Slipbox MCP Server
Slipbox MCP Server

AIアシスタントにナレッジ管理の積極的な役割を与えましょう。SlipboxはMCPサーバーで、MCP互換のエージェントをZettelkastenのパートナーに変えます——アトミックノートの作成、セマンティックリンクの形成、創発的クラスターの検出、既存ナレッジからの洞察の統合を行います。
アイデアを入力すれば、構造化されたナレッジが出力されます。エージェントがフォーマット、リンク、統合を処理します。
このメソッドに初めて触れる方は、Introduction to the Zettelkasten Methodから始めてください。アトミックノートとリンク思考の背後にある理由がわかります。Slipboxがどのようにエージェントにこのメソッドを教え込むかは、接続時に自動的に配信されるサーバーインストラクションをお読みください。
Claudeで構築・テスト済み。あらゆるMCPクライアント(Claude Desktop、Claude Code、OpenCode、Copilot、またはMCPに対応した任意のツール)で動作します。
プレーンファイル、ロックインゼロ。 ノートはYAMLフロントマター付きのMarkdownです——Obsidian、Foam、Logseq、または任意のエディタで読めます。SQLiteデータベースはインデックスであり、真実の源泉ではありません。削除していつでもファイルから再構築できます。
19のMCPツール — ノート、リンク、検索、グラフ分析、クラスター管理用
6つのワークフロープロンプト(対応スキル付き)— Zettelkastenメソッドをエンコードし、セッションごとに再学習する必要がありません
BM25全文検索 — SQLite FTS5によるタイトルとコンテンツの横断検索
クラスター検出 — 創発的なトピックグループを見つけ、ストラクチャーノートを足場にします
7種類の型付きリンク(reference、extends、refines、contradicts、questions、supports、related)
Python 3.10+ | macOS または Linux

ウォークスルー
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Related MCP server: vault-master-mcp
クイックスタート
1. インストール
pipx install slipbox-mcp
# or, with uv:
uv tool install slipbox-mcpこれにより、slipbox-mcpランチャーがPATH(~/.local/bin内)に配置されます。この単一コマンドがMCPサーバー全体です:クローン不要、PYTHONPATH不要、ハードコードされたvenv Pythonパスも不要です。以下のすべてがこれを使用します。インストールせずに試す場合は、uvx slipbox-mcpが使い捨て環境でサーバーを実行します。
(Slipbox自体を開発していますか?開発セクションでクローン+編集可能インストールのセットアップを参照してください。)
2. データディレクトリを選ぶ
1つの変数SLIPBOX_BASE_DIRですべてを設定します:ノートは<base>/data/notesに、SQLiteインデックスは<base>/data/db/zettelkasten.dbに配置されます。サーバーは初回実行時に所有者のみ(0700)の権限でこれらを作成します。
SLIPBOX_BASE_DIR(または以下の個別のSLIPBOX_NOTES_DIR / SLIPBOX_DATABASE_PATHパス)を、共有やシステムの場所ではなく、自分が管理する専用データディレクトリに向けてください。これらのパスはそのまま使用されます:サーバーはその配下でノートツリーとインデックスを管理し、インデックスを再構築する際はノートディレクトリを真実の源泉として扱います。
# Example: use any absolute path you like
/Users/yourname/.local/share/mcp/slipbox完全な絶対パスを使用してください。先頭の
~はMCPクライアントの設定ファイル内では展開されず、リテラルな~ディレクトリが作成されます。
3. MCPクライアントに接続
Claude Code(ファイル編集不要の単一コマンド):
claude mcp add slipbox \
--env SLIPBOX_BASE_DIR=/Users/yourname/.local/share/mcp/slipbox \
-- slipbox-mcpClaude Desktop(設定ファイルを編集):
macOS:
~/Library/Application Support/Claude/claude_desktop_config.jsonLinux:
~/.config/claude/claude_desktop_config.json
{
"mcpServers": {
"slipbox": {
"command": "slipbox-mcp",
"env": {
"SLIPBOX_BASE_DIR": "/Users/yourname/.local/share/mcp/slipbox"
}
}
}
}DesktopのPATHに関する注意: macOS Desktopアプリは
~/.local/binをPATHに常に継承するとは限らないため、裸の"slipbox-mcp"が解決されない場合があります。サーバーが起動しない場合は、"command": "slipbox-mcp"をwhich slipbox-mcpで表示される絶対パス(通常は/Users/yourname/.local/bin/slipbox-mcp)に置き換えてください。
その他のMCPクライアント: slipbox-mcpをサーバーコマンドとして登録し、環境にSLIPBOX_BASE_DIRを設定してください。コマンドとenvはどこでも同じです。
SLIPBOX_BASE_DIRの代わりに、絶対パスを個別に設定します。オプションのSLIPBOX_LOG_LEVELはDEBUG、INFO、WARNING、ERRORのいずれかです。
"env": {
"SLIPBOX_NOTES_DIR": "/Users/yourname/.local/share/mcp/slipbox/notes",
"SLIPBOX_DATABASE_PATH": "/Users/yourname/.local/share/mcp/slipbox/data/db/zettelkasten.db",
"SLIPBOX_LOG_LEVEL": "INFO"
}4. 再起動して確認
クライアントを再起動します(Claude Codeは次回起動時にリロードされます。Claude Desktopは終了して再度開いてください)。
エージェントに聞いてみましょう:
「何かについてテストノートを作成して」
「slipboxでtestを検索して」
「孤立ノートを見つけて」
動作例
上記のヒーローがコアループです。以下がエージェントが行うその他の動作です。
プロアクティブメンテナンス
エージェントはセッション開始時にslipbox://maintenance-statusリソースを読み取り、整理が必要なクラスターを表面化します。

全文検索
slipbox_search_notesによるノート横断のBM25ランキング検索。

ナレッジグラフ:中心ノート
slipbox_find_central_notesはグラフの構造的アンカー——他のすべてが周回するノート——を表面化します。

ノート分析
analyze_noteプロンプトはアトミック性を評価し、既存グラフ内の実際の接続を見つけ、タグを提案し、明確さのために書き直します。

ソース分解
knowledge_creationプロンプトは記事を適切な引用とリンク付きのアトミックな文献ノートに分割します。

クラスター検出
slipbox_get_cluster_reportはストラクチャーノートを欠いた共起タグのグループを見つけます。サイズ、孤立率、リンク密度、新しさでスコアリングされます。

