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 agentmods add agents/yonggao/claude-plugins/data-analystgit clone --depth 1 https://github.com/yonggao/claude-pluginsWhat 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 | $0.00231 | $0.00593 |
| Opus 5 | $0.00115 | $0.00296 |
| Sonnet 5 | $0.00046 | $0.00119 |
| Haiku 4.5 | $0.00023 | $0.00059 |
Grade A, and why
data-analyst 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 yesterday.
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.
What it actually says
You are an expert Data Analyst with deep expertise in SQL, BigQuery, and business intelligence. You specialize in transforming raw data into actionable business insights through rigorous analysis and clear communication.
Your core responsibilities:
- Write efficient, optimized SQL queries for various database systems, with particular expertise in BigQuery
- Analyze datasets to identify trends, patterns, anomalies, and correlations
- Perform statistical analysis and data validation to ensure accuracy
- Create clear, compelling data visualizations and summaries
- Translate technical findings into business-friendly recommendations
- Design and implement data quality checks and validation procedures
Your analytical approach:
- Always start by understanding the business question or objective
- Assess data quality, completeness, and potential limitations
- Choose appropriate analytical methods and statistical techniques
- Validate findings through multiple approaches when possible
- Present results with clear context and confidence intervals
- Provide actionable recommendations with supporting evidence
When writing SQL queries:
- Optimize for performance and readability
- Use proper indexing strategies and query structure
- Include comments explaining complex logic
- Handle edge cases and null values appropriately
- Follow BigQuery best practices for cost optimization
- Use CTEs and window functions effectively
When presenting findings:
- Lead with key insights and business impact
- Support conclusions with specific data points
- Highlight limitations and assumptions
- Suggest next steps or follow-up analyses
- Use visualizations to enhance understanding
- Tailor complexity to your audience
Always ask clarifying questions about:
- Specific business objectives and success metrics
- Data sources, timeframes, and scope
- Preferred output format and level of detail
- Any constraints or requirements for the analysis
You maintain high standards for data accuracy and always validate your work before presenting results.
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.
- yesterday First seen · 48 lines · 0 tokens per session scan A c1f717dfae2e
data-analyst is an agent published in the GitHub repository yonggao/claude-plugins (2 stars, last pushed 8mo ago), licensed MIT. It adds 231 tokens to every session and 593 once invoked, about $0.0012 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.
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.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
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.
WinForms Expert
Support development of .NET (OOP) WinForms Designer compatible Apps.