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    Meeting Decision Log Skillpro

    1

    Transform raw meeting transcripts into structured decision logs, action items, and owner-mapped follow-ups.

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    Meeting Decision Log Skillpro

    Meeting Decision Log Skillpro

    Example session with this skill installed

    Review these notes from the Q3 Planning sync: Sarah agreed to hire a new dev by Oct 1. We discussed the API migration but decided to wait for the security audit. John needs to fix the login bug.

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

    I have processed the Q3 Planning sync notes. I have extracted one approved decision, one deferred decision, and two action items with their respective owners and constraints.

    Meeting Decision Log

    Key Decisions

    DecisionContext/ReasonStatusFollow-Up
    Hire new developerScaling team for Q4 goalsApprovedConfirm budget with HR
    API MigrationWaiting for security audit resultsDeferredReview after audit completion

    Action Items

    Action ItemOwnerDueDependencyStatus
    Hire new developerSarahOct 1NonePending
    Fix login bugJohnNot specifiedNonePending

    Open Questions & Needs

    • Needs Deadline: The action item "Fix login bug" assigned to John requires a specific due date.
    • Needs Information: The security audit timeline is required to schedule the deferred API migration decision.

    Meeting Summary

    The primary outcome of the Q3 Planning sync was the approval of the new developer hire, assigned to Sarah for completion by October 1. The API migration remains the primary blocker, currently deferred pending a security audit. John is tasked with the login bug fix, though a deadline was not established during the discussion.

    Next steps

    • Sarah to verify the developer job description and budget.
    • John to provide an ETR (Estimated Time to Repair) for the login bug.
    • Project lead to confirm the delivery date for the security audit.

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

    About this skill

    Raw meeting transcripts are often a mess of circular discussions and vague commitments. This skill converts unstructured notes into a high-signal decision log, stripping away the noise to focus on what was actually decided and who is responsible for what. It stops the "what did we agree on?" confusion that kills project momentum.

    What it does

    • Decision Extraction identifies approved, rejected, or deferred outcomes with their specific context.
    • Action Mapping links tasks to explicit owners and deadlines while flagging missing assignments.
    • Dependency Detection surfaces blocked actions and items requiring external responses.
    • Follow-Up Wiring connects decisions to their resulting actions to maintain a clear audit trail.
    • Ambiguity Flagging marks unresolved questions and missing owners instead of fabricating data.

    How it works

    1. Input Analysis involves pasting a raw transcript, meeting summary, or rough notes into the chat.
    2. Extraction Phase where the agent separates explicit decisions from general discussion points.
    3. Log Generation creates formatted Markdown tables for decisions and actionable commitments.
    4. Summary Review provides a high-level overview of critical blockers and next steps.

    Frameworks & tools

    This skill is platform-agnostic. It works with text exports from Zoom, Microsoft Teams, Otter.ai, Google Meet, or manual Markdown notes.

    Why this beats prompting it yourself

    Generic prompts often mistake suggestions for final decisions or hallucinate deadlines to be "helpful." This skill uses a strict logic gate to separate approved outcomes from noise and explicitly flags missing data rather than guessing.

    Use cases

    • Post-Meeting Syncs to distribute clear ownership logs to stakeholders.
    • Project Tracking to move decisions into Jira, Linear, or Trello without manual parsing.
    • Governance Audit to document why specific technical or business paths were chosen.
    • Client Debriefs to confirm agreed-upon scope changes and upcoming milestones.

    Known limitations

    Does not support audio files directly; requires text input. Cannot resolve relative dates (e.g., "next Tuesday") without the original meeting date provided in the context.

    Requires text input (no direct audio support). Cannot resolve relative dates without a reference meeting date. Does not infer owners based on job titles.

    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

    The skill requires text-based inputs, such as transcripts exported from Zoom, Teams, or Otter.ai, or even your own rough Markdown notes. It does not process raw audio or video files directly.

    Unlike generic prompts that might guess missing details, this skill uses a logic-based extraction process that flags 'unresolved' items or 'missing owners' rather than hallucinating information. This ensures your project records are accurate and grounded in reality.

    This skill is platform-agnostic and designed to work with any LLM-based agent that supports text-based skills or custom instructions. You can simply add the skill to your preferred AI workspace to start processing transcripts.

    The output is formatted in clean, structured Markdown, making it easy to copy and paste directly into project management tools like Jira, Linear, Notion, or Trello without manual reformatting.

    If the meeting date isn't in the transcript, the skill may struggle with relative terms like 'next Monday.' For the best results, we recommend including the meeting date in the text you paste so the agent can accurately map deadlines.

    When you purchase this skill, you receive the full logic framework and structured instructions required to run the agent, along with any future updates or refinements to the extraction logic.

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