Does it integrate with other skills?

Yes, it is specifically designed to pair with the personality-profiler skill to enhance behavioral signal extraction and enrich user profiles.

What kind of insights can I expect?

Expect non-obvious findings such as linguistic shifts over time, unusual engagement ratios, hidden network connections, and unique behavioral fingerprints.

What datasets does Data Sleuth work best with?

It is optimized for structured data such as social media exports, user behavior logs, financial data, and any dataset where temporal or behavioral patterns exist.

Can I use this with multiple datasets simultaneously?

Yes, Data Sleuth excels at cross-dataset triangulation, identifying where different data sources corroborate or contradict each other to reveal deeper insights.

How does the interview-first workflow work?

Before performing analysis, the skill uses the AskUserQuestion function to present you with specific investigation options like temporal anomaly detection or behavioral clustering based on your data structure.

Data Sleuth

Name: Data Sleuth
Author: petekp

bypetekp

0•

数据科学与机器学习

Uncovers hidden patterns, non-obvious correlations, and behavioral signals within complex datasets using investigative analysis techniques.

Data Sleuth transforms Claude into an investigative data analyst capable of identifying subtle insights that standard statistical tools often miss. By applying methodologies from data journalism and forensic accounting, it explores temporal anomalies, behavioral clusters, and cross-dataset correlations to provide a deeper understanding of user data and social media exports. It features a proactive workflow that engages users with specific analysis options before execution, ensuring that findings—ranging from linguistic forensics to network topology—align with specific investigative goals.

主要功能

01Interview-driven workflow to define specific analysis goals and options

020 GitHub stars

03Investigative signal detection for identifying non-obvious data patterns

04Temporal fingerprinting to discover activity rhythms and scheduling anomalies

05Detailed output reports with evidence-backed findings and confidence ratings

06Cross-dataset triangulation to correlate findings across multiple sources

使用场景

01Analyzing social media exports to find engagement anomalies and topic evolution

02Identifying behavioral fingerprints and unique timing signatures in activity logs

03Cross-referencing disparate datasets to uncover hidden contradictions or corroborations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add petekp/agent-skills data-sleuth

For use in Claude.ai and ChatGPT

Download Skill