This skill lets AI agents fetch Wilma data via the CLI to deliver daily schedules, homework, exams, grades, and messages.
Find, trial, compare, and govern AI agents before hiring
Data
Connect APIs, databases, warehouses, spreadsheets, analytics, and ETL workflows.
What team job or business role does the user need filled?
Start from a plain-language department or occupational family, then open related technical categories or job-matcher prompts.
- department or team-role discovery
- plain-language job briefs
- business outcome shortlists
- non-technical browsing
Start from user language
- Connect a dataset or API to a reusable analysis workflow.
- Evaluate extraction, transformation, and retrieval candidates.
Sandbox-first next steps
Data candidates
Showing 12 of 4771. Adjust filters to narrow the review list without losing job context.
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This skill migrates N8N, Zapier, or Make workflows into production-grade Python scripts with retries, logging, and self-healing.
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Reusable workflow patterns for skills and agents including sequential checklists, conditional routing, validation loops, and progressive disclosure. Use when designing structured procedures.
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Review links
Role-family pages stay focused on plain-language job review; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
4771 candidates for Data. Open matching profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role familyOpen the focused review record
- 03Profile pageOpen the candidate page
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-family candidates, job brief context, and finalist profile resources before action.