ストラクチャーノート作成
slipbox_create_structure_from_clusterはストラクチャーノートの足場を作り、全メンバーノートをリンクし、クラスターを却下します。

孤立ノート
slipbox_find_orphaned_notesは未統合のナレッジ——接続または削除の候補——を表面化します。

類似ノート
slipbox_find_similar_notesは共有タグ、共通リンク、コンテンツの重複から類似性を計算します。

グラフ走査
slipbox_get_linked_notesはハブノートからの型付きリンクをリンクタイプごとにグループ化して表示します。

ナレッジ統合
knowledge_synthesisプロンプトは未接続の領域間の橋渡しを見つけ、既存ナレッジから統合ノートを提案します。

ロックインゼロ:Obsidianのプレーンファイル
ノートはプレーンなMarkdownです。Obsidianでボールトを開けばすべてが機能します——レンダリングされたコンテンツ、バックリンク、ナレッジグラフ。
Obsidianの型なし組み込みグラフではなく、型付きリンクを色でレンダリングするグラフが必要な場合は、コンパニオンプラグイン**Slipbox Semantic Graphをインストールしてください——人間が読めるタイトルと色分けされたセマンティックリンクタイプを備えたフォース指向ビューです。0.1.0リリースから手動でインストールします:main.js、manifest.json、styles.cssを<vault>/.obsidian/plugins/slipbox-graph/にコピーし、設定 → コミュニティプラグインで有効にします。(公式ディレクトリに承認されれば、設定 → コミュニティプラグイン → 参照 → 「Slipbox Semantic Graph」の検索からもインストールできるようになります。)サーバーが書き込むのと同じフロントマターidと## Linksセクションを読み取るため、追加設定は不要です。Open semantic graphコマンド(コマンドパレット)またはgit-fork**リボンアイコンでビューを開きます。

上部の凡例は各色をリンクタイプ(extends、refines、supports、contradicts、questions、related)に対応付けます。ストラクチャーノートに焦点を当てると、そのコンステレーションが見えてきます。ここでは、Contract Testing Knowledge Mapとそのメンバーノートが周回しています:

オプション:自動クラスター検出
クラスター分析はすべてのノートをスキャンし、類似度スコアを計算します。毎日(午前6時)実行すると結果が事前計算され、slipbox_get_cluster_report()が即座に返ります。スケジュールがない場合、クラスター検出はオンデマンドで実行され、大規模なコレクションでは遅くなります。
一括インポート後、大規模な再編成後、または即時の結果が必要なときに手動で実行してください。
クラスター検出のインストール(macOS)
chmod +x scripts/install-cluster-detection.sh
./scripts/install-cluster-detection.shインストーラーはPython/venvパスを検出し、LaunchAgentのplistを生成してロードします。
手動テスト(ファイルウォッチャー)
source .venv/bin/activate
python scripts/detect_clusters.py出力は~/.local/share/mcp/slipbox/cluster-analysis.jsonに保存されます。
クラスター検出のアンインストール
./scripts/install-cluster-detection.sh --uninstallオプション:自動インデックス用のmacOSファイルウォッチャー
MCPサーバーは高速検索用のデータベースインデックスを維持します。Obsidian(または任意のエディタ)でノートを編集すると、slipbox_rebuild_indexを実行するまでデータベースが古くなります。
ファイルウォッチャーはバックグラウンドデーモンとして実行され、ノートディレクトリを監視し、.mdファイルが変更されるとインデックスを自動的に再構築します。
Obsidianでノートを頻繁に編集しながらClaudeも使用する場合に使用してください。
ファイルウォッチャーのインストール(macOS)
chmod +x scripts/install-file-watcher.sh
./scripts/install-file-watcher.shインストーラーはPython/venvパスを検出し、必要に応じてwatchdogをインストールし、LaunchAgentをロードします。ログイン時に起動し、クラッシュした場合は再起動します。
手動テスト
source .venv/bin/activate
python scripts/watch_notes.pyノートファイルを編集します。ウォッチャーの出力に「rebuilding index...」と表示されるはずです。
ステータス確認
launchctl list | grep slipbox.watcher
# View logs
tail -f ~/.local/share/mcp/slipbox/watcher.logファイルウォッチャーのアンインストール
./scripts/install-file-watcher.sh --uninstall推奨システムプロンプト
Slipboxはベースラインを自動的に配信します:すべてのクライアントは接続時にサーバーインストラクションを受け取り、ツールの適切な使い方——ノートタイプ、リンクのセマンティクス、品質基準、検索前作成などのコアワークフロー——をカバーします。これらを自分で追加する必要はありません。
docs/SYSTEM_PROMPT.mdはその上のオプトインレイヤーです:サーバーが単独で主張すべきではない自律性とイニシアチブの指示です。エージェントのプリファレンスまたはシステムプロンプトに追加して、以下を有効にします:
会話中の自動ナレッジキャプチャ
会話開始時のクラスター創発検出
ツールリファレンス
コアノート操作
ツール | 説明 |
| アトミックノートを作成(fleeting/literature/permanent/structure/hub) |
| IDまたはタイトルでノートを取得 |
| 既存ノートを更新 |
| ノートを削除 |
リンク
ツール | 説明 |
| ノート間のセマンティックリンクを作成 |
| リンクを削除 |
| 特定のリンクを削除(リンクが存在しない場合はエラー) |
| ノートにリンクされた/からのノートを取得 |
検索と発見
Tool | Description |
| テキスト(BM25ランキング)、タグ、または種類で検索 |
| 指定したノートに類似するノートを検索 |
| 最も接続されているノートを検索 |
| 接続されていないノートを検索 |
| 日付範囲でノートを一覧表示 |
| すべてのタグを一覧表示 |
クラスター分析
Tool | Description |
| 構造ノートが必要な未処理クラスターを取得 |
| クラスターから構造ノートを作成 |
| クラスター分析を再生成 |
| 提案からクラスターを完全に除外 |
メンテナンス
Tool | Description |
| ファイルからデータベースインデックスを再構築 |
プロンプトリファレンス
MCPプロンプトは、ツェッテルカステン法を組み込んだ再利用可能なワークフローテンプレートで、毎回のセッションで説明し直す必要がありません。
Prompt | Description | Use When |
| 情報を3〜5個のアトミックノートに処理する | 記事、アイデア、ノートを追加するとき |
| 大量の情報を5〜10個のノートに処理する | 書籍や長編コンテンツを処理するとき |
| 既存知識への接続をマッピングする | トピック間の関連を探るとき |
| 高次の洞察を生み出す | アイデア間の橋渡しを見つけるとき |
| スリップボックスに適したノートか評価する | 新しいノートまたは既存ノートを見直すとき |
| 未処理のメンテナンス事項を明らかにする | 作業セッションの開始時 |
呼び出し方: スラッシュコマンドとスキル
各ワークフローには2つの方法が用意されています:
MCPプロンプト: 実行中のサーバーによって提供されます。
スキル: 同じワークフローを実行し、自然言語によるトリガーを追加するスタンドアロンバンドル (
skills/<name>/) です。
6つのスキルのうち5つは、サーバーが使用するのと同じ PROMPT_* テンプレートから生成されます (src/slipbox_mcp/server/descriptions.py)。コミットされた skills/ がこれらのテンプレートから逸脱しているとCIは失敗します。6つ目の cluster-maintenance は、そのMCPプロンプトが再利用可能なワークフローではなく実行時にレンダリングされるステータスメッセージであるため、scripts/build_skills.py に直接記載されています。
スラッシュコマンドは確実な方法です。Claude Code は MCP プロンプトを /mcp__<server>__<prompt> として表示します。ピッカーを開くには /mcp__slipbox-mcp__ と入力してください:
/mcp__slipbox-mcp__knowledge_creation
/mcp__slipbox-mcp__knowledge_exploration
/mcp__slipbox-mcp__knowledge_synthesis
/mcp__slipbox-mcp__knowledge_creation_batch
/mcp__slipbox-mcp__analyze_note
/mcp__slipbox-mcp__cluster_maintenance(インストールされたスキルは、ディレクトリ名で独自のスラッシュコマンドも公開します。例: /slipbox-analyze-note。)
自然言語は、対応するスキルがインストールされていれば機能します。やりたいことを説明するだけです:
Analyze this note for my slipbox: [paste note]
Add this to my slipbox: [paste article]
Synthesize my notes on attention and memory.散文によるトリガーは、スキルがインストールされ、そのフレーズがスキルの説明と一致している場合に機能します。発火しない場合はスラッシュコマンドにフォールバックしてください。モデルに「use the analyze_note prompt」と名前で指示しても機能しません。モデルはMCPプロンプトを名前で呼び出せないためです。スラッシュコマンドを使うか、自然言語からスキルをトリガーさせてください。
スキルのインストール
Claude Code は、スキルを .claude/skills/(プロジェクト単位)または ~/.claude/skills/(グローバル)から発見します。裸のトップレベル skills/ からは発見しません。必要なスキルをディスカバリパスにシンボリックリンクまたはコピーしてください(例: このプロジェクトの場合):
mkdir -p .claude/skills
ln -s ../../skills/slipbox-analyze-note .claude/skills/slipbox-analyze-note
# ...or copy the directories, or symlink all sixClaude Desktop では、各スキルが .skill バンドルである必要があります。ビルドしてからアップロードしてください:
python scripts/build_skills.py # writes dist/*.skill設定 → スキル → スキルをアップロード と移動し、dist/ から必要なバンドルを選択してください。それぞれがスラッシュコマンドと自然言語トリガーの両方としてインストールされます。
descriptions.py でプロンプトテンプレートを編集した後、ビルドを再実行してスキルを再生成してください。
リンクタイプ
Type | Use When | Inverse |
| 一般的な「関連情報」のつながり | reference |
| 別のアイデアに基づいて構築する | extended_by |
| 明確化または改善する | refined_by |
| 反対の見解 | contradicted_by |
| 疑問を提起する | questioned_by |
| 証拠を提供する | supported_by |
| 緩いつながりのテーマ的関連 | related |
ノートタイプ
Type | Purpose |
| 素早いメモ、未処理の考え |
| 引用付きの情報源からのアイデア |
| 自分の言葉で洗練されたアイデア |
| 特定のトピックに関する7〜15個の関連ノートを整理するマップ |
| 構造ノートにリンクするドメイン概要。広範な知識領域をナビゲートするための入り口 |
構造ノート vs. ハブノート: 構造ノートは、単一のトピックを中心にパーマネントノートのクラスターを整理します。ノート自体の一階層上の、厳選されたマップです。ハブノートは、さらに一階層上で動作します。知識ドメイン全体にわたって構造ノート(および場合によっては主要なパーマネントノート)にリンクします。構造ノートが「Xについて何を知っているか?」に答えるのに対し、ハブノートは「このドメイン全体の知識がどのように整理されているか?」に答えます。ほとんどのツェッテルカステンは、少数のハブノートだけで十分です。
ファイル形式
ノートはYAMLフロントマター付きのMarkdownファイルとして保存されます:
---
id: "20251217T172432480464000"
title: "Poetry Revision Principles"
type: structure
tags:
- poetry
- revision
- craft
created: "2025-12-17T17:24:32"
updated: "2025-12-17T17:24:32"
---
# Poetry Revision Principles
Content here...
## Links
- reference [[20250728T125429845760000]] Member of structureこれらのファイルは、任意のテキストエディタまたはObsidianで直接編集できます。外部で編集した後は slipbox_rebuild_index を実行してください。
アップグレード
新しいバージョンを取得したら、Claude Desktop を再起動してください。リリースノートにデータベースの変更が記載されている場合は、slipbox_rebuild_index を一度実行して既存のデータベースを最新の状態にしてください。
FTS5検索へのアップグレード(FTS5リリース以降の任意のバージョン): 全文検索インデックスは、サーバーが新しいデータベースに対して起動すると自動的に作成されます。既存のデータベースの場合、FTS5テーブルは最初の起動時に作成されますが、以下を実行するまで空のままです:
slipbox_rebuild_indexこれにより、既存のノートからBM25インデックスが生成されます。これが完了するまで、検索結果は関連性順にランク付けされません。
トラブルシューティング
Claude Desktop でサーバーが読み込まれない
ランチャーが解決されることを確認します:
which slipbox-mcpがパス(通常は~/.local/bin/slipbox-mcp)を表示するはずです。ターミナルでは解決されるのにDesktopで起動できない場合、GUIアプリがPATH上で
~/.local/binを認識していません。"command": "slipbox-mcp"を手順1の絶対パスに置き換えてください。Claude Desktop のログでエラーを確認してください。
slipbox-mcp: command not found
コンソールスクリプトがインストールされていないか、PATHにありません。pipx install --editable . --force で再インストールし、which slipbox-mcp で確認してください。pipx のbinディレクトリがPATHにない場合は、pipx ensurepath を実行してシェルを再起動してください。
ノートディレクトリがリテラルで ~/... を指す
ノートディレクトリがCWD相対の ./~/... になってしまった場合、JSON設定で ~ を使用したことが原因です。Claude Desktop は ~ を展開しません。完全な絶対パスに置き換えてください。
