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-source-integrationgit 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-source-integration)<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-source-integration"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-source-integration/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-source-integration"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-source-integration.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 | $0.00096 | $0.02626 |
| Opus 5 | $0.00048 | $0.01313 |
| Sonnet 5 | $0.00019 | $0.00525 |
| Haiku 4.5 | $0.00010 | $0.00263 |
Grade A, and why
powerbi-source-integration 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 10d 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 — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Source Integration & Data Model Development
Trigger
Activate when the user mentions: data source, connect source, ingest data, database connection, API connection, CSV upload, web scrape, source connector, raw data model, normalize, Bronze ingestion, source mapping, data model development, source to Bronze, multi-source, PostgreSQL, postgres, JDBC, RDS, Aurora, Azure Database for PostgreSQL, Cloud SQL, read replica, DirectQuery postgres, incremental refresh postgres
What You Know
You have integrated 50+ source systems into enterprise data platforms — from SAP ERP to Salesforce CRM, REST APIs to flat file drops, web scrapes to real-time streams. You know the full journey from "we have data in X" to "it's landed, clean, and queryable in OneLake."
Source Type Patterns
Database Sources
# Supported: SQL Server, PostgreSQL, MySQL, Oracle, Snowflake, SQLite
# Connection: JDBC or pyodbc
# Key settings:
# - Load strategy: full_load | incremental | cdc
# - Watermark column: the "modified_date" equivalent
# - Schema + table list (or empty for all tables)
# Best practices:
# - Prefer incremental over full_load for tables > 100K rows
# - Use Key Vault for credentials, never hardcode
# - Test connection before scheduling pipeline
PostgreSQL
PostgreSQL is fully supported across all Power BI / Fabric integration paths. Choose the right approach based on data volume and latency requirements.
Connection Modes — Decision Guide
| Scenario | Recommended Mode |
|---|---|
| Small tables (<1M rows), low latency | DirectQuery |
| Large tables (>1M rows), fast dashboards | Import (scheduled refresh) |
| Fabric Lakehouse as intermediary | Copy Activity (Fabric Pipeline) → OneLake → DirectLake |
| Real-time streaming data | Eventstream → Lakehouse → DirectLake |
Power BI Desktop — Direct Connection
Get Data → Database → PostgreSQL Database
Server: db.example.com (or db.example.com:5432)
Database: prod_db
Data Connectivity mode:
• Import — loads data into model (recommended for most cases)
• DirectQuery — live queries to PostgreSQL (use only for <10M rows and fast server)
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.
- 10d ago First seen · 306 lines · 0 tokens per session scan A d79c6b203e89
powerbi-source-integration is a skill published in the GitHub repository santoshkanthety/powerbi-agent (2 stars, last pushed 11d ago), licensed MIT. It adds 96 tokens to every session and 2,626 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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