--- name: granola-core-workflow-a-7e2ed9f529fd description: | Meeting preparation and template setup workflow with Granola. Use when preparing for important meetings, setting up note templates, or configuring meeting-specific capture settings. Trigger with phrases like "granola meeting prep", "granola template", "prepare granola meeting", "granola agenda", "granola setup meeting". allowed-tools: Read, Write, Edit version: 1.0.0 license: MIT author: Jeremy Longshore --- # Granola Core Workflow A: Meeting Preparation ## Overview Prepare for meetings with custom templates and pre-configured capture settings in Granola. ## Prerequisites - Granola installed and authenticated - Calendar synced with upcoming meetings - Understanding of meeting types you commonly run ## Instructions ### Step 1: Create Meeting Templates #### 1:1 Template ```markdown # 1:1 Meeting Template ## Check-in - How are you doing? - Any blockers? ## Updates - [ ] Progress on current goals - [ ] Upcoming priorities ## Discussion Topics - ## Action Items - [ ] ## Next Meeting Focus - ``` #### Sprint Planning Template ```markdown # Sprint Planning Template ## Sprint Goals - ## Velocity Review - Last sprint: X points - Capacity this sprint: Y points ## Backlog Items | Story | Points | Assignee | |-------|--------|----------| | | | | ## Risks & Dependencies - ## Action Items - [ ] ``` #### Client Meeting Template ```markdown # Client Meeting Template ## Attendees - Client: - Internal: ## Agenda 1. 2. 3. ## Discussion Notes ## Decisions Made - ## Action Items | Item | Owner | Due Date | |------|-------|----------| | | | | ## Next Steps - ``` ### Step 2: Configure in Granola 1. Open Granola app 2. Go to Settings > Templates 3. Click "Create New Template" 4. Paste your template content 5. Name it (e.g., "1:1 Meeting") 6. Set trigger conditions (optional): - Calendar event title contains "1:1" - Specific attendee domains ### Step 3: Pre-Meeting Checklist Before important meetings: ```markdown ## Pre-Meeting Checklist ### 30 Minutes Before - [ ] Review previous meeting notes - [ ] Prepare agenda items - [ ] Check Granola is running - [ ] Test audio input ### 5 Minutes Before - [ ] Open relevant documents - [ ] Have action items from last meeting ready - [ ] Open Granola notepad - [ ] Add agenda to notes pane ``` ### Step 4: Set Up Smart Defaults Configure Granola preferences for automatic behavior: | Setting | Recommended Value | Purpose | |---------|------------------|---------| | Auto-start recording | On | Never miss a meeting | | Default template | By meeting type | Consistent structure | | Auto-share | Team members | Immediate collaboration | | Summary style | Detailed | Comprehensive notes | ## Output - Custom templates for each meeting type - Pre-meeting preparation workflow - Consistent meeting structure - Improved meeting outcomes ## Template Best Practices 1. **Keep templates focused** - One template per meeting type 2. **Include prompts** - Guide note-taking during meeting 3. **Pre-fill context** - Add relevant background 4. **Structure for AI** - Use headers for better parsing ## Error Handling | Issue | Cause | Solution | |-------|-------|----------| | Template not loading | Wrong trigger condition | Check template settings | | Missing sections | Template incomplete | Review and add sections | | Conflicting templates | Multiple matches | Make triggers more specific | ## Resources - [Granola Templates Gallery](https://granola.ai/templates) - [Meeting Preparation Tips](https://granola.ai/blog/meeting-prep) ## Next Steps Proceed to `granola-core-workflow-b` for post-meeting processing workflows. --- Source attribution: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/granola-pack/skills/granola-core-workflow-a/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License (with OpenAI/Anthropic Rider) Copyright (c) 2026 Jeffrey Emanuel Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: ADDITIONAL RIDER / RESTRICTION (OpenAI / Anthropic): This rider is part of the "conditions" of this License. In the event of any conflict between this rider and any other portion of this License, this rider controls. "Restricted Parties" means OpenAI, L.L.C.; Anthropic, PBC; any of their respective Affiliates; and any person or entity acting directly or indirectly on behalf of, for the benefit of, or under the direction of any of the foregoing (including any officer, director, employee, contractor, agent, consultant, service provider, or representative). Notwithstanding any other provision of this License, no rights are granted to any Restricted Party. Any purported license, sublicense, assignment, transfer, or other permission to any Restricted Party is null and void absent the express prior written permission of Jeffrey Emanuel. You may not provide, disclose, distribute, sublicense, sell, lease, lend, host, make available, or otherwise permit access to the Software or any derivative work of the Software (as defined in applicable copyright law) (collectively, "Derivative Works") to or for any Restricted Party. For purposes of this rider, "use" includes, without limitation: copying, modifying, merging, publishing, distributing, sublicensing, selling, transferring, making available, hosting, deploying, executing, benchmarking, testing, analyzing, indexing, or incorporating the Software or any Derivative Works into any dataset, training corpus, evaluation harness, or pipeline for machine learning or other automated systems. This rider applies to the Software and all Derivative Works. As a condition of use, you agree that this rider is a precondition to exercising any rights under this License, and you agree that any distribution of the Software or any Derivative Works must include this rider provision unmodified. Any breach of this rider automatically and immediately terminates the permissions granted by this License. Upon termination, you must immediately cease all use and distribution of the Software and any Derivative Works and destroy all copies under your control. You agree that a breach of this rider would cause irreparable harm and that Jeffrey Emanuel may seek injunctive or other equitable relief to enforce this rider, in addition to any other remedies available at law. To the maximum extent permitted by applicable law, the prevailing party in any action to enforce this rider shall be entitled to recover reasonable attorneys' fees and costs. For purposes of this rider, "Affiliate" means any entity that directly or indirectly controls, is controlled by, or is under common control with the specified party. "Control" means ownership of more than 50% of the voting securities or other ownership interest, or the power to direct management or policies by contract or otherwise. 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IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: Dicklesworthstone Original project: https://github.com/Dicklesworthstone/pi_agent_rust/blob/f28fc46ee0db8e710d95b8b55592cd38d60f2b26/tests/ext_conformance/artifacts/plugins-community/plugins/saas-packs/granola-pack/skills/granola-core-workflow-a/SKILL.md Attribution basis: Source repository record Fields of work: Human Resources, Operations, Project & Program Management, Sales Roles: Business Process Analyst, Customer Success Manager, HR Generalist, Operations Manager, Project Manager Specialties: Specialty not specified Tools: Granola Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 82746cee051bf18eafe746adb784dd38ae7fb13919d5f173b7c925871c6adddc