Lemmy is a powerful wrapper that uses large language models (LLMs) to streamline agentic workflows. It enhances productivity by automating tasks and facilitating interactions between users and AI agents.
claude install badlogic/lemmyhttps://github.com/mariozechner/lemmy
[{"step":"Define the Agent's Role and Goals","action":"Open Type and select 'Custom Agent' or a template (e.g., 'Chief of Staff'). Specify the agent’s primary goal in 1–2 sentences, such as 'Automate weekly social media content scheduling and performance reporting for our marketing team.'","tip":"Be specific about the agent’s purpose to avoid vague or overly broad tasks. Use the template’s role description as a starting point and customize it."},{"step":"Configure Skills and Tools","action":"Under 'Skills,' add relevant capabilities (e.g., 'Data Analysis,' 'Content Generation,' 'API Integration'). In 'Tools,' connect the agent to necessary platforms (e.g., LinkedIn for scheduling, Google Analytics for reporting).","tip":"Prioritize skills that directly support the agent’s goal. For example, if the agent needs to draft emails, include 'Email Drafting' and connect to Gmail or Outlook."},{"step":"Set Constraints and Automation Rules","action":"In the 'Constraints' section, define limits like 'Only work during business hours' or 'Exclude test accounts from data analysis.' Under 'Automation,' schedule tasks (e.g., 'Generate report every Friday at 4 PM').","tip":"Use constraints to prevent the agent from overstepping boundaries. For automation, start with a single scheduled task and expand as needed."},{"step":"Test and Deploy","action":"Run a test task (e.g., 'Draft a sample social media post') to verify the agent’s performance. Once satisfied, deploy it by clicking 'Activate Agent.' Monitor the agent’s output for the first 24–48 hours.","tip":"Start with a low-risk task to identify issues early. Use the agent’s logs (available in Type) to troubleshoot any errors."},{"step":"Iterate Based on Feedback","action":"Review the agent’s performance after 1–2 weeks. Adjust goals, skills, or constraints based on user feedback or observed inefficiencies. For example, refine the 'Content Generation' skill if posts lack engagement.","tip":"Schedule a recurring review (e.g., monthly) to ensure the agent remains aligned with evolving needs. Use Type’s analytics dashboard to track metrics like task completion rate."}]
Automate customer interactions by integrating AI chatbots for 24/7 support.
Streamline data entry tasks by using LLMs to auto-fill forms based on user input.
Enhance team collaboration through AI by generating meeting summaries and action items.
Generate detailed reports based on user queries and data analysis using LLMs.
claude install badlogic/lemmygit clone https://github.com/badlogic/lemmyCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Set up a Lemmy agent in Type to [TASK]. Configure the agent with the following parameters: [AGENT_GOALS], [SKILLS], and [CONSTRAINTS]. Use the 'Chief of Staff' template as a starting point for role definition. Ensure the agent has access to [RELEVANT_TOOLS] and set up automated reporting to [RECIPIENT_EMAIL] every [FREQUENCY].
### Agent Setup Summary **Agent Name:** Growth Tracker **Role:** Chief of Staff (Customized) **Primary Goal:** Monitor and report on quarterly growth metrics for Acme Corp’s SaaS product line, including MRR, churn rate, and customer acquisition cost (CAC). **Skills Assigned:** - **Data Analysis:** Pulls data from Salesforce, HubSpot, and Stripe APIs to calculate key metrics. - **Reporting:** Generates a weekly PDF report with visualizations (line graphs for MRR trends, bar charts for churn by segment). - **Alerting:** Flags anomalies (e.g., churn spike >10% week-over-week) and notifies the VP of Product via Slack. - **Integration:** Connects to Google Drive for auto-saving reports and to Notion for updating the executive dashboard. **Constraints:** - Only pull data from the last 30 days to avoid processing delays. - Exclude internal test accounts from churn calculations. - Limit report generation to business hours (9 AM–5 PM PST). **Tools Configured:** - **API Access:** Salesforce (read-only), HubSpot (read-only), Stripe (read-only). - **Communication:** Slack (alerts), Email (weekly reports to vp@acme.com). - **Storage:** Google Drive (auto-save), Notion (dashboard updates). **Automation Schedule:** - **Daily:** Data refresh at 8 AM PST. - **Weekly:** Full report generation every Monday at 9 AM PST. - **Real-time:** Slack alerts for critical anomalies (e.g., churn spike detected). ### Agent Performance Metrics (First 2 Weeks) - **Data Accuracy:** 99.8% (validated against manual calculations). - **Report Delivery:** 100% on-time (no delays in 14 days). - **Alert Response:** 3 critical alerts triggered (all resolved within 2 hours). - **User Feedback:** VP of Product noted the agent "saved 5 hours/week" and improved data reliability. ### Next Steps 1. **Review Alerts:** Check the Slack channel `#growth-alerts` for any pending notifications. 2. **Adjust Thresholds:** Fine-tune anomaly detection (e.g., reduce churn spike threshold to 8%). 3. **Expand Scope:** Add competitor benchmarking data to the weekly report (requires API access to G2).
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