Agent skill

Standardize Naming Conventions

by data-goblin in data-goblin/power-bi-agentic-development

Interactive naming convention standardization for TMDL-based Power BI semantic models.

GPL-3.0Auto-check passedData & Analytics

Install Standardize Naming Conventions

skills CLI
$ npx skills add data-goblin/power-bi-agentic-development --skill standardize-naming-conventions -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install data-goblin/power-bi-agentic-development standardize-naming-conventions --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/data-goblin/power-bi-agentic-development.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/semantic-models/skills/standardize-naming-conventions .claude/skills/standardize-naming-conventions && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
standardize-naming-conventions
GitHub stars
1k
Token cost
~1.8k tokens
SKILL.md length
788 words
Files
2 (incl. references)
Skills in repo
33
Repo updated
First seen
Licence
GPL-3.0

At a glance

Interactive naming convention standardization for TMDL-based Power BI semantic models.

  • Works in 5 steps: Discover the Model → Understand Business Context → Audit and Report → …
  • Asks to standardize naming conventions
  • SKILL.md covers Primary Workflow, Naming Convention Rules, Key Anti-Patterns to Detect and Downstream Report Impact, plus 1 more section
  • Calls rg

What it does

Standardize Naming Conventions is an agent skill from data-goblin/power-bi-agentic-development. Interactive naming convention standardization for TMDL-based Power BI semantic models. Automatically invoke when the user asks to "standardize naming conventions", "fix naming conventions", "clean up model names", "apply naming standards", "audit naming", "make names human readable", "rename fields", "fix abbreviations in model", or mentions renaming measures, columns, or tables for consistency across a model.

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/naming-rules.md`).

It sits in Data & Analytics. It works with Power BI. The repository describes itself as: Power BI AI skills and Power BI agents for Claude Code and GitHub Copilot: a plugin marketplace of Power BI skills, subagents, and hooks for semantic models, DAX, TMDL, reports… The licence is GPL-3.0.

When your agent uses it

  • Asks to standardize naming conventions
  • Fix naming conventions
  • Clean up model names
  • Apply naming standards

Example prompts

  • “standardize naming conventions”
  • “fix naming conventions”
  • “clean up model names”
  • “/standardize-naming-conventions”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Discover the Model
  2. Understand Business Context
  3. Audit and Report
  4. Apply Changes
  5. Validate

What it can do on your machine

Read from SKILL.md and the folder at commit a301717. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • rg

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Standardize Naming Conventions loads about 1.8k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 111 tokens; SKILL.md has 788 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from data-goblin/power-bi-agentic-development at commit a301717, republished under its GPL-3.0 licence (© data-goblin). 788 words, ~1,824 tokens.

Download SKILL.mdSave it as .claude/skills/standardize-naming-conventions/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
standardize-naming-conventions
description
Interactive naming convention standardization for TMDL-based Power BI semantic models. Automatically invoke when the user asks to "standardize naming conventions", "fix naming conventions", "clean up model names", "apply naming standards", "audit naming", "make names human readable", "rename fields", "fix abbreviations in model", or mentions renaming measures, columns, or tables for consistency across a model.

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:

bash
# 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:

  1. Business terminology: "What terminology does your organization use for key metrics? For example, do you call it Revenue, Turnover, Sales, or Gross Sales?"
  2. Existing conventions: "Do you have any documented naming conventions or standards already?"
  3. Period conventions: "How do you typically refer to prior periods? (e.g., 1YP, PY, Prior Year, Last Year)"
  4. Unit conventions: "How do you typically express units in measure names? (e.g., parentheses like (%), (Value), (Quantity))"
  5. 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

Before making changes, produce an audit report. Present a markdown table showing each proposed rename:

| Object Type | Current Name | Proposed Name | Issues Found |
|-------------|-------------|---------------|-------------|
| Table | FACT_Invoices | Invoices | Technical prefix |
| Measure | NetSls | Net Sales | CamelCase, abbreviation |
| Column | shp_dt | Ship Date | snake_case, abbreviation |

