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    Meeting Decision Log Skill

    2

    Transform messy meeting transcripts and notes into structured decision logs, action items, and dependency maps.

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    Meeting Decision Log Skill

    Meeting Decision Log Skill

    Example session with this skill installed

    Analyze these notes: Project Alpha sync. We talked about switching to PostgreSQL. Sarah thinks it's better for scaling. Jim agreed. Sarah needs to check the migration cost by Friday.

    • Read your context and instructions
    • Compiled the meeting decision log

    I have analyzed the Project Alpha sync notes. I have extracted one confirmed decision, one owned action item, and mapped the relevant rationale.

    Meeting Decision Log: Project Alpha Sync

    Executive Snapshot

    • Decisions Made: Switch to PostgreSQL for scaling.
    • Key Action: Migration cost analysis assigned to Sarah.
    • Critical Deadline: Friday (Migration cost check).
    • Blockers: None identified.

    1. Decisions Made

    IDDecisionRationaleOwnerStatus
    D-001Switch to PostgreSQLBetter suited for scaling requirements.Engineering TeamConfirmed

    2. Action Items

    ActionOwnerDeadlineRelated DecisionStatus
    Check migration costsSarahFridayD-001Pending

    3. Decision Rationale Capture

    • Decision: Migrate to PostgreSQL.
    • Why: Improved scaling capabilities compared to the current solution.
    • Alternatives: None explicitly detailed in notes.
    • Constraints: Costs must be evaluated before proceeding.

    4. Accountability Gaps

    • Complete: Migration cost task has an owner and a deadline.
    • Partial: Implementation phase lacks a specific owner beyond "Engineering Team."

    Next steps

    1. Review Sarah's cost analysis on Friday to finalize the migration budget.
    2. Assign a technical lead for the actual migration sequence.
    3. Update the infrastructure roadmap once the cost is approved.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    The problem

    Meeting notes are often walls of text where critical commitments and technical blockers get buried. Project momentum stalls when "we discussed" never turns into "who is doing what by when."

    What it does

    • Extracts concrete decisions, actions, and open questions from messy transcripts or chat logs.
    • Maps every task to an owner and deadline, explicitly flagging items that are unassigned or lack a date.
    • Identifies technical, approval, and external dependencies to surface potential project bottlenecks.
    • Detects decision conflicts and accountability gaps where tasks lack clear deliverables or owners.
    • Generates structured decision logs and executive snapshots for immediate team distribution.

    Why this beats prompting it yourself

    General LLMs often hallucinate owners or turn vague suggestions into firm commitments. This skill uses a strict verification workflow to distinguish confirmed decisions from mere discussion, preserving original relative deadlines and identifying specific gaps in accountability that manual prompting usually misses.

    Use cases

    • Converting a raw Zoom or Teams transcript into a structured technical decision log.
    • Performing an accountability audit on meeting notes to find tasks missing owners or dates.
    • Generating a "next meeting" agenda based on unresolved questions and blocked actions.
    • Mapping complex dependencies between cross-functional teams after a project kickoff.

    Known limitations

    Requires a source text like a transcript, notes, or agenda. It cannot attend live meetings or access external calendar data directly.

    Requires source text (transcript, notes, or agenda). Does not verify if named owners actually exist in your org chart or if dates are holidays.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before any payment.

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    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill is compatible with any AI agent or LLM interface that supports text input, such as ChatGPT, Claude, or specialized project management AI assistants. It works by processing your raw text through a specialized verification workflow to ensure accuracy.

    Unlike a standard prompt, this skill uses a multi-step logic to differentiate between casual discussion and firm commitments. It is specifically programmed to flag missing owners and deadlines, reducing the hallucinations and vague summaries common with general-purpose prompting.

    You receive the production-ready logic for the Meeting Decision Log Skill, along with a configuration guide to help you integrate it into your preferred AI workspace. You will also have access to any minor version updates and bug fixes for the life of the product.

    The skill requires a text-based source, such as a copied transcript from Zoom/Teams, a text file of meeting notes, or an exported chat log. It does not record live audio or join meeting invites directly; it processes the data you provide.

    If a task is mentioned without a clear owner or date, the skill will explicitly flag it as an 'Accountability Gap.' This ensures that you know exactly what needs to be clarified in your follow-up email or next meeting.

    Setup is instantaneous; once you import the skill into your AI agent's environment, you can begin pasting transcripts immediately. There is no complex coding required, as the skill is designed to work out of the box with standard text inputs.

    New in Business & Operations