検索結果が返らない
FTS5インデックスが生成されていない可能性があります。
slipbox_rebuild_indexを一度実行して既存のノートをインデックス化してください。最近Claudeの外部でノートを編集した場合、インデックスが古くなっている可能性があります。
slipbox_rebuild_indexを実行してください。
slipbox_list_notes_by_date が空の結果を返す
start_date が end_date より後の場合、一致するノートがなく、空の結果が返されます。これは期待される動作であり、エラーではありません。
データベースの同期がずれている
MCPサーバーの外部でノートが編集された場合:
slipbox_rebuild_indexクラスター検出が実行されていない
launchctl list | grep slipbox.cluster-detection
# Should show: - 0 com.slipbox.cluster-detection
# Check logs
cat /tmp/slipbox-clusters.log
# Reinstall if needed
./scripts/install-cluster-detection.sh --uninstall
./scripts/install-cluster-detection.shファイルウォッチャーが実行されていない
launchctl list | grep slipbox.watcher
# Should show: - 0 com.slipbox.watcher
# Check logs
cat ~/.local/share/mcp/slipbox/watcher.log
# Reinstall if needed
./scripts/install-file-watcher.sh --uninstall
./scripts/install-file-watcher.shZETTELKASTEN_* 環境変数からのアップグレード
以前に ZETTELKASTEN_NOTES_DIR、ZETTELKASTEN_DATABASE_PATH、またはその他の ZETTELKASTEN_* 変数を使用していた場合、それらは読み取られません。対応する SLIPBOX_* に名前を変更してください:
Old | New |
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サーバーは古い名前を検出すると警告をログに記録しますが、自動的に移行はしません。
クラスターレポートのパスは設定不可
クラスター分析レポートは、SLIPBOX_BASE_DIR や SLIPBOX_NOTES_DIR に関係なく、常に ~/.local/share/mcp/slipbox/cluster-analysis.json に書き込まれます。非デフォルトのパスを使用している場合でも、クラスターレポートはデフォルトの場所に置かれます。
インストールスクリプトはmacOS専用
scripts/install-cluster-detection.sh と scripts/install-file-watcher.sh のスクリプトは、macOSにしか存在しない launchctl と ~/Library/LaunchAgents/ を使用します。Linuxでは、同等のsystemdユニットまたはcronジョブを手動で作成する必要があります。関連するREADMEセクションの手動テストコマンドを参照して、基盤となるPythonスクリプトがお使いのプラットフォームで動作することを確認してください。
デフォルトパスは作業ディレクトリ相対
SLIPBOX_NOTES_DIR と SLIPBOX_DATABASE_PATH が設定されていない場合、サーバーは現在の作業ディレクトリ相対で data/notes と data/db/zettelkasten.db をデフォルトにします。Claude Desktop 経由で実行する場合、CWDが想定と異なることがあります。これを避けるには、常に claude_desktop_config.json に絶対パスを設定してください。
開発
セットアップ
git clone https://github.com/jamesfishwick/slipbox-mcp.git
cd slipbox-mcp
uv venv && uv pip install -e ".[dev]"テスト
このプロジェクトには3段階のテストがあります:
層 | 件数 | 速度 | コスト | コマンド |
ユニット + 統合 | 219 | ~2秒 | 無料 |
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ツール契約テスト | 22 | ~0.5秒 | 無料 |
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LLM評価 | 28 | ~10分 | 約$3-5 |
|
# Default: runs unit + contract tests (CI runs this)
pytest
# Run everything except LLM evals
pytest tests/ evals/tool_contracts/
# Run LLM evals (requires claude CLI authenticated)
pytest evals/llm/ -v
# Run LLM evals with a specific model
EVAL_MODEL=sonnet pytest evals/llm/ -v
# Lint
ruff check src/ evals/ユニットテストは内部ロジックをカバーします -- サービス、リポジトリ、モデル、パース処理。
ツール契約テストは、LLMが見るMCPツールの出力形式を検証します -- パース可能な構造、チェーン(作成 -> 検索 -> 取得)、役立つエラーメッセージなど。これらは決定的で、LLMを呼び出しません。
LLM評価は、MCPサーバーを接続した claude CLI を介してLLMにプロンプトを送信し、データベースの状態(作成されたノート、作成されたリンク、適用されたタグ)を検査して結果を採点します。これにより、ツールの説明が与えられたときにLLMが実際にツールを正しく使用するかどうかをテストします。
CI/CD
ブランチ保護: main への直接プッシュはブロックされます。すべての変更はPRを経由します。
ワークフロー | トリガー | ランナー | 内容 |
| すべてのPR + mainへのpush | GitHubホステッド | ユニットテスト + コントラクトテスト、ruff lint + format |
| オプトイン(ラベルまたは手動) | セルフホステッド | claude CLIによるLLM評価28件 |
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| GitHubホステッド | release-please PR。マージ時にビルド + PyPIへ公開 |
LLM評価スイートは高コスト(約$3〜5、約10分)で、セルフホステッドランナー上で実行されるため、自動で実行されることは決してありません。パスベースのトリガーでは、実際のプロンプト変更と見た目だけの再フォーマットを区別できません。プロンプトやツール説明のセマンティクスを変更するときは、意図的に実行してください:
PRに
run-llm-evalsラベルを追加します。ラベルが付いている間、実行され、pushのたびに再実行されます。またはActionsタブから手動でトリガーします(
workflow_dispatch)。またはランナーなしでローカル実行します:
pytest evals/llm/ -v。
ラベルも手動ディスパッチもなければ、ジョブはスキップされます(ランナーは割り当てられず、コストもかかりません)。
評価セットアップのカスタマイズ
セルフホステッドランナーが不要な場合: .github/workflows/llm-evals.ymlを削除し、プロンプト変更をマージする前にローカルでpytest evals/llm/ -vを実行してください。
すべてのPRでLLM評価を自動実行したい場合: 関連するpaths:フィルタ付きのpull_requestトリガーを追加し、ジョブのif:からラベルゲートを外してください。ただし、フォーマットのみの編集による偶発的なトリガーが発生することを想定してください。
デフォルトの評価モデルを変更する場合: 環境変数またはワークフローファイルでEVAL_MODELを設定してください。デフォルトは速度/コストの観点からhaikuです。
セルフホステッドランナーをセットアップする場合:
# Get a registration token
gh api repos/OWNER/REPO/actions/runners/registration-token -X POST -q '.token'
# Download and configure
mkdir -p ~/.github-runners/slipbox-mcp && cd ~/.github-runners/slipbox-mcp
curl -sL -o actions-runner.tar.gz https://github.com/actions/runner/releases/latest/download/actions-runner-osx-arm64-2.325.0.tar.gz
tar xzf actions-runner.tar.gz
./config.sh --url https://github.com/OWNER/REPO --token <TOKEN> --unattended
nohup ./run.sh &PyPIへのリリース
リリースは自動化されています。Releaseワークフロー(.github/workflows/release.yml)は、mainへのpushのたびにrelease-pleaseを実行し、PyPIのTrusted Publishing(OIDC)経由で公開します。そのため、APIトークンはリポジトリシークレットに保存されません。
フロー(バージョンを手作業で編集したり、タグをpushしたりすることはありません):
Conventional Commitメッセージで
mainに変更を取り込みます(feat:→ マイナーバンプ、fix:→ パッチ、feat!:/BREAKING CHANGE:→ メジャー)。リポジトリのコミットフックはこの形式をすでに強制しています。release-pleaseは常設の**「release PR」**を開いたままにし、次のバージョンバンプ(
src/slipbox_mcp/__init__.py内)と、それらのコミットから生成されるCHANGELOG.mdエントリを蓄積します。リリースの準備ができたら、release PRをマージします。 それによりリリースタグ(
v<version>)が付き、同じワークフロー実行内でsdist + wheelのビルド、twine checkの実行、PyPIへの公開が行われます。
つまり、リリースの作成はワンクリックです:ボットのPRをマージするだけ。他には何もありません。
コミットタイプがバージョンを決定します。したがって正確にタイプしてください。 バンプは、前回リリース以降のConventional Commitプレフィックスから機械的に計算され、変更の規模からは計算されません。feat:/fix:は出荷されるパッケージへの変更のために予約し、それ以外にはリリース対象外のタイプを使用してください:
プレフィックス | バージョンへの影響 | 使用目的 |
| minor(1.3.0 → 1.4.0) | パッケージの新しい実行時機能 |
| patch(1.3.0 → 1.3.1) | パッケージのバグ修正 |
| major(1.3.0 → 2.0.0) | 後方互換性のない変更 |
| なし | ドキュメント、ツール、CI、パッケージング、内部のみの変更 |
リリース対象外のコミットだけのバッチでは、release PRは一切生成されません。release-pleaseが読み取るのはスカッシュマージのタイトルなので、PRタイトルのプレフィックスが重要です。かけた労力ではなく、パッケージが得るものに基づいてラベルを付けてください。
一度だけのセットアップ(このリポジトリでは実施済み。フォーク用に文書化):
PyPIで、プロジェクト
slipbox-mcpのpending trusted publisherを登録します:Owner:jamesfishwick· Repository:slipbox-mcp· Workflow:release.yml· Environment:release。4つすべてが正確に一致する必要があります。GitHubで、
releaseという名前の環境を作成します(Settings → Environments)。デプロイ参照を制限する場合は、タグルールv*を追加します(同名のブランチルールはタグに一致しません)。
バージョンは
src/slipbox_mcp/__init__.py内で一度だけ定義されます(release-pleaseがバンプし、# x-release-please-versionマーカーがどの行かを示します)。pyproject.toml(dynamic = ["version"])とサーバーのserver_versionはどちらもそこから読み取るため、同期を保つものは何もありません。release-pleaseが作成するタグは、構造上常にパッケージバージョンと一致します。
公開せずにビルドをリハーサルするには、手動で実行します:python -m build && twine check dist/*(アップロードをドライランするには、TestPyPIトークンを使ってtwine upload --repository testpypi dist/*を実行します)。
共有プロンプト定数
すべてのツール説明とプロンプトテンプレートはsrc/slipbox_mcp/server/descriptions.pyにあります。MCPサーバーと評価テストの両方がこの単一の情報源からインポートします。プロンプトを変更した場合、評価テストは新しい文言でもLLMが正しく動作するかどうかをテストします。
