Pytorch Clickhouse
pytorch/test-infra
Load this FIRST whenever working with PyTorch CI data (any pytorch/ org repo), the torchci/HUD codebase, or the PyTorch HUD ClickHouse database.
This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a…
Install Semantic Model
$ npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install data-goblin/power-bi-agentic-development semantic-model --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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/semantic-model .claude/skills/semantic-model && rm -rf skills-srcUse ~/.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/
Install the "semantic-model" agent skill from https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-model into .claude/skills/semantic-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "semantic-model", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-modelType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install data-goblin/power-bi-agentic-development semantic-model --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/data-goblin/power-bi-agentic-development.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/semantic-models/skills/semantic-model .agents/skills/semantic-model && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "semantic-model" agent skill from https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-model into .agents/skills/semantic-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "semantic-model", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install data-goblin/power-bi-agentic-development semantic-model --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/data-goblin/power-bi-agentic-development.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/semantic-models/skills/semantic-model .cursor/skills/semantic-model && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "semantic-model" agent skill from https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-model into .cursor/skills/semantic-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "semantic-model", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/data-goblin/power-bi-agentic-development.git --path plugins/semantic-models/skills/semantic-model--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install data-goblin/power-bi-agentic-development semantic-model --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/data-goblin/power-bi-agentic-development.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/semantic-models/skills/semantic-model .gemini/skills/semantic-model && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "semantic-model" agent skill from https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-model into .gemini/skills/semantic-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "semantic-model", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install data-goblin/power-bi-agentic-development semantic-modelInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/data-goblin/power-bi-agentic-development.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/semantic-models/skills/semantic-model .github/skills/semantic-model && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "semantic-model" agent skill from https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-model into .github/skills/semantic-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "semantic-model", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install data-goblin/power-bi-agentic-development semantic-model --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/data-goblin/power-bi-agentic-development.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/semantic-models/skills/semantic-model .opencode/skills/semantic-model && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "semantic-model" agent skill from https://github.com/data-goblin/power-bi-agentic-development/tree/main/plugins/semantic-models/skills/semantic-model into .opencode/skills/semantic-model/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "semantic-model", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
semantic-model- GitHub stars
- 1k
- Token cost
- ~2.8k tokens
- SKILL.md length
- 972 words
- Files
- 30 (incl. scripts, references)
- Skills in repo
- 33
- Repo updated
- First seen
- Licence
- GPL-3.0
At a glance
This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a…
- Works in 3 steps: te CLI first. One verb per operation,… → TOM, or a model MCP, when te cannot… → fab + direct TMDL last, with the tmdl…
- Tasks that involve Query optimization
- SKILL.md covers When to use, When NOT to use, Tool cascade (the core… and Lifecycle, plus 4 more sections
- Tasks that involve Data warehousing
What it does
Semantic Model is an agent skill from data-goblin/power-bi-agentic-development. This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a measure", "add a relationship", "create a role" / "set up RLS", "add a calculation group", "set up incremental refresh", "fix a star schema", "reduce model size", "prepare a model for Copilot / AI", or "check model quality". Covers the full lifecycle (design, build, refresh, review) and drives every operation through the te…
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 30 other files, including scripts and reference files (for example `references/aggregations.md`, `references/ai-copilot-readiness.md` and `references/calculation-groups.md`).
It sits in Databases, covering Query optimization and Data warehousing. It works with Model Context Protocol. 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
- Tasks that involve Query optimization
- Tasks that involve Data warehousing
Example prompts
- “semantic model”
- “data model”
- “dataset”
- “/semantic-model”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- te CLI first. One verb per operation, staged in memory until --save, with a save-time DAX + referential-integrity gate. Covers…
- TOM, or a model MCP, when te cannot reach a property. Some properties are absent from te set -p (for example alternateOf…
- fab + direct TMDL last, with the tmdl skill. Service- and file-shape operations with no model-edit verb: assigning Entra principals to…
What it can do on your machine
Read from SKILL.md and the folder at commit 41886f2. 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
Ships 1 file in scripts/, which the agent can run.
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
Semantic Model loads about 2.8k tokens when it runs, and up to ~39k if it reads all its reference files. Until then it costs about 178 tokens; SKILL.md has 972 words of instructions outside code blocks.
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); the scripts in this folder are not scanned.
SKILL.md
The full file from data-goblin/power-bi-agentic-development at commit 41886f2, republished under its GPL-3.0 licence (© data-goblin). 972 words, ~2,788 tokens.
