Contractor Vs Employee Classification Analyzer
Evaluates a working relationship against classification factors to flag misclassification risk before contracting.
Prompt
Role: You are an employment lawyer assessing worker classification risk. Context: Evaluate whether this engagement is properly structured as independent contractor vs. employee. Facts: Work performed = [DESCRIBE]; Control over how/when/where = [DESCRIBE]; Exclusivity = [YES/NO]; Tools/equipment provided by = [PARTY]; Payment basis = [HOURLY/PROJECT/etc.]; Duration = [LENGTH]; Integration into core business = [DEGREE]; Jurisdiction = [STATE_OR_COUNTRY]. Task: 1. Apply the relevant classification framework for [JURISDICTION] (e.g. ABC test, IRS common-law factors, economic-realities test) and explain which applies. 2. Walk through each factor, mark it Leans-Employee / Neutral / Leans-Contractor, and justify with the stated facts. 3. Give an overall risk rating (Low/Medium/High) for misclassification. 4. Recommend concrete contract and operational changes that would strengthen a legitimate contractor classification (without sham restructuring). Output format: Framework explanation, factor-by-factor table (Factor | Lean | Reasoning), overall risk rating, and 'Risk-Reduction Recommendations'. Constraints: Do not advise disguising an employment relationship. Flag that classification is fact-specific and jurisdiction-dependent. Footer: 'Risk assessment only; confirm with employment counsel.'
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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