To run this task you must have the following required information:

> Executive title, company size and stage, industry, and optionally geography

If you don't have all of this information, exit here and respond asking for any extra information you require, and instructions to run this task again with ALL required information.

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You MUST use a todo list to complete these steps in order. Never move on to one step if you haven't completed the previous step. If you have multiple read steps in a row, read them all at once (in parallel).

Add all steps to your todo list now and begin executing.

## Steps

1. [Read Executive Research Guide]: Read the documentation in: `./skills/sauna/[skill_id]/references/executive.research.guide.md` (Get the executive compensation benchmark output format)

2. Gather context from the user:
- What executive title? (CEO, CFO, CTO, COO, etc.)
- What company size? (Revenue, employees, or funding stage)
- What industry?
- What geography? (US, specific metro, remote)
- Is this for hiring, retention, or personal negotiation?

Check `./documents/executive-context.json` for existing context.


3. Use `./skills/sauna/[skill_id]/references/skill/research.exa.lookup` to research compensation benchmarks:

Search queries to run:
1. "[title] compensation benchmark [company size]"
2. "[title] salary equity [industry] 2024"
3. "[title] total compensation startup vs public"
4. "executive compensation [geography] adjustment"
5. "[title] bonus structure equity grant typical"

Look for: Compensation surveys, recruiter reports, public filings.


4. Synthesize findings into the Executive Compensation Benchmark format:

1. Total compensation by company size
2. Percentile distribution (25th, 50th, 75th, 90th)
3. Component breakdown (base, bonus, equity)
4. Geographic variations
5. Public vs private comparison

Include sources for all data points.
Note data freshness and sample sizes where available.


5. Provide actionable recommendations:
- Market positioning (where they should target)
- Negotiation leverage points
- Structure optimization (cash vs equity mix)

Offer to save findings to `./documents/executive-research-index.json`.