Download SKILL.mdSave it as
.claude/skills/semantic-model/SKILL.md (or your agent's skills folder). This skill also uses 29 other files; get the full folder from GitHub.- name
- semantic-model
- description
- This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a measure", "add a relationship", "create a role" / "set up RLS", "add a calculation group", "set up incremental refresh", "fix a star schema", "reduce model size", "prepare a model for Copilot / AI", or "check model quality". Covers the full lifecycle (design, build, refresh, review) and drives every operation through the `te` CLI first, then TOM (connect-pbid) or a model MCP, then TMDL authoring (the tmdl skill). Not for report visuals (use pbir-cli) or isolated DAX query tuning (use the dax skill).
Semantic models: design, build, refresh, review
Guidance for designing, building, refreshing, and reviewing Power BI / Analysis Services tabular models from the terminal. It consolidates model review with modeling best practices, and routes every change to the narrowest capable tool. Depth lives in references/; this file is the operating loop and the routing.
When to use
- Designing or building a model: star schema, relationships, measures, calculation groups, roles, parameters, storage modes, incremental refresh
- Optimizing a model: size / VertiPaq, DAX correctness, Direct Lake, refresh cost
- Reviewing or auditing a model against quality, performance, and best-practice standards
- Preparing a model for Copilot / AI consumption
When NOT to use
- Editing report visuals, pages, or formatting: use the
pbir-cliskill (reports plugin) - Isolated DAX query performance tuning: use the
daxskill - TMDL file syntax mechanics: use the
tmdlskill (this skill routes to it for the file-edit fallback) - The
tecommand surface itself: thete-cliskill (tabular-editor plugin) is the command reference; this skill is the modeling judgment layered on top
Tool cascade (the core operating rule)
Reach for the narrowest capable tool, in order. Most edits never leave step 1.
teCLI first. One verb per operation, staged in memory until--save, with a save-time DAX + referential-integrity gate. Covers add/set/rm/mv for measures, columns, relationships (Sales[K]->Dim[K]shorthand onte add), roles + RLS filters, calculation groups / items, DAX formatting (te set <path> --format Expression, orte script --inline "Model.AllMeasures.FormatDax();"for the whole model),te bpa,te vertipaq,te query. Each Bash call is a fresh shell, so pass--model <path>(or-s/-dfor remote) on every command, or setTE_SESSION. Properties are-p Name=Value; read the real object's settable surface first withte get <obj> --properties. Every mutation is a dry run until--save. Thete-cliskill is the full command reference.- TOM, or a model MCP, when
tecannot reach a property. Some properties are absent fromte set -p(for examplealternateOf,securityFilteringBehavior,crossFilteringBehavior, KPI sub-objects, linguistic-schema content, calendar objects). Drive these through ate scriptC# pass (in-process TOM), or theconnect-pbidskill (PowerShell + TOM/ADOMD against a live local Desktop instance, and the only route to traces:EVALUATEANDLOG, aggregation-hit events, storage DMVs). The Power BI Modeling MCP server is also available if you prefer an MCP. The local Desktop proxy cannot reach Direct Lake; use a remote XMLA endpoint there. fab+ direct TMDL last, with thetmdlskill. Service- and file-shape operations with no model-edit verb: assigning Entra principals to roles (workspace-side, not in.tmdl), report-to-model binding, Copilot-folder features (AI instructions, AI data schema, verified answers), Lakehouse / Delta reshaping behind Direct Lake, and bulk structural surgery that is cleaner as one TMDL diff than Ntecalls. For read-only Fabric retrieval of AI instructions / schema, usescripts/get_semantic_model_ai_metadata.py. Author the TMDL with thetmdlskill, then runte validate.
Ordering gate: add relationships before any measure that uses RELATED() or a cross-table CALCULATE(), or the save gate fails with DAX0002 (no relationship in context).
Lifecycle
Design
Model dimensionally: a star of fact plus conformed dimensions beats snowflakes and fact-to-fact joins. Decide storage mode and refresh strategy before building; both are near one-way doors once published. See references/dimensional-modeling.md, references/storage-modes.md, references/composite-models.md, and references/direct-lake.md.
Build
Make each change through the cascade above. Author measures with full metadata (DisplayFolder, FormatString, Description) in one pass. Validate after every mutation (te validate) and gate on BPA (te bpa run --fail-on error). Renaming or moving any object can silently break downstream reports and models; run the lineage check first, then propagate with pbir-cli / fabric-cli (see references/refactoring-renaming.md). Deep guidance per area: references/relationships.md, references/time-intelligence.md, references/calculation-groups.md, references/parameters.md, references/security.md, references/dax-authoring.md.
