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.
npx agentmods add skills/luccapinto/agentic-data-kit/pbi-quality-rulesnpx skills add luccapinto/agentic-data-kit --skill pbi-quality-rulesgit clone --depth 1 https://github.com/luccapinto/agentic-data-kitWrote 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/luccapinto/agentic-data-kit/pbi-quality-rules)<a href="https://agentmods.dev/skills/luccapinto/agentic-data-kit/pbi-quality-rules"><img src="https://agentmods.dev/badge/skills/luccapinto/agentic-data-kit/pbi-quality-rules.svg" alt="Measured on agentmods" 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 | $0.00040 | $0.00560 |
| Opus 5 | $0.00020 | $0.00280 |
| Sonnet 5 | $0.00008 | $0.00112 |
| Haiku 4.5 | $0.00004 | $0.00056 |
Grade A, and why
pbi-quality-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 4d 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 — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: pbi-quality-rules
Run the Best Practice Analyzer (BPA) — the industry-standard model linter — against a PBIP semantic model. This skill uses the real BPA engine from Tabular Editor 2 (free, open source) instead of a homegrown checker, so results match what Power BI developers expect and the rules are portable.
Rule set
bpa-rules.json (next to this file) holds the team's BPA rules in Tabular Editor's native
format (ID, Name, Category, Severity, Scope, Expression in Dynamic LINQ over the
TOM). Severity: 3 = error, 2 = warning, 1 = info. Edit this file to add or tune rules;
it loads directly into Tabular Editor's BPA UI too.
Primary path — Tabular Editor 2 CLI (recommended)
Requires Tabular Editor 2 (free). Desktop should be closed so disk reflects the latest state.
# Windows (TabularEditor.exe on PATH). Point at the .SemanticModel folder (TMDL) or model.bim.
TabularEditor.exe "Sales.SemanticModel" -A ".agent/skills/pbi-quality-rules/bpa-rules.json" -V
-A <rulesfile>runs the BPA with the given rules;-Vwrites violations to the console (and sets a non-zero exit code on error-severity hits — useful in CI).- The cross-platform
teCLI (preview) accepts the same rules file if installed instead.
Parse the console output, then present errors and warnings only (omit info unless asked).
Fallback — no Tabular Editor installed
The kit stays usable without the tool. Parse the TMDL files directly and evaluate the same
rules by hand: for each rule, read its Scope and Expression from bpa-rules.json and apply
the equivalent check to the parsed objects (measures, tables, columns, relationships). This is
less robust than the real BPA — say so, and recommend installing Tabular Editor 2 for accuracy.
Agent flow
- Run after large model edits / refactors, or on demand.
- Show errors first; for each
error, offer an immediate fix. Forwarning, suggest but don't force. Group by category so the report is scannable.
What ships with it
1 file 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.
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.
- 4d ago First seen · 43 lines · 40 tokens per session scan A 72f3ba938c51
pbi-quality-rules is a skill published in the GitHub repository luccapinto/agentic-data-kit (7 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 560 once invoked, about $0.0002 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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