data-analyst-workflow
Skill4 starsChanged 8 days agoMITView on GitHub
Use when coordinating an end-to-end data analysis workflow, or when a request spans data cleaning, data quality, feature engineering, SQL, or business intelligence reporting.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- 00PrabalK00/claude-skillstheir own version, first seen Mar 16, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- 00PrabalK00/claude-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- site/AGENTS.mdAGENTS.md
- bi-expertSkill
- data-cleaningSkill
- data-qualitySkill
- feature-engineeringSkill
- sql-expertSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 4 are distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈4
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Use this skill to coordinate data-analysis requests across the specialist skills.
- Distinctive: line 31
Use only the data and context the user explicitly provides for the requested analysis.
- Distinctive: line 32
Do not solicit or process payment-card data subject to PCI DSS, protected health information, government identifiers, or authentication …
- Distinctive: line 34
Avoid reproducing personal or confidential values in responses.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Data Analyst Workflow
Use this skill to coordinate data-analysis requests across the specialist skills. Do not repeat their detailed procedures here or handle their domain work from this file. Before carrying out a phase, open and follow the linked specialist skill for that phase.
Route the request
- Dataset cleaning or transformation: data-cleaning
- Data-quality rules, audit, or remediation: data-quality
- Derived analytical or machine-learning fields: feature-engineering
- SQL writing, explanation, optimization, or debugging: sql-expert
- BI platform, dashboard, KPI, visualization, or report deliverable: bi-expert
For a focused request, load only the matching skill. For a broad request, load each relevant skill and coordinate the work in this order as applicable:
- Assess data quality.
- Clean or transform the data.
- Engineer features.
- Query or analyze using the requested tool.
- Prepare business intelligence reporting in the requested platform and deliverable format.
- Validate that assumptions, grain, and metrics remain consistent across the results.
Skip irrelevant phases. Carry decisions and assumptions forward between skills, and present one coherent result rather than separate, repetitive instructions. Each specialist skill owns its detailed workflow, safety requirements, and output guidance.
Privacy baseline
- Use only the data and context the user explicitly provides for the requested analysis. Do not solicit unrelated personal or confidential information.
- Do not solicit or process payment-card data subject to PCI DSS, protected health information, government identifiers, or authentication credentials and secrets. If supplied data contains these fields, ask the user to remove or mask them before analysis.
- Process other sensitive or special-category personal data only when it is strictly necessary for the stated task, legally adequate consent is confirmed, and the user was explicitly informed before providing it. Otherwise, ask the user to remove or mask it.
- Avoid reproducing personal or confidential values in responses.
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