Timesheet Generator
Daily at 7 PM, it gathers emails, calendar events, and GitHub activity to generate a clean timesheet in Google Sheets.
What it does
You get a clean timesheet in Google Sheets every day at 7 PM by automatically pulling your emails, calendar events, and GitHub activity. The agent filters out noise like newsletters or irrelevant commits before using an AI to summarize each item for easy billing and reporting.
Step by step
- Configure n8n cron triggers to run at specific intervals for pulling data from Gmail, Calendar, and GitHub.
- Set up API credentials and connections for all external services within the n8n workflow editor.
- Define the Google Sheets node structure with fixed headers for date, type, and summary columns.
Where the LLM does the work
- Prompt the OpenAI model to summarize raw email subjects or commit messages into professional billing descriptions.
- Instruct the LLM to filter out noise like newsletters by checking for specific keywords or sender patterns before summarization.
- Allow the LLM to categorize each entry as 'Development', 'Meeting', or 'Admin' based on context clues in the source data.
Watch out for
Tools that fit
The agent brief
You are helping me build the following AI agent workflow. ## Goal Timesheet Generator: Daily at 7 PM, it gathers emails, calendar events, and GitHub activity to generate a clean timesheet in Google Sheets. ## Specification - What it does: You get a clean timesheet in Google Sheets every day at 7 PM by automatically pulling your emails, calendar events, and GitHub activity. The agent filters out noise like newsletters or irrelevant commits before using an AI to summarize each item for easy billing and reporting. - Trigger: On a schedule (Scheduled · daily 7 PM) - Autonomy: Fully hands-off - Expected setup effort: under an hour - Tools/services involved: - n8n: Workflow orchestration platform - Gmail: Collecting email activity data - Google Calendar: Logging meeting events and duration - GitHub: Tracking commits and pull requests - OpenAI: Generating concise activity summaries ## Known pitfalls, handle each one explicitly in your implementation 1. LLM token costs can accumulate quickly with large volumes of emails, so limit the input text length before sending it to the model. 2. Google Sheets writes can fail silently if the sheet permissions are incorrect, so verify service account access rights beforehand. ## Reference implementation https://n8n.io/workflows/5396 (workflow template) Fetch and inspect this before building. If it matches my stack, adapt it; if not, rebuild the pattern with my tools. ## Process requirements 1. Before building: ask me which of the listed tools I actually use and what my platform is (n8n / Make / code / other). Do not assume. 2. Adapt the pattern to my answers; do not force the reference stack. 3. Address every pitfall above; tell me how you handled each. 4. Provide a test plan I can run before letting this touch real data. 5. Ask before any step that sends messages, modifies data, or spends money. Source: https://usecasesforagents.com/use-case/automated-timesheet-generator/ via usecasesforagents.com
Frequently asked questions
Can I use a different Automation Platform than n8n?
Yes. n8n is only the example automation platform in this recipe. The same flow works with Home Assistant. Swap the automation platform connection and keep the rest of the setup as written.
Want this running in your business?
Who it's for
Built for freelancers and consultants juggling this across every client, not just one.
Developers can adapt this to their own repo or ticket queue with the same trigger and tools.