Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/santoshkanthety/powerbi-agentnpx agentmods add skills/santoshkanthety/powerbi-agent/powerbi-bpa-rulesWrote 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.
[](https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-bpa-rules)<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-bpa-rules"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-bpa-rules/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.
<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-bpa-rules"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-bpa-rules.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00091 | $0.04167 |
| Opus 5 | $0.00046 | $0.02083 |
| Sonnet 5 | $0.00018 | $0.00833 |
| Haiku 4.5 | $0.00009 | $0.00417 |
Grade A, and why
powerbi-bpa-rules 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 396 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Best Practice Analyzer Rules
Expert guidance for creating and improving BPA (Best Practice Analyzer) rules for Tabular Editor and Power BI semantic models.
When to Use This Skill
Activate automatically when tasks involve:
- Creating new BPA rules for semantic model validation
- Recommending or choosing BPA rules for a model, team, or organization
- Improving or debugging BPA rule expressions
- Writing FixExpression to auto-remediate rule violations
- Understanding BPA annotations in TMDL files
- Analyzing a semantic model against best practices
- Converting ad-hoc checks into reusable BPA rules
- Auditing or discovering all BPA rules across sources (built-in, URL, model, user, machine)
Primary Workflow: Interactive Q&A Discovery (Double Diamond)
CRITICAL: Do NOT generate BPA rules immediately. This is a requirements-gathering exercise. Use the AskUserQuestion tool to conduct an iterative, back-and-forth conversation with the user across multiple rounds. Continue asking questions until sufficient context about the user's business, team, model, and priorities has been gathered. Only then move to rule generation.
The workflow follows a double-diamond pattern:
- Diverge -- broadly explore the user's context, organization, and goals
- Converge -- narrow down to specific priorities and constraints
- Diverge -- explore the model structure and identify candidate rule areas
- Converge -- select and generate the final tailored rule set
Diamond 1: Requirements Gathering (Phases 1-2)
Phase 1: Understand the User and Organization
Call AskUserQuestion with 2-4 questions per round. After each round, review the answers and ask follow-up questions. Do not proceed to Phase 2 until the organizational context is clear. Continue rounds until satisfied.
Round 1 -- Goal and audience:
Ask about the primary goal and who will use the rules. Example AskUserQuestion call:
- Question 1: "What is the primary goal for these BPA rules?" -- options: "Set up BPA for my team", "Improve a specific model", "Create governance/compliance rules", (Other)
- Question 2: "Who will use these rules?" -- options: "Solo developer", "Small team (2-5)", "Large org / multiple teams", (Other)
- Question 3: "What tooling do you use?" -- options: "Tabular Editor 3", "Tabular Editor 2", "TE CLI in CI/CD", "Fabric notebooks"
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.
- 12d ago First seen · 396 lines · 91 tokens per session scan A 7d3649d1955b
powerbi-bpa-rules is a skill published in the GitHub repository santoshkanthety/powerbi-agent (2 stars, last pushed 13d ago), licensed MIT. It adds 91 tokens to every session and 4,167 once invoked, about $0.0005 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.
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