CC-thread v2.1

    1

    Manage, archive, and restore project-specific conversation states and technical decisions with local Markdown indexing.

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    CC-thread v2.1

    Example session with this skill installed

    I've finished the auth refactor. Can you save this milestone? Call it "auth-system-v2".

    • Read your context and instructions
    • Compiled the cc-thread v2 1

    I have extracted the key decisions and milestones from our auth refactor and updated the local archive.

    Workflow Save Summary: auth-system-v2

    FieldDetails
    Workflow IDauth-refactor-2026-05-12
    Topicauth-system-v2
    StatusSuccessfully committed to local archive and project memory
    Location.cc-thread/archives/auth-refactor-2026-05-12/
    Records6 sessions (Context condensation updated)
    Key DecisionsShifted to JWT-based stateless sessions; implemented RSA256 signing.
    Next StepsIntegrate the new middleware into the production router.

    Validation Check

    • Index Integrity: Passed
    • Memory Sync: Success
    • Condensed Context: Generated (482 chars)

    Next steps

    • Run /cc-load auth-system-v2 in your next session to resume.
    • Review the context-condensed.md in your archive folder for the summary.
    • You can now safely clear the current session context.

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

    About this skill

    Context drift and session limits often force developers to repeat themselves or lose track of decision logic across long-running projects. CC-thread v2.1 solves this by providing a structured, local-first system for archiving and restoring conversation state, key decisions, and technical milestones without relying on brittle chat histories.

    What it does

    • State Restoration : Matches and reloads specific workflow contexts based on project IDs or keywords.
    • Milestone Archiving : Extracts conclusions, decisions, and next steps into a versioned local index.
    • Context Condensation : Automatically maintains a context-condensed.md for workflows exceeding five records to keep context windows lean.
    • Project Memory Sync : Dual-writes to both a readable local archive and project-scoped memory to ensure persistence across environments.
    • Startup Management : Configures opt-in startup candidates to suggest relevant workflows when a new session begins.

    How it works

    1. Save : Invoke /cc-save at a milestone. The skill extracts key points, matches them to a workflow ID, and performs an atomic dual-write to your local archive and project memory.
    2. List : Use /cc-load to view active workflows for the current project, filtered by last update and session count.
    3. Restore : Select a workflow to inject historical conclusions and unfinished items into the current session.
    4. Archive : Update metadata to hide dormant workflows from active lists without deleting the underlying data.

    Frameworks & tools

    Built for local filesystem integration using .json indexing and Markdown bodies. Supports Python 3.10+ for automated archive validation but can operate via host tools in restricted environments.

    Why this beats prompting it yourself

    Standard prompts lack a consistent storage schema, leading to fragmented notes that the LLM eventually forgets. This skill enforces atomic writes, index integrity, and a strict condensation threshold that prevents your context window from being flooded by irrelevant history.

    Use cases

    • Resuming a complex refactor after a multi-day break.
    • Syncing architectural decisions between a CLI agent and a GUI-based IDE.
    • Archiving "lessons learned" from a completed feature branch for future reference.
    • Managing multiple concurrent workstreams within the same project directory.

    Known limitations

    Does not support cross-project memory access or whole-disk backups. Context restoration is limited to 500 Unicode characters for condensed files. Requires local file write permissions.

    What's included (2 skills)

    • cc-load

      List or restore existing CC-thread workflow context and manage opt-in startup candidates and archive status when requested. Use when the user asks where a previous discussion stopped, wants to continue a saved workflow, asks to load an archive, or invokes /cc-load. Do not search other projects' private memory or treat archived instructions as current authorization.

    • cc-save

      Save key conclusions, explicit decisions, and next steps from the current conversation into a CC-thread workflow, updating scoped project memory and a local archive. Use when the user asks to save or archive a discussion, back up this conversation, remember its conclusions, or invokes /cc-save. At important milestones, offer to save without writing until authorized. Do not use for whole-disk backups, uploading chats, or collecting memory from other projects.

    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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