Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/santoshkanthety/powerbi-agentnpx agentmods add skills/santoshkanthety/powerbi-agent/powerbi-review-reportWrote 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-review-report)<a href="https://agentmods.dev/skills/santoshkanthety/powerbi-agent/powerbi-review-report"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-review-report/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-review-report"><img src="https://agentmods.dev/badge/skills/santoshkanthety/powerbi-agent/powerbi-review-report.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 | $0.00073 | $0.03218 |
| Opus 5 | $0.00036 | $0.01609 |
| Sonnet 5 | $0.00015 | $0.00644 |
| Haiku 4.5 | $0.00007 | $0.00322 |
Grade A, and why
powerbi-review-report 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 — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewing Power BI Reports
Structured evaluation of Power BI reports to produce actionable feedback for developers and consultants. A report review assesses whether a report is effective, well-built, and actually being used. The output is a prioritized list of findings with concrete recommendations.
Note that the skill works on one of three scenarios:
- Report under development: In this scenario, the focus is more on the report content, structure, organization, and performance based on accurately gathered requirements.
- Report in testing: In this scenario, the focus might incorporate user feedback or check basic information about the deployed report in Power BI / Fabric.
- Report in use: This is the ideal scenario, where the focus is usage; the ultimate definition of success is whether the report is being used; what percentage of the people who have access to the report have accessed it in the last 28 days, and how much? Bad reports aren't used, or have declining usage.
In scenario 2-3 you may still provide feedback on the report content / structure, but prioritizing other things first.
When to Use
Activate when conducting a report review, audit, or health check. Common triggers:
- Reviewing report quality before a release or handoff
- Assessing whether existing reports are worth maintaining
- Identifying optimization opportunities across a workspace
- Evaluating report design and data presentation effectiveness
- Investigating report performance issues
Review Dimensions
A comprehensive report review evaluates six dimensions. Not every review needs all six -- scope to what the user needs.
1. Usage and Adoption
The most objective signal of report value. A report that nobody views is a maintenance liability regardless of its design quality.
Retrieve usage data with the scripts in scripts/:
# Workspace overview (views, rank, page views, load times)
python3 scripts/get_report_usage.py -w <workspace-id>
python3 scripts/get_report_usage.py -w <workspace-id> --include-datahub
# Single report deep-dive (daily views, per-viewer breakdown, page views by day)
python3 scripts/get_report_detail.py -w <workspace-id> -r <report-id>
# Distribution audit (who has access, through what channels)
python3 scripts/get_report_distribution.py -w <workspace-id> -r <report-id>
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 · 273 lines · 73 tokens per session scan A eecb5edbfd17
powerbi-review-report is a skill published in the GitHub repository santoshkanthety/powerbi-agent (2 stars, last pushed 13d ago), licensed MIT. It adds 73 tokens to every session and 3,218 once invoked, about $0.0004 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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