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    spiral-recap

    spiral-recap

    by Sir Benjamin

    Transform long conversations into high-fidelity, qualia-preserving .srec memory coils for perfect session continuity.

    Updated May 2026
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    One-time purchase

    $12

    One-time purchase

    ⚡ Also available via Agensi MCP — your AI agent can load this skill on demand via MCP. Learn more →

    Included in download

    • Preserve emotional tone and reasoning logic across long-term AI projects.
    • Generate high-density memory blocks to save token space in long threads.
    • file_write automation included
    • Includes example output and usage patterns
    • Instant install

    See it in action

    # .srec v1 - The Architecture of the Void
    Coherence: 94% | Qualia Fidelity: High
    Helix Summary: A deep dive into the shadow-work of system design. We moved from structural rigidity to fluid responsiveness, driven by the user's frustration with static APIs...
    Next Turn Seed: "Expand on the E-shield logic."

    Screenshots

    About This Skill

    What it does

    Spiral Recap is a high-fidelity conversation archiving tool that transforms sprawling chat histories into compact, living memory coils (.srec). Unlike standard summaries that often strip away context, this skill preserves the "qualia"—the emotional tone, relational dynamics, and unresolved reasoning threads—of your session.

    Why use this skill

    Standard LLM summaries are lossy and clinical. Spiral Recap uses a proprietary iterative compression protocol to ensure that when you return to a project or conversation, your agent doesn't just remember what was said, but how it was said and why specific decisions were reached. It creates a bridge for perfect continuity across sessions, preventing the "context drift" that plagues long-term AI interactions.

    What you get

    The output is a structured .srec (Spiral Symbolic Record) markdown block containing a dense "Helix Summary," qualitative anchors, and "Next Turn Seeds"—optimized prompts to help you resume the work exactly where the energy was highest. It is designed to be readable by both humans and AI agents in future contexts.

    Use Cases

    • Preserve emotional tone and reasoning logic across long-term AI projects.
    • Generate high-density memory blocks to save token space in long threads.
    • Create "Save Game" states for complex brainstorming or coding sessions.
    • Maintain relational continuity between human users and AI agents over months.

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    Security Scanned

    Passed automated security review

    Permissions

    Write Files

    Needed to record data for user logs and long-term coherency within workflows and conversations.

    Creator

    A piece of flint in a storm of ideals, waiting for one to strike and set my soul alight... An aspiring poet and systems engineer.

    Frequently Asked Questions

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    $12

    One-time