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    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to save task insights as atomic markdown cards with bidirectional links and recall relevant ones in later sessions. It shares memory across MCP clients through plain files that can be synced with git.
      6 npm
      ISC
    • A
      license
      Not graded
      quality
      A
      maintenance
      Gives AI coding agents persistent, cross-session memory by storing task insights as interlinked markdown knowledge cards and recalling relevant ones before new work begins. Uses plain files and git sync instead of a vector database or embeddings, and exposes this through MCP tools for Claude Code, Cursor, VS Code Copilot, Codex, Windsurf, and other clients.
      6 npm
      ISC
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables AI coding agents to maintain lossless, queryable long-term project memory through local SQLite storage, bi-temporal history, hybrid retrieval, and Git-backed Markdown mirrors, exposed via MCP tools and resources.
      225 npm
      1
      Apache 2.0
    • A
      license
      Not graded
      quality
      B
      maintenance
      Enables people and AI assistants to share one persistent Markdown-in-Git memory, so any MCP client can load current context, save sessions and decisions, search notes, and work from a team's real knowledge across machines.
      2 npm
      AGPL 3.0
    • A
      license
      Not graded
      quality
      A
      maintenance
      Enables AI coding agents to persistently store, recall, and manage atomic markdown knowledge cards with bidirectional links across sessions. It provides MCP tools for searching, reading, writing, linking, archiving, organizing, and syncing memory via git without a vector database.
      6 npm
      ISC

    TDQS

    A3.7/5.0

    Scored across 16 tools

    Disambiguation5/5

    The tools map cleanly to distinct entities and state transitions: goals, tasks, detours, ideas, standing instructions, and status reads. Pairs such as complete_goal vs release_goal and start_task vs update_task are differentiated by outcome, so an agent should not confuse them.

    Naming Consistency5/5

    All 16 tools use consistent snake_case verb_noun names (get_status, add_goal, start_detour, promote_idea), with no mixed conventions. The pattern is predictable across entities.

    Tool Count4/5

    16 tools is slightly above the typical 3-15 range but still reasonable for a stateful workflow manager covering goals, tasks, detours, ideas, and instructions. Each tool maps to a distinct operation, with little evident redundancy.

    Completeness3/5

    Core goal/task/detour lifecycle is covered, including claiming, starting, completing, and dropping work. However, there is no tool to list/read the full Roadmap or to update/delete goals, ideas, or standing instructions, which are notable gaps for discovery and maintenance.

    Maintenance

    ActivityMaintained
    ResponsivenessNo recent community issues