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

> CSV file with survey or exit interview data including text responses or ratings

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: Culture Amp, Lattice, SurveyMonkey, Google Forms, or HRIS exports.

Establish for the subtask:
- Output path: `./documents/tmp/hr-data.json`
- Column types to detect: text responses, scores/ratings, departments, tenure, 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 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` (Exit survey analysis output format)

6. Analyze the survey/exit interview data:

1. Identify response columns (free text, ratings, multiple choice)
2. If text responses exist, extract recurring themes using thematic analysis:
   - Group similar comments into themes
   - Count frequency of each theme
   - Identify sentiment (positive/negative/neutral) for each theme
   - Pull representative quotes
3. If rating/score columns exist, calculate averages and distributions
4. Break down by department, tenure, or other segments if that data exists
5. Identify the top concerns (negative themes) and highlights (positive themes)

Present results following the Exit Survey & Employee Feedback Analysis template.
Include actual quotes and specific numbers, not just summaries.


7. Provide 2-3 actionable recommendations based on the findings.
Focus on: addressing top concerns, reinforcing positives, specific follow-up actions.
Be concrete—name the departments, issues, or patterns that need attention.