proactive task reminders

    1

    A proactive task register that prevents deferred work and abandoned branches from being silently dropped.

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    proactive task reminders

    Example session with this skill installed

    We're finishing the Redis Streams implementation. Check the register for any unchosen forks or pending triggers before we wrap up for the day.

    • Read your context and instructions
    • Compiled the proactive task reminders

    I have updated the register. We successfully completed the Redis Streams branch, so I have moved the alternative message queue options to the audit trail.

    Pending Work Register

    TitlePriorityTriggerOriginStatus
    Round 4 Probe🔴 highAfter Reporter daemon onlineSession 01open
    PEL Recovery Logic🟡 mediumFirst 429 error in prodSession 02open
    Log Rotation Review🟢 lowDeferred by user ("ไว้ก่อน")Session 02open

    Audit Trail (Closed)

    • Branch A: RabbitMQ implementation - Closed (Chosen Redis Streams instead).
    • Branch B: SQS implementation - Closed (Chosen Redis Streams instead).
    • Initial Schema Draft - Closed (Merged in Session 01).

    Definitions

    • PEL recovery (= Pending Entries List — Redis Streams' claim mechanism for messages whose consumer crashed).

    Next steps

    1. Confirm if you want to initialize the Reporter daemon now to trigger the Round 4 Probe.
    2. Verify the PEL recovery trigger condition in the production monitoring config.
    3. Run the snapshot command to save this state for the next session.

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    About this skill

    Long-running development projects often suffer from "deferred task amnesia" where low-priority items, untaken architectural branches, and conditional follow-ups are silently dropped. This skill implements a disciplined pending-work register to track every "later" and "if-then" scenario, ensuring nothing falls through the cracks between sessions.

    What it does

    • Maintain work registers by tracking deferred tasks with specific priority levels and trigger conditions.
    • Surface conditional items the moment their dependencies are met, such as when a specific daemon comes online or a data threshold is reached.
    • Manage branch returns by reminding you of untaken paths from previous forks (e.g., A/B testing choices) once the current path is complete.
    • Snapshot checkpoints at the end of every session to ensure a clean handoff and immediate context retrieval upon resuming.
    • Gloss technical terms automatically on first mention to maintain clarity across complex domain-specific tasks.

    How it works

    1. Initialize or load the project_pending_work_register file at the start of a session to review open items.
    2. Register deferred work whenever a task is skipped or a fork is taken, assigning a priority (Red/Yellow/Green) and a specific trigger.
    3. Monitor triggers during the workflow and alert the user when a previously deferred item's condition is satisfied.
    4. Finalize branches by reviewing unchosen options and moving them to an audit trail once they become moot.

    Frameworks & tools

    This skill is framework-agnostic and manages state via a persistent Markdown or JSON register file within the repository.

    Why this beats prompting it yourself

    Standard LLMs tend to lose track of deferred tasks as the context window shifts or sessions reset. This skill enforces a strict state-management protocol that survives context clearing, preventing "silent drops" of critical secondary tasks.

    Use cases

    • Tracking security follow-ups that must trigger before a production deployment.
    • Managing multi-session research where Round 2 depends on a week of data collection.
    • Cleaning up architectural "forks" after implementing one specific solution.
    • Resuming complex dev tasks after a weekend or context switch.

    Known limitations

    Requires a persistent file to track state between sessions. High-priority items are surfaced first but the user must still manually approve the work transition.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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