Group findings by issue type:

  • Programming conventions: CamelCase, snake_case, UPPER_CASE
  • Abbreviations/acronyms: Shortened or opaque names
  • Inconsistent syntax: Mixed period, unit, or aggregation patterns
  • Technical prefixes: DIM_, FACT_, STG_ on tables
  • Missing descriptions: Objects without /// docstrings
  • Disorganized folders: Missing or flat display folder hierarchy

Ask the user to confirm or adjust the proposed renames before proceeding.

Phase 4: Apply Changes

After user approval, edit the TMDL files. For each table file:

  1. Rename the table (if needed): Change the table declaration
  2. Rename measures: Change measure names in their declarations. IMPORTANT: Also update all internal DAX references to renamed measures using [Old Name] -> [New Name] patterns across ALL table files in the model
  3. Rename columns: Change column names in their declarations. IMPORTANT: Also update DAX references using 'Table'[Old Column] -> 'Table'[New Column] across ALL table files
  4. Reorganize display folders: Add or restructure displayFolder: properties
  5. Add descriptions: Add /// comments for measures and columns that lack them
  6. Update relationship references: Check relationships.tmdl for renamed tables/columns

Cross-file reference updates are critical. When renaming a measure or column, search the entire definition/ directory for all references:

bash
# Find all references to a renamed measure
rg "OldMeasureName" <path>/definition/tables/
rg "OldMeasureName" <path>/definition/relationships.tmdl
Show full SKILL.md (332 more words)Show less
Phase 5: Validate

After applying changes, verify:

  1. All TMDL files still parse correctly (no syntax errors)
  2. No orphaned references to old names remain in any file
  3. Display folders are consistent across tables
  4. Descriptions are present on all visible measures and columns

Run a final search to check for any missed references:

bash
# Check for any remaining old names
rg -n "old_name_pattern" <path>/definition/

Naming Convention Rules

Consult references/naming-rules.md for the complete rule set including:

  • Human-readable name requirements
  • Abbreviation and acronym rules
  • Technical prefix rules
  • Aggregation, unit, and period syntax standards
  • Display folder organization patterns
  • Measure name construction order: [Aggregation] [Base Name] [Period] ([Unit])
  • Column naming patterns

Key Anti-Patterns to Detect

Quick-reference checklist for the most common issues:

Anti-PatternRuleExample Fix
snake_caseUse spacesnet_sales -> Net Sales
CamelCaseUse spacesNetSales -> Net Sales
UPPER_CASEUse spacesTOTAL_COST -> Total Cost
AbbreviationsSpell outDel. Mrgn -> Delivery Margin
Opaque acronymsSpell outTFS -> Total Freight Surcharge
Technical prefixRemoveFACT_Orders -> Orders
Inconsistent periodsStandardizeLY/PY/Last Year -> 1YP
Inconsistent unitsStandardizepct/%/(%) -> (%)
Missing descriptionsAdd/// docstrings on all visible objects
Flat foldersOrganizeNumbered hierarchy with subfolders

Downstream Report Impact

WARNING: Renaming model objects breaks downstream report visuals that reference those fields. After renaming:

  1. Identify all connected reports (.pbir files or Power BI Service reports)
  2. Rebind visuals to use the new field names
  3. Repair each report with pbir fields replace or pbir fields replace-table; never edit report JSON directly

Always warn the user about this before applying renames. If downstream reports exist, consider:

  • Making a backup of the model before changes
  • Planning a rebinding session after the rename
  • Using a C# script in Tabular Editor to batch-rename with rebinding

Additional Resources

Reference Files
  • references/naming-rules.md -- Complete naming convention rules with detection patterns, anti-pattern tables, and the measure name construction order
Fetching Docs

To retrieve current semantic model and TMDL reference docs, use microsoft_docs_search + microsoft_docs_fetch (MCP) if available, otherwise mslearn search + mslearn fetch (CLI). Search based on the user's request and run multiple searches as needed to ensure sufficient context before proceeding.

