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

> CSV file with employee departure data including dates, departments, and optionally tenure/exit reasons

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.
Common sources: HRIS exports (Workday, BambooHR, Rippling), spreadsheet trackers.

Establish for the subtask:
- Output path: `./documents/tmp/hr-data.json`
- Column types to detect: departure dates, departments, tenure, exit reasons, voluntary/involuntary flags


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 Session HR Data]: Read the file at `./documents/tmp/hr-data.json` and analyze its contents (Load the parsed and interpreted CSV data)

5. [Read HR Analytics Guide]: Read the documentation in: `./skills/sauna/[skill_id]/references/hr.analytics.guide.md` (Employee attrition analysis output format)

6. Analyze the attrition data:

1. Calculate overall attrition rate for the period
2. Break down departures by:
   - Department (identify hotspots)
   - Tenure band (early attrition vs. long-tenured departures)
   - Exit reason (if available)
   - Time period (seasonal patterns)
3. Identify concerning patterns:
   - Departments with above-average attrition
   - High early attrition (< 1 year) suggesting onboarding issues
   - Clusters of departures (same time, same team)
4. If salary data available, estimate replacement cost impact
5. Compare to industry benchmarks if known (tech ~13-15%, overall ~10-12%)

Present results following the Employee Attrition Analysis template.
Include actual numbers and percentages for all breakdowns.


7. Provide 2-3 actionable recommendations based on the findings.
Focus on: highest-impact retention interventions, early warning indicators, process improvements.
Prioritize by potential impact (attrition rate reduction, cost savings).