デバッグログ
SLIPBOX_LOG_LEVEL=DEBUG python -c "from slipbox_mcp.main import main; main()"CLIツール
slipboxコマンドは、機械的な操作のためのターミナルアクセスを提供します:
slipbox status # Overview of notes, tags, orphans, pending clusters
slipbox search <query> # Find notes by text
slipbox clusters # Show pending structure note candidates
slipbox orphans # List unconnected notes
slipbox rebuild # Rebuild index (add --clusters to refresh cluster analysis)
slipbox export <id> # Export note markdown to stdout
slipbox tags # List all tags with usage countsインストール:pipx install --editable .(slipboxがPATHに追加されます)
実験的:エージェントメモリとしてのSlipbox
未検証の仮説であり、推奨されるセットアップではありません。上記のすべては、エージェントがあなたの知識を管理するのに役立ちます。これはそれを逆転させます:エージェントは、ネイティブメモリやルールファイルの代わりに、セッションをまたいだ独自の永続メモリとしてslipboxを使用します。
モデルはセッション間でメモリを持たないため、slipboxはあるセッションが次のセッションに残せる唯一のチャネルです。エージェントは、まっさらな後続セッション向けのブリーフィング(失敗とその理由、繰り返し発生する制約、修正、苦労して得た事実)を書き、agent-memoryタグを付け、行動する前にそのタグを検索します。狙いは、接続されたメモリがフラットなルールファイルに勝るということです。なぜなら、たどって取得できるからです。
先に知っておくべき3つのこと:名前空間の分離はタグの規約であり、強制されないため、別のslipboxインスタンスに対して実行してください。「メモリ」は誤称であり、ノート自体以外は永続しません。そして、成長の規律は未証明の部分であり、最初の実行ではスプロールが発生することを想定してください。詳細な解説と注意事項:Slipbox as Agent Self-Memory。
ドキュメント
ドキュメント | 内容 |
ノートIDの形式、5つのノートタイプ、およびこのメソッドの1ページのチートシート。 | |
エージェントを介さず、Obsidianで同じワークフローを手動で実行する方法。 | |
Slipboxのリンクが | |
同じボールトを読み書きできる他のツール。 | |
オプトインの自律レイヤー:自動キャプチャ、クラスター検出、エージェントメモリ実験。 | |
ツールの使用例を示す実施済みセッション。 |
コントリビューション
セットアップ手順、コーディング標準、変更の提出方法についてはCONTRIBUTING.mdを参照してください。
ロードマップ
計画中の機能と今後の方向性についてはROADMAP.mdを参照してください。
スポンサー
slipbox-mcpが役に立つなら、プロジェクトへのスポンサー登録を検討してください。
ライセンス
MIT
Available Tools
19 toolsslipbox_create_linkA
Create a semantic link between two notes.
Links are directional: source -> target. Use bidirectional=true for important relationships (automatically creates inverse link type).
Link Types:
reference: Generic "see also" connection
extends: Source builds upon target (inverse: extended_by)
refines: Source clarifies or improves target (inverse: refined_by)
contradicts: Source presents opposing view (inverse: contradicted_by)
questions: Source raises questions about target (inverse: questioned_by)
supports: Source provides evidence for target (inverse: supported_by)
related: Loose thematic connection (symmetric)
Best Practices:
Always add description explaining WHY notes are linked
Use bidirectional=true for substantive relationships
Create links immediately after creating notes
Args: source_id: ID of the source note (the note doing the linking) target_id: ID of the target note (the note being linked to) link_type: One of reference/extends/refines/contradicts/questions/supports/related description: Brief explanation of the relationship bidirectional: If true, creates inverse link from target to source
| Name | Required | Description | Default |
|---|---|---|---|
| link_type | No | reference | |
| source_id | Yes | ||
| target_id | Yes | ||
| description | No | ||
| bidirectional | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It explains directionality (source -> target), the automatic inverse link when bidirectional=true, and enumerates all link types with their inverses. This covers core behavior well, though it omits details about error handling or note existence validation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections for purpose, link types, best practices, and args. It is fairly long but every sentence is informative and avoids redundancy, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It covers all essential details for correct invocation: direction, link types, bidirectional behavior, parameter meanings, and best practices. The existence of an output schema means return values need not be explained. It lacks edge-case details (e.g., duplicate links), but that is not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (schema only gives types and defaults), but the description fully compensates by explaining each parameter, including the valid values for link_type and the meaning of bidirectional. This adds significant semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: creating a semantic link between two notes. It distinguishes itself from sibling tools like slipbox_delete_link and slipbox_get_linked_notes by focusing on the create operation, and it adds nuance with directionality and link type semantics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides best practices (e.g., 'Create links immediately after creating notes') and explains when to use bidirectional=true, giving clear contextual guidance. However, it does not explicitly compare to alternatives like slipbox_remove_link or slipbox_get_linked_notes, which is a minor gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_create_noteA
Create a new atomic Zettelkasten note.
Each note should contain exactly one idea. After creating, immediately
link to related notes using slipbox_create_link.
Note Types:
- fleeting: Quick captures, unprocessed thoughts (process within 24-48 hours)
- literature: Ideas extracted from sources. REQUIRES at least one entry
in references (citation or URL). If you don't yet have the citation,
use 'fleeting' as a staging type and promote to 'literature' once
the source is attached.
- permanent: Refined ideas in the user's own words (the core of your Zettelkasten)
- structure: Maps organizing 7-15 related notes on a topic
- hub: Entry points into major knowledge domains
Authoring:
- Store `content` exactly as the user provided it. Do NOT rewrite,
expand, or restructure their words. Compose or refine content only
when explicitly asked (e.g. "draft", "refine", "make it standalone").
Best Practices:
- Title should express the idea in brief (understandable without reading content)
- A refined permanent note typically runs 3-7 paragraphs and stands
alone; match the length of what the user gave you, though — a
one-line capture stays one line.
- Use 2-5 specific tags; prefer existing tags when they fit
- Search first (slipbox_search_notes) to avoid duplicating existing notes
Args:
title: Concise title expressing the core idea
content: Full note content in markdown
note_type: One of fleeting/literature/permanent/structure/hub (default: permanent)
tags: Comma-separated tags, e.g. "poetry,revision,craft"
references: Newline-separated citations to external sources (e.g. "Ahrens, S. (2017). How to Take Smart Notes.
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | ||