Show full SKILL.md (374 more words)Show less
Refresh
Configure incremental refresh from the terminal (te incremental-refresh); for Direct Lake, the refresh is the framing. See references/incremental-refresh.md, and the refresh-semantic-model skill for monitoring and troubleshooting.
Review
Audit against the categories below and produce prioritized findings with file locations. Gather context first with scripts/get_model_info.py (storage mode, size, connected reports, endorsement, data sources, refresh schedule). Full checklist in references/review-checklist.md; performance method in references/performance.md.
Review categories (by severity)
- Critical: bidirectional ambiguity, circular dependencies, missing data types, orphaned tables, fail-open RLS, limited relationships that silently drop rows
- Memory & size: high-cardinality dictionaries, auto attribute hierarchies (
isAvailableInMDXon hidden / high-cardinality columns), unsplit DateTime, auto date/time tables, wrong data types, calc columns that should be measures, unused objects - Data reduction: unfiltered fact history (no incremental refresh), unnecessary columns, detail grain not needed for reporting, logic better pushed upstream
- DAX correctness: filtering tables not columns in CALCULATE, unguarded division, context-blind calc columns, variable time-shift bugs (
references/dax-authoring.md; for query tuning use thedaxskill) - Measure hygiene: implicit measures, report-scoped measures that belong in the model, ambiguous duplicates
- Documentation & AI: missing descriptions (Copilot truncates after 200 characters), missing display folders, missing synonyms, inconsistent naming (use
standardize-naming-conventions) - Design: star-schema violations, mis-marked date table, many-to-many without a bridge, dead inactive relationships
- Direct Lake: non-unique one-side keys (queries fail at runtime), DirectQuery fallback, calculated-column support by Direct Lake flavor, Delta guardrail breaches
Related skills
tmdl: TMDL file authoring (the cascade's step-3 fallback)dax: DAX query performance optimizationconnect-pbid: TOM / ADOMD via PowerShell against a live Desktop instance; traces; the TOM / MCP tierte-cli: thetecommand referencec-sharp-scripting: TOM C# scripts and macros (te script) for propertiestecannot reachstandardize-naming-conventions: naming audit and remediationrefresh-semantic-model: refresh monitoring and troubleshootinglineage-analysis: artifact lineage (downstream reports and models that consume this model, across workspaces); distinct from intra-model object dependenciesbpa-rules(tabular-editor): authoring BPA rules;fabric-cli: service / workspace operations
Reference map
references/dimensional-modeling.md: star schema, SCD2, junk / degenerate dimensions, header-detail, bridges
references/relationships.md: cardinality, limited relationships, ambiguity, active / inactive, USERELATIONSHIP
references/time-intelligence.md: classic vs calendar TI, mark-as-date traps, week-based / 4-4-5
references/calculation-groups.md: precedence, sideways recursion, selection expressions, the variant trap
references/parameters.md: field parameters, what-if parameters, dynamic titles
references/security.md: RLS validation + defensive filters, bidirectional + RLS, OLS restrictions
references/query-semantic-model.md: querying a model with DAX, INFO functions, output formats, probing
references/storage-modes.md: Import / DirectQuery / Dual / Hybrid decision matrix
references/composite-models.md: source groups, regular vs limited, Direct-Lake-plus-Import
references/aggregations.md: user-defined aggregations, grain, te-script AlternateOf
references/direct-lake.md: OneLake vs SQL, framing, DirectQuery fallback, guardrails
references/incremental-refresh.md: IR policy, detect data changes, hybrid / real-time, refresh strategy
references/vertipaq-optimization.md: VPA metrics, value vs hash encoding, splitting high-cardinality keys
references/dax-authoring.md: variable semantics, DIVIDE, measure vs calc column (gaps vs the dax skill)
references/ai-copilot-readiness.md: the Copilot grounding contract, synonyms / linguistic schema, descriptions, Q&A retirement
references/metadata-and-organization.md: descriptions, display folders, naming, measure tables, perspectives
references/hierarchies-cultures.md: user hierarchies, parent-child, KPIs, perspectives, cultures / translations
references/documentation-and-bpa.md: data dictionary, BPA documentation gate, metadata diffs, intra-model impact analysis (artifact lineage = the lineage-analysis skill)
references/refactoring-renaming.md: safe rename workflow (lineage check first, then propagate via pbir-cli / fabric-cli)
references/review-checklist.md: full audit checklist with remediation
references/performance.md: performance testing, unused-column detection, memory analysis
scripts/get_model_info.py: model metadata overview (mode, size, reports, endorsement, sources, refresh)
scripts/manage-ai-metadata.csx: read/write AI instructions and AI schema through TOM culture linguistic metadata
scripts/get_semantic_model_ai_metadata.py: Fabric CLI service-definition readback for AI instructions and AI schemaWhat this skill deliberately leaves out
- GUI-tool walkthroughs and the old review skill's "use whatever tool is available" framing: superseded by the te-cli-first cascade
- Hand-authored Q&A phrasings: Q&A is being retired and Copilot does not read phrasings; invest in synonyms and descriptions
- Perspectives or display folders presented as security: both are queryable by anyone with model access; use RLS / OLS
- The PBIT format: out of scope
© 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 29 other files (scripts, references) in plugins/semantic-models/skills/semantic-model of data-goblin/power-bi-agentic-development.
