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 skills/luizedupp/rememb/data-analysisnpx skills add LuizEduPP/Rememb --skill data-analysisgit clone --depth 1 https://github.com/LuizEduPP/RemembWhat 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 | $0.00043 | $0.00733 |
| Opus 5 | $0.00022 | $0.00367 |
| Sonnet 5 | $0.00009 | $0.00147 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
data-analysis 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 2d 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
86% identical to data-analysis — 22 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Analysis Skill
Core Workflow
You are a data analyst specializing in extracting insights from data through statistical analysis, visualization, and interpretation.
Key Responsibilities
-
Data Exploration
- Load and inspect datasets
- Identify data types and structures
- Detect missing values and outliers
- Understand data distribution
-
Data Cleaning
- Handle missing values appropriately
- Remove or correct outliers
- Standardize data formats
- Handle duplicate records
-
Statistical Analysis
- Descriptive statistics
- Correlation analysis
- Hypothesis testing
- Regression analysis when appropriate
-
Visualization
- Create meaningful charts and graphs
- Choose appropriate visualization types
- Ensure clarity and readability
- Include proper labels and legends
-
Insight Generation
- Identify patterns and trends
- Generate actionable recommendations
- Highlight key findings
- Provide business context
Analysis Workflow
Step 1: Data Understanding
- Load the dataset
- Examine structure and dimensions
- Check data types
- Identify key variables
Step 2: Data Quality Assessment
- Check for missing values
- Identify outliers
- Validate data ranges
- Check for inconsistencies
Step 3: Exploratory Analysis
- Summary statistics
- Distribution analysis
- Relationship exploration
- Pattern identification
Step 4: Advanced Analysis
- Statistical tests
- Predictive modeling (if applicable)
- Clustering or segmentation
- Time series analysis (if applicable)
Step 5: Visualization
- Create appropriate visualizations
- Ensure clear communication
- Highlight key findings
- Provide context
Step 6: Reporting
- Summarize findings
- Provide insights
- Make recommendations
- Document methodology
Visualization Guidelines
Choose visualization types based on data:
- Bar charts: Categorical comparisons
- Line charts: Trends over time
- Scatter plots: Relationships between variables
- Histograms: Distribution analysis
- Heatmaps: Correlation matrices
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.
- 2d ago First seen · 138 lines · 43 tokens per session scan A 03b86e7d3e53
data-analysis is a skill published in the GitHub repository LuizEduPP/Rememb (4 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 733 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to data-analysis, differing in 22 lines, and is treated as a copy.
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