CSV Data Analyzer

Load, explore, clean, analyze, and visualize CSV data to provide statistical summaries, correlations, filtered views, and charts for insights.

Security Scan

The skill's requirements and instructions are coherent with its stated purpose (CSV analysis/visualization); it is an instruction-only skill that expects Python + pandas/matplotlib and does not request unrelated credentials or installs.

Purpose & Capability

The name/description (CSV analysis) matches the runtime instructions: loading CSVs, cleaning, statistics, grouping, correlations, and charts. The only external dependency mentioned (Python with pandas and matplotlib) is appropriate and expected for this purpose.

Instruction Scope

SKILL.md confines actions to reading user-supplied CSV files, performing data cleaning/analysis, generating summaries, saving PNG charts, and exporting cleaned CSVs. It does not instruct the agent to read unrelated system files, environment variables, or to transmit results to external endpoints.

Install Mechanism

There is no install spec (instruction-only), which is the lowest-risk model. The skill expects required Python libraries to already exist; it does not download or run external installers.

Credentials

No environment variables, credentials, or config paths are requested. The only resource access implied is the user-provided CSV file(s) and the ability to write output files (PNGs, CSVs), which is proportionate to the stated function.

Persistence & Privilege

always is false and the skill does not request persistent or elevated privileges or modifications to other skills. Autonomous invocation is allowed by default but is not combined with broad credential access or other red flags.

Assessment

This skill is internally consistent and appears to do what it says. Before installing or using it: 1) Ensure the execution environment has Python with pandas and matplotlib (the skill will not install them). 2) Be deliberate about what CSVs you upload—CSV files can contain sensitive data (credentials, PII); the skill will read the full file and may write cleaned CSVs and PNGs to the environment. 3) Confirm where output files are saved and whether that storage is private/trusted. 4) If you lack the necessary Python packages, either provision an isolated environment with them or decline until you can run it in a controlled environment. No scanner findings were present because this is instruction-only (no code files) — that is expected but also means runtime behavior depends on the agent environment and available libraries.

A skill that enables Claw to load, explore, analyze, and visualize CSV datasets, providing statistical insights and answering questions about the data.

What This Skill Does

This skill equips Claw with a structured approach to CSV data analysis:

1. Data Loading & Inspection — Read CSV files, detect column types, and display basic structure (shape, columns, sample rows)
2. Data Cleaning — Identify and handle missing values, duplicates, and type inconsistencies
3. Statistical Summary — Compute descriptive statistics (mean, median, mode, standard deviation, percentiles) for numeric columns
4. Filtering & Grouping — Slice data by conditions and aggregate by categories
5. Correlation Analysis — Find relationships between numeric variables
6. Visualization — Generate charts (bar, line, scatter, histogram) to illustrate patterns

How to Use

Provide a CSV file and ask Claw to analyze it:

• "Analyze this sales data and tell me which product category has the highest revenue"
• "Find outliers in the temperature column of this dataset"
• "Create a chart showing monthly trends from this CSV"
• "Compare group A vs group B performance in this experiment data"

Requirements

• Input must be a valid CSV file (comma-separated by default; other delimiters can be specified)
• Python with pandas and matplotlib should be available in the environment

Output

• Summary statistics table
• Key insights in plain language
• Charts saved as PNG files when visualization is requested
• Cleaned dataset exported as a new CSV if data cleaning was performed