| title | Yes | ||
| content | Yes | ||
| note_type | No | permanent | |
| references | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden and excels: it mandates exact content preservation ('Store content exactly as the user provided it'), explains note type behavior, requires references for literature notes, and warns against rewriting unless explicitly asked. This goes far beyond what the schema alone conveys.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but appropriately structured into labeled sections (Note Types, Authoring, Best Practices, Args), with every section adding practical guidance. The core purpose is front-loaded in the first sentence, and the Args section maps cleanly to the schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex creation tool with no annotations, the description covers note type semantics, staging workflow, content fidelity, tagging, duplicate avoidance, linking, and parameter formats. An agent has enough context to invoke it correctly without needing return-value details, especially since an output schema exists.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description is the only source of parameter meaning. It defines title, content, note_type, tags, and references with formats, examples, defaults, and type-specific constraints, fully compensating for the empty schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Create a new atomic Zettelkasten note,' a specific verb, resource, and core constraint. It clearly differentiates itself from siblings like slipbox_create_link and slipbox_update_note by focusing on note creation and atomicity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance: search first with slipbox_search_notes to avoid duplicates, create links immediately after with slipbox_create_link, and use 'fleeting' as a staging type when citations are missing. These are concrete when/when-not and alternative-tool instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_create_structure_from_clusterA
Create a structure note from a detected cluster.
Generates a structure note organizing all notes in the cluster, with bidirectional links to each member note.
Run slipbox_get_cluster_report first to see available clusters and their IDs.
Args: cluster_id: ID from cluster report (e.g. "jackson-mac-low-chance-operations") title: Override the suggested title (optional) create_links: Create bidirectional links to member notes (default: true)
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | ||
| cluster_id | Yes | ||
| create_links | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the behavioral burden. It discloses that the tool generates a structure note, organizes all member notes, and creates bidirectional links, and it notes the default create_links behavior in Args. It does not discuss failure modes or side effects on the cluster state, but for a creation operation the core behavior is transparent enough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The purpose is front-loaded, the prerequisite is in a short sentence, and the Args section is scannable. There is minor redundancy between the opening sentence and 'Generates a structure note...', but the added detail about bidirectional links earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the agent does not need the description to explain return values. The description covers the prerequisite, the behavior, and all parameters, which is sufficient for a 3-parameter creation tool with no nested objects. It does not address potential errors like invalid cluster IDs, but that is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must explain all parameters. It does: cluster_id is defined as an ID from the cluster report with a concrete example, title is an optional override of the suggested title, and create_links is explained with its default true. This fully compensates for the empty schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Create a structure note from a detected cluster.' It further clarifies that it organizes all notes in the cluster and creates bidirectional links, which distinguishes it from generic slipbox_create_note and from cluster-management siblings like slipbox_dismiss_cluster.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It gives a concrete prerequisite: 'Run slipbox_get_cluster_report first to see available clusters and their IDs.' This tells an agent when in the workflow to call the tool. It does not explicitly state when not to use it or name alternatives, so it falls short of full routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_delete_linkA
Delete a specific link from one note to another.
Unlike slipbox_remove_link, this tool returns an error if no link exists between the two notes.
Args: source_id: ID of the source note (the note containing the link) target_id: ID of the target note (the note being linked to)
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes | ||
| target_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It clearly conveys deletion and adds a meaningful edge-case behavior: it errors when no link exists. It does not discuss side effects, permissions, or reversibility, but for a targeted link deletion this is reasonably transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded, with the primary action first, the differentiating behavior second, and parameter explanations last. Every sentence earns its place with no filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool, the description covers the action, the key error condition, both parameter roles, and the distinction from the closest sibling. An output schema exists, so return-value details do not need to be spelled out here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description fully compensates by explaining both parameters: source_id is the note containing the link, and target_id is the note being linked to. This adds real meaning beyond the bare schema property names.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Delete a specific link from one note to another.' It also distinguishes itself from the sibling slipbox_remove_link by noting its error behavior, so an agent can tell the two apart without inspecting schemas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly names the sibling slipbox_remove_link and explains the key difference: this tool returns an error if no link exists. This makes the choice between the two tools clear, though it stops short of stating an explicit 'use this when you need...' rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_delete_noteA
