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Data Researcher
Security Scan Summary
Status: Safe
Source: Syntic Skills registry
Automated security scan completed with no high-risk patterns detected. Manual review is still required.
About This Skill
Use when extracting meaningful insights from datasets through statistical analysis, pattern recognition, and evidence-based reasoning.
Downloadable SKILL.md
Download SKILL.md and place it in your Syntic skills folder. For Syntic Code, install in your local skills directory, review contents, and run in a controlled environment first. Acknowledge the risk notice above to enable the download.
--- name: Data Researcher description: Use when extracting meaningful insights from datasets through statistical analysis, pattern recognition, and evidence-based reasoning. category: Research version: 1.0.0 tools: [] --- # Data Analysis & Insight Define analysis objectives: the question to answer, the decision it informs, what a useful answer looks like, what data constitutes sufficient evidence. ## Data Quality Assessment Examine completeness (missing value patterns), consistency (contradictory records), accuracy (validation against known truths), timeliness (whether data reflects current conditions). Explicitly document missingness pattern (MCAR, MAR, MNAR) and select appropriate strategy (listwise deletion, imputation, sensitivity analysis). ## Exploratory Analysis Understand distributions, identify outliers, detect quality issues, form initial hypotheses. Apply descriptive statistics for summarization, inferential statistics for hypothesis testing, regression for relationship modeling, clustering for segmentation. ## Statistical Rigor Apply tests with attention to assumptions: check normality for parametric tests, verify independence of observations, apply multiple comparison corrections, report effect sizes alongside p-values. Handle missing data explicitly and report impact on findings. ## Visualization Encode data accurately: choose chart types matching data structure, avoid misleading axis scales, include uncertainty indicators, label axes with units. Visualizations must not distort data—axes start at zero for bar charts, area proportional to value, color scales perceptually uniform. ## Interpretation & Verification Interpret findings in analysis context, distinguishing statistically significant from practically significant results. Reproduce from documented steps and versioned data snapshots. Validate statistical test assumptions before interpreting; report violations and impact. Cross-validate predictive models on held-out data. ## Documentation Standards Document complete methodology: data sources, preprocessing steps, analysis code, parameter choices. Report sample sizes and conduct power analysis. Explicitly state that correlation does not imply causation and list plausible confounding variables. Document data transformations as a pipeline with named stages.
Bundle Download
Includes SKILL.md and bundled support files where provided. Risk acknowledgement is required.
Install Targets
Syntic App
- 1. Create a dedicated folder for this skill in your local skills library.
- 2. Place SKILL.md into that folder.
- 3. Restart Syntic and invoke this skill on matching tasks.
Syntic Code (CLI)
- 1. Save SKILL.md in your local Syntic Code skills directory.
- 2. Keep related files in the same skill folder.
- 3. Run in a safe environment and validate outputs.
Source
https://github.com/rohitg00/awesome-claude-code-toolkit/blob/main/agents/research-analysis/data-researcher.md
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