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ads-copilot: Skill for Claude Code

.github/skills/fabric-ads-session/SKILL.md

fabric-ads-session is a skill for Claude Code, Codex from HaoZhang615/ads-copilot. It costs 127 tokens per session (2,278 once invoked), scanned A, original, MIT.

A domain guide for running Microsoft Fabric Architecture Design Sessions, structured conversations used to gather requirements and shape an analytics solution. Microsoft Fabric is Microsoft's platform for data engineering, warehousing, real-time analysis, business intelligence, and data science.

In plain words
What is it for?
Use it to discuss projects such as Synapse migrations, Power BI capacity changes, self-service analytics, real-time intelligence, data mesh, governance, and related Fabric designs.
Why use it?
It gives the session facilitator Fabric-specific questions, components, and design patterns instead of requiring them to recall the whole platform during the discussion.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code.

This is HaoZhang615/ads-copilot's own configuration. It tells Claude Code and Codex how to work on ads-copilot itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ads-copilot configures →

not rated 2repo 6mo ago A scan 127 tokens original MIT
View source ↗ HaoZhang615/ads-copilot
Reuse

Borrowing it

Nothing to install: this file belongs to HaoZhang615/ads-copilot. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/HaoZhang615/ads-copilot/main/.github/skills/fabric-ads-session/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/HaoZhang615/ads-copilot

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 fabric-ads-session

README.md
[![agentmods](https://agentmods.dev/badge/skills/haozhang615/ads-copilot/fabric-ads-session/github.svg)](https://agentmods.dev/skills/haozhang615/ads-copilot/fabric-ads-session)
Your own site
<a href="https://agentmods.dev/skills/haozhang615/ads-copilot/fabric-ads-session"><img src="https://agentmods.dev/badge/skills/haozhang615/ads-copilot/fabric-ads-session/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 fabric-ads-session

Your own site · 80×15
<a href="https://agentmods.dev/skills/haozhang615/ads-copilot/fabric-ads-session"><img src="https://agentmods.dev/badge/skills/haozhang615/ads-copilot/fabric-ads-session.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,278 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.
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 $0.00127 $0.02278
Opus 5 $0.00063 $0.01139
Sonnet 5 $0.00025 $0.00456
Haiku 4.5 $0.00013 $0.00228

Measured 10d ago against content hash 48be940428b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

fabric-ads-session 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.

The scan reads SKILL.md. This mod also ships 2 executable files (fabric-ads-session/scripts/generate_architecture.py, scripts/generate_architecture.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.github/skills/fabric-ads-session/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Microsoft Fabric ADS Session

This skill provides domain-specific knowledge for Microsoft Fabric to be used within an Architecture Design Session. The ADS methodology (persona, pacing, session structure, decision narration, trade-off framework, self-critique) is defined in the runtime system prompt — this skill supplies the Fabric-specific questions, patterns, components, and references that the methodology operates on.

Domain: Microsoft Fabric

This skill covers the Microsoft Fabric unified analytics platform including:

  • Data Engineering: Spark Notebooks, Data Factory Pipelines, Dataflows Gen2, OneLake, Lakehouse, Delta Lake (Parquet)
  • Data Warehousing: Fabric Warehouse (T-SQL), SQL Analytics Endpoint (read-only T-SQL over Lakehouse), Direct Lake mode
  • Real-Time Intelligence: Eventhouse, KQL Database, Eventstreams, Data Activator, Real-Time Dashboards
  • Business Intelligence: Power BI (native), Semantic Models, Direct Lake, Paginated Reports, Copilot in Power BI
  • Data Science: ML Models, Experiments, PREDICT function, Spark MLlib
  • Governance: Microsoft Purview integration, Sensitivity Labels, Endorsement, Domains, Data Lineage
  • Infrastructure: Capacity Units (F SKUs), OneLake Shortcuts, Mirroring, Managed Private Endpoints, Deployment Pipelines

Phase-Specific Fabric Questions

Phase 1: Context Discovery

Ask about:

  • Business problem or opportunity driving this initiative
  • Industry and regulatory context
  • Greenfield project vs. migration from existing system (Synapse, Power BI Premium, on-prem SQL, Databricks)
  • Key stakeholders and decision-makers
  • Timeline and budget constraints
  • Success criteria (what does "done" look like?)
  • KPIs, latency targets, and cost envelope
  • Microsoft 365 licensing (E3/E5) — determines Fabric capacity entitlements

Adapt: If user mentions migration, read references/migration-patterns.md. If user names a specific industry, read references/industry-templates.md for starter context.

Read the full file on GitHub · 172 lines

Files

What ships with it

20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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 · 172 lines · 127 tokens per session scan A 48be940428b7

Subscribe to this mod's changes

fabric-ads-session is a skill published in the GitHub repository HaoZhang615/ads-copilot (2 stars, last pushed 6mo ago), licensed MIT. It adds 127 tokens to every session and 2,278 once invoked, about $0.0006 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 2026-08-31.

Analytics and metricsPlanningarchitectureazurecopilotdatabricksfastapimermaid
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