Statistical Analysis
CheckedAnalyzes Braesology log data to identify trends, anomalies, and statistically significant patterns in user behavior.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add braselog/researchassistant --skill statistical-analysis -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
braselog
Taken from the source listing. We haven't verified who controls this account.
Install target
Live repository
Not pinned. Installing fetches whatever the repository holds at the time you run the command.
Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
Declares what it does: passed
SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
No undeclared network calls: passed
Makes no network calls.
Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.
No obfuscated payloads: passed
No encoded or obfuscated payloads.
No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.
No credential access: passed
Reads no keys, tokens, keychains or credential files.
Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.
No pipe-to-shell installers: passed
No pipe-to-shell or download-and-run installers.
No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.
Pinned to a commit: passed
Scanned braselog/researchassistant at 6e1e60a1d7.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 6e1e60a1d7
- Scanned
- 1 file, 20 lines
About this skill
What it does
This skill performs statistical analysis on provided datasets. It can calculate descriptive statistics like mean, median, and standard deviation, as well as perform more complex analyses such as hypothesis testing and regression. The tool aims to provide data-driven insights from numerical information.
When to use it
- Analyzing survey results to identify trends and patterns in responses.
- Evaluating the effectiveness of an A/B test by comparing key metrics.
- Exploring a dataset of sales figures to understand seasonality or growth rates.
- Performing correlation analysis between different variables to find relationships.
Key capabilities
- Descriptive statistics calculation (mean, median, standard deviation)
- Hypothesis testing
- Regression analysis
Example prompts
- "Calculate the mean and standard deviation of this dataset: [dataset]"
- "Perform a t-test comparing group A and group B with these results: [data for group A], [data for group B]"
- “Run a linear regression on sales data to predict future trends, using advertising spend as an independent variable.”
Tips & gotchas
The skill requires numerical data in a structured format (e.g., CSV or list of numbers) to function correctly. Ensure the input data is clean and properly formatted for accurate analysis.