Agentcall (join-meeting) lets your AI agent to join meetings and collaborate like a real teammate
Create detailed user stories, acceptance criteria, and feature specs
Example: Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example: Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example: Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example: Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Submit your Claude Code skill and start earning
epx add pattern-ai-labs/agentcall --skill join-meetingCompatible with
Supported agents
| name | join-meeting |
| description | AgentCall lets an AI agent join a video meeting (Google Meet, Microsoft Teams, Zoom) as a participant with voice and visual presence. Use when asked to join a call, attend a meeting, or participate in a video conference. |
AgentCall lets any AI coding agent join Google Meet, Zoom, and Microsoft Teams as a real participant. The agent can speak via text-to-speech, receive live transcripts, share its screen, show an animated avatar, and read meeting chat — all while keeping its full coding session context.
Pass the meeting link, and optionally the mode, the voice strategy, and a port number.
npx skills add pattern-ai-labs/agentcall --skill join-meeting
Works with Claude Code, Cursor, Codex, Gemini CLI, Windsurf, OpenClaw, and 30 plus other agents.
Complete instructions, scripts, modes, and setup are in the repository: github.com/pattern-ai-labs/agentcall
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionjoin-meetingExecute the skills CLI command in your project's root directory to begin installation:
epx add pattern-ai-labs/agentcall --skill join-meetingFetches join-meeting from pattern-ai-labs/agentcall and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/join-meeting
Restart Cursor to activate join-meeting. Access via /join-meetingin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Time estimate: 30-60 minutes to see productivity improvements
Prerequisites
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
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Keeps context tight: join-meeting is the kind of skill you can hand to a new teammate without a long onboarding doc.
join-meeting is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in join-meeting — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend join-meeting for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added join-meeting from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
join-meeting reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: join-meeting is focused, and the summary matches what you get after install.
I recommend join-meeting for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
join-meeting reduced setup friction for our internal harness; good balance of opinion and flexibility.
Keeps context tight: join-meeting is the kind of skill you can hand to a new teammate without a long onboarding doc.
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