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    Action Item Recovery

    1

    Recover real commitments, owners, deadlines, and blockers from meetings, chats, emails, and notes.

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    Action Item Recovery

    Action Item Recovery

    Example session with this skill installed

    Recover action items from notes dated September 14, 2026 UTC: Maya asked Lina to finish payment retry tests by September 18, and Lina replied “I’ll own it.” Omar suggested updating the rollout guide, but nobody accepted. The team needs staging credentials before verification; no owner or deadline was named.

    • Read your context and instructions
    • Compiled the action item recovery

    Action recovery report

    Confirmed commitments

    ActionClassificationOwnerDue dateEvidence
    Finish payment retry testsCommittedLinaSep 18, 2026Maya requested it and Lina explicitly said, “I’ll own it.”

    Requested or suggested—not yet committed

    ItemStatusWhat is missing
    Update the rollout guideSuggestedAn accepting owner and deadline
    Provide staging credentialsRequired dependencyOwner, delivery date, and confirmation

    Dependency chain

    Verification cannot begin until staging credentials are available. The source does not identify who owns that dependency, so no owner was inferred.

    Follow-up draft

    “Quick ownership check: Lina has accepted payment retry testing for September 18. We still need an owner and delivery date for staging credentials before verification can start. Omar’s rollout-guide idea also needs an accepting owner and deadline if we want it tracked as work.”

    Audit notes

    • One explicit commitment recovered.
    • One suggestion kept separate from committed work.
    • One unassigned dependency flagged.
    • No deadline or owner was invented.

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

    About this skill

    The problem

    Meeting transcripts and chat logs often bury actual commitments under layers of context, leading to missed deadlines and "ownerless" tasks. General summaries frequently fail to distinguish between a casual suggestion and a binding project commitment.

    What it does

    • Extracts concrete tasks, owners, and deadlines from messy unstructured text like Zoom transcripts or Slack exports.
    • Classifies statements into committed, requested, or suggested actions to prevent "wishful thinking" from becoming tasks.
    • Identifies ownership conflicts and unassigned responsibilities that need immediate human resolution.
    • Maps dependencies and required approvals to show the ripple effect of delayed items.
    • Generates a neutral follow-up draft to re-engage owners without manual drafting.

    Why this beats prompting it yourself

    Generic LLM summaries often hallucinate owners or miss subtle relative deadlines. This skill uses a strict evidence-based classification system to ensure every item in the tracker is backed by specific fragments from the source, preventing the creation of "phantom" tasks.

    Use cases

    • Turning a messy Zoom transcript into a structured Project Management board update.
    • Auditing a long email thread to find who actually agreed to do what by when.
    • Generating a list of unassigned blockers after a chaotic planning session.
    • Tracking how deadlines shifted over the course of a multi-day chat discussion.

    Known limitations

    Relative deadlines (e.g., "by next Friday") are only normalized if the source date is provided. It will not infer owners based on proximity to a mention.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Business & Operations.

    Requires explicit source dates for deadline normalization. Won't guess owners without clear evidence. Focuses on extraction, not task execution or management.

    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 buying a skill.

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    Listed1 month ago

    What's inside

    Frequently Asked Questions

    This skill uses an evidence-based classification system to distinguish between casual suggestions and binding commitments, ensuring your task list is free from 'phantom' tasks often created by generic LLM summaries.

    The skill requires unstructured text input, such as Zoom transcripts, Slack exports, or email threads; for relative deadlines like 'by Tuesday' to be accurate, you should also provide the date the source material was created.

    Upon purchase, you receive the full skill logic, configuration documentation, and pre-built templates for mapping extracted items directly into common project management board formats.

    Yes, the skill is designed to identify ownership conflicts and unassigned responsibilities, highlighting specific blockers that require human intervention to resolve.

    This skill is compatible with any AI agent or platform that supports structured text processing and tool-calling, making it easy to integrate into your existing automated workflows.

    New in Business & Operations