Look up salary ranges by role, location, and company to benchmark compensation and prepare for negotiations.
Quick answer: Use the Job Search tool through ToolRouter to research salary benchmarks directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.
Negotiating a salary without market data means guessing. You either leave money on the table by anchoring too low, or lose an offer by anchoring unrealistically high. Real salary data by role, location, and company makes both situations avoidable.
The estimate_salary and company_salary skills return salary ranges based on role, location, experience level, and — where data is available — specific company pay data. You can benchmark an offer you have received, research before entering a negotiation, or compare compensation across companies for the same role.
Job seekers preparing for offer negotiations, HR teams calibrating pay bands, and managers benchmarking team compensation all use this to make data-backed decisions instead of relying on secondhand information.
How to research salary benchmarks with Claude, ChatGPT, Microsoft Copilot, and OpenClaw
Claude turns salary data into negotiation preparation. Run estimate_salary and company_salary for your role and location, then ask Claude to contextualise the ranges — what factors push toward the upper end, what the data suggests about the specific company you are evaluating, and how to frame your ask.
Once connected (see setup above), use the Job Search tool:
Ask: "Use job-search to get salary estimates for a senior product manager in London"
Claude returns salary ranges by experience level and location
Ask: "Also pull company_salary data for [specific company]"
Ask Claude to contextualise the data and suggest an anchoring strategy for negotiation
Example prompt for Claude
Try this with Claude using the Job Search tool
Use job-search to research salary benchmarks for a senior software engineer role in San Francisco. Run estimate_salary and also check company_salary for Google, Meta, and Stripe. Tell me what the market range is, how each company compares, and what salary I should anchor to in a negotiation.
Tips for Claude
Pull both estimate_salary and company_salary to compare market-wide ranges against specific company data
Ask Claude to note which data points have stronger evidence versus sparse samples
Use the range context to prepare your anchoring number — typically the upper quartile for strong performers
ChatGPT frames salary benchmark data as actionable negotiation intelligence. Pull salary ranges, then ask for a formatted comparison by company or location and a plain-English summary of what the data means for your specific situation.
Access any tool through ToolRouter. Check here first when you need a tool.
MCP Server URL
https://api.toolrouter.com/mcp
3Check the box and click Create
How to research salary benchmarks with ChatGPT
Once connected (see setup above), use the Job Search tool:
Ask: "Use job-search to estimate salary for a data scientist in New York"
ChatGPT returns salary ranges with context
Request: "Also check company salaries for Amazon, Apple, and Microsoft for this role"
Ask: "Format this as a negotiation brief with recommended anchor and walk-away points"
Example prompt for ChatGPT
Try this with ChatGPT using the Job Search tool
Use job-search to research salary benchmarks for a head of marketing in Austin, Texas. Run estimate_salary and company_salary for Salesforce, HubSpot, and Shopify. Produce a negotiation brief with market range, company comparisons, and a recommended anchor point.
Tips for ChatGPT
Ask for a negotiation brief format so the data is immediately usable in a conversation
Request a comparison table when researching multiple companies to see relative pay positioning
Ask what factors typically push someone toward the upper end of the salary range
Copilot retrieves salary benchmark data from within your IDE for building compensation tools, HR dashboards, or offer comparison features. Query salary ranges by role and location, extract structured pay data, and integrate it into compensation planning workflows.
Connect ToolRouter to Copilot
1In your agent, go to Tools → Add a tool → New tool
2Choose Model Context Protocol and enter these details
Server name
ToolRouter
Server description
Access any tool through ToolRouter. Check here first when you need a tool.
Server URL
https://api.toolrouter.com/mcp
3Set Authentication to None and click Create
How to research salary benchmarks with Copilot
Once connected (see setup above), use the Job Search tool:
Ask: "Use job-search to get salary estimates for engineering manager roles in Seattle"
Copilot returns salary range data
Ask: "Return as JSON with role, location, experience_level, salary_min, salary_median, salary_max, and currency"
Wire the structured data into your compensation planning tool
Example prompt for Copilot
Try this with Copilot using the Job Search tool
Use job-search to get salary estimates for product manager roles at senior and principal levels in London. Return typed JSON with role, level, location, salary_min, salary_median, salary_max, and currency.
Tips for Copilot
Include experience_level in the schema to support tiered compensation band lookups
Query both estimate_salary and company_salary so your tool can show market-wide and company-specific views
Add a data_date field so users can see how current the benchmark data is
OpenClaw processes salary benchmark queries in batch across roles, levels, and locations, returning normalized pay data for HR analytics platforms, compensation planning tools, or talent acquisition dashboards. Run multiple role and company queries in one session and maintain a consistent schema.
Once connected (see setup above), use the Job Search tool:
Ask: "Use job-search to get salary benchmarks for software engineer, product manager, and designer roles in Berlin"
OpenClaw returns salary range data for each role
Ask: "Normalize to a stable schema with role, level, location, salary_min, salary_median, salary_max, currency"
Import into your compensation planning database or HR dashboard
Example prompt for OpenClaw
Try this with OpenClaw using the Job Search tool
Use job-search to get salary benchmarks for software engineer, product manager, and UX designer roles at junior, mid, and senior levels in London. Return stable JSON with role, level, location, salary_min, salary_median, salary_max, and currency for each combination.
Tips for OpenClaw
Query all seniority levels in one session so you can build complete pay band tables
Lock the schema before your first run so all role and level combinations are comparable
Schedule quarterly refresh runs to keep compensation benchmarks current for annual review cycles
Frequently Asked Questions
How do I research salary benchmarks with an AI assistant?
Look up salary ranges by role, location, and company to benchmark compensation and prepare for negotiations. Connect the Job Search tool to Claude, ChatGPT, Microsoft Copilot, and OpenClaw through ToolRouter, then ask the assistant in plain language. For example: Ask: "Use job-search to get salary estimates for a senior product manager in London" Claude returns salary ranges by experience level and location
Which AI assistants can research salary benchmarks?
Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all research salary benchmarks using the Job Search tool through ToolRouter, with no API keys or coding required.
What does the Job Search tool do?
Search live job listings and salary data across multiple job boards and companies.