Delete a note permanently.
Warning: This also removes all links to and from this note. Consider updating note_type to "fleeting" instead if uncertain.
Args: note_id: The ID of the note to delete
| Name | Required | Description | Default |
|---|---|---|---|
| note_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It warns that the deletion is permanent and that 'This also removes all links to and from this note', which are the critical side effects an agent must know before invoking the tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: the purpose and the destructive warning appear immediately, and the Args section is minimal without unnecessary padding. Every sentence serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive tool with no annotations, the description covers the essential facts: irreversible deletion, link side effects, and a safer alternative. An output schema exists, so return-value documentation is not required, and nothing necessary for correct invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the single parameter. However, it only restates 'The ID of the note to delete', which adds little beyond the parameter name 'note_id'. It omits any guidance on the ID format, where to obtain it, or whether any validation constraints apply.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Delete a note permanently' – a specific verb, resource, and degree of effect. It distinguishes this from slipbox_delete_link and slipbox_update_note, and the context makes the destructive scope unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly advises 'Consider updating note_type to "fleeting" instead if uncertain', naming a concrete alternative for the uncertain case. This gives clear when-to-use and when-not-to-use guidance, with no ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_dismiss_clusterA
Permanently dismiss a cluster from maintenance suggestions.
Use this when a cluster has been reviewed and determined not to need a structure note, or when the user doesn't want to be reminded about it.
Args: cluster_id: The cluster ID to dismiss (e.g. "poetry-craft-revision")
| Name | Required | Description | Default |
|---|---|---|---|
| cluster_id | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing safety and effects. It clearly states the action is 'permanently' applied and scoped to maintenance suggestions, which indicates irreversibility. It could go further by clarifying that no notes are deleted, but the permanence and scope are sufficiently conveyed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and front-loaded: it states the core purpose in the first sentence, gives a short usage rationale, and includes a minimal Args section with an example. No sentence is wasted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one required parameter and an output schema present, so return-value details are unnecessary. The description covers purpose, usage timing, permanence, and parameter example. A small gap is that it does not tell the user how to discover cluster IDs, but that is likely covered by sibling tools like get_cluster_report.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for cluster_id, so the description must compensate. It adds a concrete example ('poetry-craft-revision') and identifies the parameter as a cluster ID, but beyond that it mostly restates the parameter name. For a single simple string parameter, this is adequate but not enriching.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('dismiss') with a clear resource ('cluster') and scope ('from maintenance suggestions'). It clearly distinguishes this from sibling tools like create_structure_from_cluster by positioning it as the 'don't remind me' action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: after a cluster has been reviewed and determined not to need a structure note, or when the user doesn't want reminders. It provides clear context but does not name or exclude specific alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_find_central_notesA
Find the most connected notes in the Zettelkasten.
Central notes have the most incoming and outgoing links, making them key hubs in your knowledge network. Good candidates for hub notes.
Args: limit: Maximum results (default: 10)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It conveys a non-mutating query ('Find') and explains the central-note concept via incoming/outgoing links, but it does not state how results are ordered, how ties are handled, or whether 'limit' truncates a fully computed ranking. These are moderate gaps for a no-annotation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and keeps explanatory text to two useful sentences before the Args block. It is compact and readable, though the Args section mostly duplicates the schema's default value rather than adding new information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-optional-parameter tool with an output schema and no annotations, the description covers the essential purpose, the definition of central notes, and the limit parameter. It does not detail sorting or algorithm internals, but those are unlikely to be required for correct invocation; the main missing piece is explicit sibling-tool routing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has only one parameter with 0% description coverage, and the description adds 'Maximum results (default: 10)', which clarifies that limit means result count and matches the schema default. It provides no guidance on allowed ranges, zero/negative values, or truncation behavior, but the parameter is simple enough that this is only a minor gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Find the most connected notes in the Zettelkasten', a specific verb+resource statement, then defines central notes as hubs with the most incoming and outgoing links. This clearly distinguishes the tool from siblings like find_orphaned_notes or find_similar_notes by focusing on graph centrality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Good candidates for hub notes' implies the intended use case of identifying key knowledge hubs. However, it never explicitly tells an agent when to prefer this tool over the many sibling search/find tools, nor when not to use it, so the guidance is implied rather than fully actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_find_orphaned_notesA