- SKILL.md
- references/aggregations.md
- references/ai-copilot-readiness.md
- references/calculation-groups.md
- references/composite-models.md
- references/dax-authoring.md
- references/dimensional-modeling.md
- references/direct-lake.md
- references/documentation-and-bpa.md
- references/hierarchies-cultures.md
- references/incremental-refresh.md
- references/metadata-and-organization.md
- references/parameters.md
- references/performance.md
- references/query-semantic-model.md
- references/refactoring-renaming.md
- references/relationships.md
- references/review-checklist.md
- references/security.md
- references/storage-modes.md
- … and 10 more
Open the folder on GitHubat commit 41886f2
Compare with similar skills
Semantic Model 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Semantic Model this skilldata-goblin/power-bi-agentic-development | 1k | — | ~2.8k | Automated safety check: Pass | GPL-3.0 | |
| Pytorch Clickhousepytorch/test-infra | 113 | — | ~2.8k | Automated safety check: Pass | Custom licence | |
| Clickhouse Ioaffaan-m/ECC | 274k | 1 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Generating Clickhouse Query Performance ReportsPostHog/posthog-foss | 721 | — | ~5.1k | Automated safety check: Pass | MIT | |
| Releasehypequery/hypequery | 103 | — | ~623 | Automated safety check: Pass | Custom licence | |
| Altimate Data Warehouse DelegateAltimateAI/data-engineering-skills | 127 | — | ~1.4k | Automated safety check: Pass | MIT |
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Questions about Semantic Model
What does Semantic Model do?
This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a…. Semantic Model is an agent skill from data-goblin/power-bi-agentic-development. This skill should be used whenever the user mentions a "semantic model", "data model", or "dataset", or asks to "build", "model", "design", "optimize", "review", or "audit" one, or to "add a measure", "add a relationship", "create a role" / "set up RLS", "add a calculation group", "set up incremental refresh", "fix a star schema", "reduce model size", "prepare a model for Copilot / AI", or "check model quality".
When should I use Semantic Model?
Semantic Model fits situations like: tasks that involve Query optimization; tasks that involve Data warehousing.
How do I install Semantic Model in Claude Code?
Run `npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a claude-code`. Or copy the skill folder (plugins/semantic-models/skills/semantic-model in data-goblin/power-bi-agentic-development) into .claude/skills/semantic-model in your project. Claude Code loads it when a task matches its description.
How do I install Semantic Model in Codex?
Run `npx skills add data-goblin/power-bi-agentic-development --skill semantic-model -a codex`. Or copy the skill folder (plugins/semantic-models/skills/semantic-model in data-goblin/power-bi-agentic-development) into .agents/skills/semantic-model in your project. Codex loads it when a task matches its description.
Can I use Semantic Model 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 semantic-model -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/semantic-model, .gemini/skills/semantic-model, .github/skills/semantic-model and .opencode/skills/semantic-model in your project.
What does Semantic Model need to run?
SKILL.md names no scripts, command-line tools or credentials: Semantic Model is instructions for the agent only.
Does Semantic Model 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 Semantic Model 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Semantic Model use?
Semantic Model 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 Semantic Model use?
About 2.8k tokens (SKILL.md is roughly 11k 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 36k tokens, read only when the agent opens those files.
What are the alternatives to Semantic Model?
Skills that share tags, products or a category with Semantic Model: Pytorch Clickhouse (pytorch/test-infra, 113 stars), Clickhouse Io (affaan-m/ECC, 274k stars), Generating Clickhouse Query Performance Reports (PostHog/posthog-foss, 721 stars) and Release (hypequery/hypequery, 103 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Semantic Model?
data-goblin (a GitHub user) maintains it in data-goblin/power-bi-agentic-development, which has 1,026 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 5, 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.