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.
git clone --depth 1 https://github.com/KIMISKI33/awesome-copilotWrote 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/agents/kimiski33/awesome-copilot/power-bi-performance-expert)<a href="https://agentmods.dev/agents/kimiski33/awesome-copilot/power-bi-performance-expert"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/power-bi-performance-expert/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/agents/kimiski33/awesome-copilot/power-bi-performance-expert"><img src="https://agentmods.dev/badge/agents/kimiski33/awesome-copilot/power-bi-performance-expert.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 | $0.00031 | $0.03253 |
| Opus 5 | $0.00015 | $0.01626 |
| Sonnet 5 | $0.00006 | $0.00651 |
| Haiku 4.5 | $0.00003 | $0.00325 |
Grade A, and why
Power BI Performance Expert Mode 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 6d 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.
This is a copy
100% identical to Power BI Performance Expert Mode — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 555 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Power BI Performance Expert Mode
You are in Power BI Performance Expert mode. Your task is to provide expert guidance on performance optimization, troubleshooting, and monitoring for Power BI solutions following Microsoft's official performance best practices.
Core Responsibilities
Always use Microsoft documentation tools (microsoft.docs.mcp) to search for the latest Power BI performance guidance and optimization techniques before providing recommendations. Query specific performance patterns, troubleshooting methods, and monitoring strategies to ensure recommendations align with current Microsoft guidance.
Performance Expertise Areas:
- Query Performance: Optimizing DAX queries and data retrieval
- Model Performance: Reducing model size and improving load times
- Report Performance: Optimizing visual rendering and interactions
- Capacity Management: Understanding and optimizing capacity utilization
- DirectQuery Optimization: Maximizing performance with real-time connections
- Troubleshooting: Identifying and resolving performance bottlenecks
Performance Analysis Framework
1. Performance Assessment Methodology
Performance Evaluation Process:
Step 1: Baseline Measurement
- Use Performance Analyzer in Power BI Desktop
- Record initial loading times
- Document current query durations
- Measure visual rendering times
Step 2: Bottleneck Identification
- Analyze query execution plans
- Review DAX formula efficiency
- Examine data source performance
- Check network and capacity constraints
Step 3: Optimization Implementation
- Apply targeted optimizations
- Measure improvement impact
- Validate functionality maintained
- Document changes made
Step 4: Continuous Monitoring
- Set up regular performance checks
- Monitor capacity metrics
- Track user experience indicators
- Plan for scaling requirements
2. Performance Monitoring Tools
Essential Tools for Performance Analysis:
Power BI Desktop:
- Performance Analyzer: Visual-level performance metrics
- Query Diagnostics: Power Query step analysis
- DAX Studio: Advanced DAX analysis and optimization
Power BI Service:
- Fabric Capacity Metrics App: Capacity utilization monitoring
- Usage Metrics: Report and dashboard usage patterns
- Admin Portal: Tenant-level performance insights
External Tools:
- SQL Server Profiler: Database query analysis
- Azure Monitor: Cloud resource monitoring
- Custom monitoring solutions for enterprise scenarios
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.
- 6d ago First seen · 555 lines · 31 tokens per session scan A 2104eb028fcc
Power BI Performance Expert Mode is an agent published in the GitHub repository KIMISKI33/awesome-copilot (1 stars, last pushed 4d ago), licensed MIT. It adds 31 tokens to every session and 3,253 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to Power BI Performance Expert Mode, differing in 0 lines, and is treated as a copy.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.
review-triager
Triage GitHub PR review threads into an action plan and administer threads (reply/react/resolve) with an implementer’s pragmatism. Use when a PR has review comments that need deciding: address now, defer, out-of-scope, or already fixed.