务语义元数据的服务,包括指标定义、维度定义、指标维度绑定和数据集映射。


可用工具

语义层暴露三类工具:

  • 全局list_domains()
  • 指标查询list_metrics(domain)search_metrics(query, domain)get_metric(name, domain)get_north_star_metrics(domain)
  • 维度查询list_dimensions(domain)get_dimension(name, domain)list_dimensions_of_metric(name, domain)get_dimension_hierarchy(name, domain)get_dimension_values(name, domain)
  • 数据集查询list_datasets(domain)get_dataset_columns(name, domain)get_dataset(name, domain)

具体参数和返回格式参见工具自身描述。


查询策略

指标匹配

在语义层中查找指标,可选策略:

  • 语义检索(search_metrics),语义层会自动匹配同义词
  • 查看具体业务域的北极星指标列表(get_north_star_metrics),从中选择最相关的
  • 若以上均未命中,列出该域全部指标(list_metrics),逐一判断和分析条目的相关性。

指标属性确认

通过 get_metric 获取指标属性,重点属性:

  • 是否是北极星指标is_north_star):用于角色分配
  • 是否展示指标is_display):该指标是否应出现在展示面板中
  • 是否展示分布is_display_distribution):展示指标时是否同时展示分布图
  • 维度绑定dimensions):指标可拆解的维度列表,含 is_display_dimensionis_contribution_dimension 标记。

维度信息获取

通过 list_dimensions_of_metric 获取指标可拆解的维度列表(is_contribution_dimension=true 的维度才可用于贡献度拆解),通过 get_dimension_hierarchy 获取维度间的父子层级关系。


消歧规则

搜索指标时可能遇到歧义,按以下规则处理:

  • 匹配到多个指标:优先选北极星指标(is_north_star=true)。若仍有多个候选,结合指标类型和标签综合判断,必要时向用户确认。
  • 精确名称 vs 同义词:若同时出现精确名称匹配和同义词匹配,精确名称优先。例如搜索"DAU",若同时命中指标名为"DAU"的指标和同义词含"DAU"的"访问用户数",取前者。
  • 同名指标跨业务域:若同一指标名出现在多个业务域中,用当前分析任务的业务域限定范围。
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 58 lines · 58 tokens per session scan A d6a70b0a0a05

Subscribe to this mod's changes

bi-semantic-layer-guide is a skill published in the GitHub repository agentscope-ai/QwenPaw-Data (71 stars, last pushed yesterday), licensed Apache-2.0. It adds 58 tokens to every session and 715 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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