Analyze Quarterly Metrics
Requirements
CSV file with date/period column and business metric columns (revenue, customers, etc.)
1
If the CSV path was not already provided, ask the user for it.
Common sources: Finance exports, BI dashboards, quarterly reports.
Establish for the subtask:
- Output path:
Parsed Executive Data
- Column types to detect: dates/periods, revenue, customers, growth metrics
5
Analyze the quarterly data:
- Identify the date/period column and key metric columns
- Calculate quarter-over-quarter (QoQ) changes for each metric
- If year-ago data exists, calculate year-over-year (YoY) changes
- Identify the best performing metric this quarter
- Identify concerning trends (consecutive declines, missed targets)
- Note any significant shifts in patterns
Present results following the Quarterly Business Review template.
Include the summary table with actual numbers and percentage changes.
6
Generate 3 board-ready insights that an executive could share.
These should be:
- Concise (one sentence each)
- Data-backed (reference specific numbers)
- Actionable or conversation-starting
Also suggest 2 follow-up questions the board might ask.
To run this task you must have the following required information:
> CSV file with date/period column and business metric columns (revenue, customers, etc.)
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: Finance exports, BI dashboards, quarterly reports.
Establish for the subtask:
- Output path: `./documents/tmp/executive-data.json`
- Column types to detect: dates/periods, revenue, customers, growth metrics
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 Executive Data]: Read the file at `./documents/tmp/executive-data.json` and analyze its contents (Load the parsed and interpreted CSV data)
5. [Read Executive Analytics Guide]: Read the documentation in: `./skills/sauna/[skill_id]/references/executive.analytics.guide.md` (Quarterly business review output format)
6. Analyze the quarterly data:
1. Identify the date/period column and key metric columns
2. Calculate quarter-over-quarter (QoQ) changes for each metric
3. If year-ago data exists, calculate year-over-year (YoY) changes
4. Identify the best performing metric this quarter
5. Identify concerning trends (consecutive declines, missed targets)
6. Note any significant shifts in patterns
Present results following the Quarterly Business Review template.
Include the summary table with actual numbers and percentage changes.
7. Generate 3 board-ready insights that an executive could share.
These should be:
- Concise (one sentence each)
- Data-backed (reference specific numbers)
- Actionable or conversation-starting
Also suggest 2 follow-up questions the board might ask.