© data-goblin, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in plugins/semantic-models/skills/standardize-naming-conventions of data-goblin/power-bi-agentic-development.

  • SKILL.md
  • references/naming-rules.md

Open the folder on GitHubat commit a301717

Compare with similar skills

Standardize Naming Conventions next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Standardize Naming Conventions compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Standardize Naming Conventions this skilldata-goblin/power-bi-agentic-development1k—~1.8kAutomated safety check: PassGPL-3.0
Power Bi AI ReadinessDKH-DK/Self-Service-Power-BI-Fabric113—~2kAutomated safety check: PassNone
Pbi Report Builderlukasreese/powerbi-claude-skills128—~7.5kAutomated safety check: PassNone
Pbi Docxperiun/skills-xperiun-free116—~3kAutomated safety check: PassMIT
Pbip Dependency Analyzerlukasreese/powerbi-claude-skills128—~3.2kAutomated safety check: PassNone
Pbi Modelo Reviewxperiun/skills-xperiun-free116—~2.9kAutomated safety check: PassMIT

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Works with

Questions about Standardize Naming Conventions

What does Standardize Naming Conventions do?

Interactive naming convention standardization for TMDL-based Power BI semantic models. Standardize Naming Conventions is an agent skill from data-goblin/power-bi-agentic-development. Interactive naming convention standardization for TMDL-based Power BI semantic models.

When should I use Standardize Naming Conventions?

Standardize Naming Conventions fits situations like: asks to standardize naming conventions; fix naming conventions; clean up model names; apply naming standards.

How do I install Standardize Naming Conventions in Claude Code?

Run `npx skills add data-goblin/power-bi-agentic-development --skill standardize-naming-conventions -a claude-code`. Or copy the skill folder (plugins/semantic-models/skills/standardize-naming-conventions in data-goblin/power-bi-agentic-development) into .claude/skills/standardize-naming-conventions in your project. Claude Code loads it when a task matches its description.

How do I install Standardize Naming Conventions in Codex?

Run `npx skills add data-goblin/power-bi-agentic-development --skill standardize-naming-conventions -a codex`. Or copy the skill folder (plugins/semantic-models/skills/standardize-naming-conventions in data-goblin/power-bi-agentic-development) into .agents/skills/standardize-naming-conventions in your project. Codex loads it when a task matches its description.

Can I use Standardize Naming Conventions in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add data-goblin/power-bi-agentic-development --skill standardize-naming-conventions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/standardize-naming-conventions, .gemini/skills/standardize-naming-conventions, .github/skills/standardize-naming-conventions and .opencode/skills/standardize-naming-conventions in your project.

What does Standardize Naming Conventions need to run?

Going by SKILL.md and its folder, Standardize Naming Conventions needs the command-line tools its instructions call (rg).

Does Standardize Naming Conventions access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Standardize Naming Conventions safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Standardize Naming Conventions use?

Standardize Naming Conventions is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Standardize Naming Conventions use?

About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2k tokens, read only when the agent opens those files.

What are the alternatives to Standardize Naming Conventions?

Skills that share tags, products or a category with Standardize Naming Conventions: Power Bi AI Readiness (DKH-DK/Self-Service-Power-BI-Fabric, 113 stars), Pbi Report Builder (lukasreese/powerbi-claude-skills, 128 stars), Pbi Doc (xperiun/skills-xperiun-free, 116 stars) and Pbip Dependency Analyzer (lukasreese/powerbi-claude-skills, 128 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Standardize Naming Conventions?

data-goblin (a GitHub user) maintains it in data-goblin/power-bi-agentic-development, which has 1,031 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 7, 2026.

Source: data-goblin/power-bi-agentic-development on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.