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 skills add santoshkanthety/powerbi-agent --skill powerbi-standardize-naming-conventionsgit clone --depth 1 https://github.com/santoshkanthety/powerbi-agentWrote 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-standardize-naming-conventions)<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-standardize-naming-conventions"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-standardize-naming-conventions/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-standardize-naming-conventions"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-standardize-naming-conventions.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 | $0.00090 | $0.01654 |
| Opus 5 | $0.00045 | $0.00827 |
| Sonnet 5 | $0.00018 | $0.00331 |
| Haiku 4.5 | $0.00009 | $0.00165 |
Grade A, and why
powerbi-standardize-naming-conventions 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Standardize Naming Conventions
Interactive workflow for auditing and standardizing naming conventions in Power BI semantic models stored as TMDL files. Ensures tables, columns, measures, and display folders follow human-readable, consistent, business-aligned naming standards.
Primary Workflow
Phase 1: Discover the Model
Locate the TMDL files. Ask the user for the path to the .SemanticModel/definition/ directory if not obvious from context. Then scan the model structure:
# Count tables and get an overview
ls <path>/tables/*.tmdl
Read all table TMDL files to build a complete picture of current naming patterns. Focus on:
- Table names (check for DIM_, FACT_, or other technical prefixes)
- Measure names (check for abbreviations, programming conventions, inconsistent syntax)
- Column names (check for CamelCase, snake_case, abbreviations)
- Display folder structure (check for organization and consistency)
- Presence of descriptions (
///comments)
Phase 2: Understand Business Context
CRITICAL: Do not rename anything without understanding the business terminology.
Use AskUserQuestion to gather context:
- Business terminology: "What terminology does your organization use for key metrics? For example, do you call it Revenue, Turnover, Sales, or Gross Sales?"
- Existing conventions: "Do you have any documented naming conventions or standards already?"
- Period conventions: "How do you typically refer to prior periods? (e.g., 1YP, PY, Prior Year, Last Year)"
- Unit conventions: "How do you typically express units in measure names? (e.g., parentheses like (%), (Value), (Quantity))"
- Downstream impact: "Are there downstream reports connected to this model that would need visual rebinding after renaming?"
Adapt the naming rules to the user's business context. The rules in references/naming-rules.md are defaults -- override them when the user's organization has established conventions.
Phase 3: Audit and Report
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 · 148 lines · 90 tokens per session scan A 8be6e8b85a18
powerbi-standardize-naming-conventions is a skill published in the GitHub repository santoshkanthety/powerbi-agent (2 stars, last pushed 13d ago), licensed MIT. It adds 90 tokens to every session and 1,654 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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