Power BI Agentic Development is a marketplace of skills, plugins, agents, commands, and an MCP server that help coding agents work with Power BI and Microsoft Fabric. It is for creating and managing semantic models, DAX, TMDL, reports, dashboards, workspaces, and deployment processes, with the catalogue entries providing these specialized agent resources.
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 data-goblin/power-bi-agentic-development --skill fabric-cligit clone --depth 1 https://github.com/data-goblin/power-bi-agentic-developmentWrote 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/data-goblin/power-bi-agentic-development/fabric-cli)<a href="https://agentmods.dev/skills/data-goblin/power-bi-agentic-development/fabric-cli"><img src="https://agentmods.dev/badge/skills/data-goblin/power-bi-agentic-development/fabric-cli/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/data-goblin/power-bi-agentic-development/fabric-cli"><img src="https://agentmods.dev/badge/skills/data-goblin/power-bi-agentic-development/fabric-cli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Tool Misuse · line 362 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
- medium Memory Poisoning · line 29 Skill injects content designed to persist in agent memory or context across interactions. Persistent injection can alter agent behavior long after the initial interaction.Fix: Do not allow untrusted input to persist in agent memory or context. Validate all content before storing and implement memory isolation between sessions.
- medium Prompt Injection · line 69 Subtle instructions detected that may alter agent decision-making or introduce hidden biases.Fix: Review content for implicit steering or bias. Ensure instructions are explicit and align with the skill's stated purpose.
- medium Excessive Agency · line 323 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 369 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00133 | $0.10251 |
| Opus 5.5 | $0.00053 | $0.04100 |
| Sonnet 5.5 | $0.00027 | $0.02050 |
| Haiku 4.5 | $0.00013 | $0.01025 |
Grade A, and why
fabric-cli 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.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
41 files 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.
- examples/pyspark-notebook.ipynb 2.6 KB
- examples/python-notebook.ipynb 5.7 KB
- references/admin.md 21 KB
- references/capacity-cost.md 5.3 KB
- references/connections.md 4.3 KB
- references/dashboards.md 6.4 KB
- references/dataflows.md 13 KB
- references/deployment-pipelines.md 34 KB
- references/fab-api.md 6.2 KB
- references/fab-vs-az-cli.md 19 KB
- references/folders.md 6.8 KB
- references/gateways.md 16 KB
- references/import-download-deploy.md 13 KB
- references/lakehouses.md 6.4 KB
- references/notebooks.md 25 KB
- references/org-apps.md 7.6 KB
- references/paginated-reports.md 16 KB
- references/permissions.md 23 KB
- references/querying-data.md 31 KB
- references/reference.md 37 KB
- references/reports.md 6.0 KB
- references/scorecards.md 14 KB
- references/semantic-models.md 17 KB
- references/service-principals.md 9.3 KB
- references/sql-databases.md 2.5 KB
- references/tags.md 6.8 KB
- references/warehouses.md 2.5 KB
- references/workspaces.md 30 KB
- scripts/create_direct_lake_model.py 8.1 KB runs code
- scripts/deploy_notebook.py 12 KB runs code
- scripts/download_workspace.py 12 KB runs code
- scripts/execute_dax.py 8.2 KB runs code
- scripts/get_semantic_model_ai_metadata.py 24 KB runs code
- scripts/get-downstream-reports.py 5.6 KB runs code
- scripts/query_lakehouse_duckdb.py 9.5 KB runs code
- scripts/query_sql_endpoint.py 10 KB runs code
- scripts/query_sql_mcp.py 9.2 KB runs code
- scripts/README.md 10 KB
- scripts/run_notebook_checked.py 17 KB runs code
- scripts/search_across_workspaces.py 40 KB runs code
- scripts/task_flow.py 18 KB runs code
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 Changed · -7 lines 9d6cc00a62ed
- 8d ago Changed 27cdcb985bc2
- 21d ago Changed c7552b06539c
- 22d ago Changed · +13 lines · +81 tokens per session 4bdaed1d4ba5
- 1mo ago First seen · 617 lines · 52 tokens per session scan A dc9675993846
fabric-cli is a skill published in the GitHub repository data-goblin/power-bi-agentic-development (1,060 stars, last pushed 2d ago), licensed GPL-3.0. It adds 133 tokens to every session and 10,251 once invoked, about $0.0005 per session on Opus 5.5. 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 2026-08-30.
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