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

> CSV file with rep/owner column and deal amount/outcome data

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. If the CSV path was not already provided, ask the user for it.
Should include: rep names, deal amounts, and ideally win/loss status.

Establish for the subtask:
- Output path: `./documents/tmp/sales-data.json`
- Column types to detect: reps/owners, amounts, stages/outcomes, dates


2. [Gather Requirements for Parse and Interpret CSV] The next step has the following requirements: "CSV file path to parse. Column type hints (e.g., "scores, customers, dates, categories"). Output file path for the interpreted data.". Search the user's data for this information or ask them directly if needed. Do not proceed until you have this information.

3. [Execute Parse and Interpret CSV Task]: Spawn a subagent and provide it with the requirements gathered above and instructions to read `./skills/sauna/[skill_id]/references/recipes/stdlib.csv.interpret.md` for its task list

4. [Read Parsed Sales Data]: Read the file at `./documents/tmp/sales-data.json` and analyze its contents (Load the parsed and interpreted CSV data)

5. [Read Sales Analytics Guide]: Read the documentation in: `./skills/sauna/[skill_id]/references/sales.analytics.guide.md` (Rep performance output format)

6. Analyze rep performance data:

1. Identify the rep/owner column and amount column from interpreted columns
2. If a status/outcome column exists, calculate close rates
3. If no status column, rank by total revenue
4. Calculate per-rep metrics: deals won, total deals, close rate, total revenue
5. Rank reps by close rate (or revenue if no outcome data)
6. Compare top 25% vs bottom 25% performers

Present results following the Rep Performance Rankings template.
Include individual rep strengths based on what the data shows.


7. Highlight what separates top performers from the rest.
If possible, identify coachable behaviors (deal size, volume, etc.).