プラグイン

P0–P4 deterministic-first permission gate with permissive tier, learning sedimentation and approval-history UI; hard-deny credentials and protected paths, auto-allow internal read-only tools.

Forces periodic Engram memory recall and save reminders for DeepSeek Harness agents: injects a dynamic system-prompt context that reminds the model to load prior session memory at the start of a session, and to save new decisions/bugfixes/learnings every

Fail-closed network recovery, recommended answers, and safe unattended continuation for DeepSeek Harness.

Dual-model auto-routing plugin: low-cost direct / high-cost upgrade with an escape-learning closed loop (wrong direct answers auto-learn fingerprints, force-upgrading the same fingerprint next time), persisted and interoperable with the Python ModelRouter.

DeepSeek Harness 用の自己学習ハビットエンジン。ユーザー修正シグナルを検出し、しきい値で低コストモデルによって習慣を判定し、二段階の人手ゲートの背後で候補を確定します。

家族全員のための居心地の良いオフライン語彙トレーナー：1094 の厳選単語、間隔反復、6 種類のクイズ、スペリングゲーム、怠け者向け大画面モード。サイドバーパネルとして開くほか、単一 HTML ファイルとしてスタンドアロン実行も可能。

DSH 向けの深い協働型ライティングエージェント：編集ペアからのユーザー別文体学習、clarify→outline→section-writing→red-team→reader-gallery のフロー、プロジェクトからレポートへの合成（実験レポート／製品紹介／調査／README）、41 の MCP ツール、アプリ内ファイルプレビュー付きの Web 選択改善 UI。

学習したプロンプトプロファイルに照らして各リクエストを書き換え、習慣、ハルシネーション防止ルール、学習記録を自動更新します。

Legal training workbench: three-pane academic UI that reads the "Minglü" (lawagent preset) learning profile (case dossiers, flashcards, wrong-answer book, notes) and sends instructions into a Minglü session with one click.

Coordinates bounded project recall from compatible memory and learning providers, with shared settings and provider lifecycle management.

Report stage — academic paper writing for asset pricing and machine learning research. Ships one skill.

Data stage — data discovery and quality assessment for asset pricing and machine learning research. Ships one skill.

Literature review stage — search, synthesis, and citation-chain tracking for asset pricing and machine learning research. Ships one skill.

Model training stage — end-to-end analysis, model training, and estimation for asset pricing and machine learning research. Ships one skill.

PPT stage — presentation generation (Beamer/Quarto) from the paper for asset pricing and machine learning research. Ships one skill.

Project-based learning coach: a subject-agnostic teaching engine plus swappable domain packs (Unity/C# included), shipped both as a DSH skill and as an installable bundle. The skill protocol enforces attempt-first teaching and graded hints; a zero-dependency validator rejects ability claims their evidence does not support and blocks stage acceptance while blockers are open.

dsh (DeepSeek Harness) plugins for project-level persistent context: session archive with a mechanical index, memory consolidation (CONTEXT.md + MEMORY.md), low-frequency skill autolearn, and automatic handoff.

Algorithm learning toolkit syncing Codeforces and AtCoder submissions, profiling weaknesses, generating AI training plans, and tracking spaced-repetition reviews across a 114-lesson algorithm curriculum.

Bridges the agent to a persistent OKF memory vault over MCP stdio: a Python server (SQLite FTS5 + Markdown) with 10 tools for searching and storing decisions, facts, learnings, conventions, profiles and sources.

Real Red Alert 2 AI battlefield for DeepSeek Harness with fog-safe control and post-match learning

Evidence-backed Skill self-evolution for DeepSeek Harness: redacted trajectory learning, quarantined proposals, arena validation, canary monitoring, automatic rollback.

Beginner starter pack for DeepSeek Harness: welcome flow, 0→1 learning path, scenario-based plugin recommendations and a self-check checklist, paired with the dsh-handbook-zh Chinese tutorial repo.