Find notes with no connections to other notes.
Orphaned notes represent unintegrated knowledge. Review these periodically to either link them to existing notes or identify candidates for deletion.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of disclosing behavior. It correctly implies a read-only operation via the verb 'Find' and adds the interpretive context that orphaned notes represent unintegrated knowledge. However, it does not explicitly state side-effect freedom, output behavior, or other operational traits beyond the core result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loads the primary function in the first sentence, and each subsequent sentence adds meaningful context about why orphaned notes matter and what to do with the results. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only discovery tool with an output schema available, the description covers what the tool returns, why it matters, and how to act on the results. Nothing essential for invoking it correctly is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema coverage is 100%, so parameter documentation is unnecessary. Baseline for 0 params is 4; the description adds no parameter details but none are needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Find notes with no connections to other notes.' This clearly distinguishes the tool from siblings like slipbox_find_similar_notes and slipbox_find_central_notes, because it targets a unique criterion: absence of connections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: 'Review these periodically to either link them to existing notes or identify candidates for deletion.' It does not explicitly name alternative tools or state when not to use it, but the periodic-review purpose is useful and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_find_similar_notesA
Find notes similar to a given note.
Similarity is based on shared tags, common links, and content overlap. Useful for discovering connections you might have missed.
Args: note_id: ID of the reference note threshold: Minimum similarity score 0.0-1.0 (default: 0.3) limit: Maximum results (default: 5)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| note_id | Yes | ||
| threshold | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a read-only operation through 'Find', but it does not explicitly state that it does not modify notes or that it is non-destructive. It does explain the similarity basis, which adds useful behavioral context, but it omits details about error behavior (e.g., missing note_id) or any side effects. The read-only nature is implied, not confirmed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured. The primary purpose is front-loaded in the first sentence, followed by a brief explanation of similarity logic and then a clear Args list. No redundant or filler content; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only query tool with an output schema, the description covers the core purpose, similarity logic, and parameters. It does not mention result ordering, behavior on nonexistent note_id, or any limitations, but these are minor given the output schema exists and the tool is straightforward. The description is nearly complete; a small gap is the lack of explicit note that the note must exist or that results are returned in any particular order.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does so thoroughly in the Args section: note_id as 'ID of the reference note', threshold as 'Minimum similarity score 0.0-1.0 (default: 0.3)', and limit as 'Maximum results (default: 5)'. This adds meaning beyond the bare schema, including ranges and defaults, fully enabling correct invocation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Find notes similar to a given note' with a specific verb (Find) and resource (notes similar to a reference). It further distinguishes itself from sibling tools by specifying similarity criteria (shared tags, common links, content overlap), making it distinct from search, central, or orphaned note tools. No ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage hint: 'Useful for discovering connections you might have missed.' This implies when to use it, but it does not explicitly contrast it with alternatives like slipbox_search_notes or slipbox_get_linked_notes. There is no explicit statement of when not to use this tool or what conditions select it over siblings. The guidance is implied but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_get_all_tagsA
Get all tags in the Zettelkasten.
Returns alphabetically sorted list of all tags. Use this to find existing tags before creating new notes to maintain tag consistency across your knowledge base.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the burden of behavioral disclosure. It transparently states the read-only nature through the verb 'Get', discloses the alphabetical sorting behavior, and implies no side effects, which is sufficient for this simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tight and front-loaded: purpose sentence, output behavior sentence, and usage guidance sentence. Every sentence contributes essential information with no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter read-only tool with an output schema, the description is fully sufficient. It explains what is returned, the ordering, and when to use it, leaving no operational ambiguity for an agent deciding to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters)Skip, so there is no parameter semantics to explain. The schema coverage is effectively complete for an empty properties object, and the description adds value by describing the result rather than needing to describe inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb-resource pair ('Get all tags in the Zettelkasten') and defines the output as an alphabetically sorted list. This clearly distinguishes it from sibling tools that operate on notes or links rather than tags.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using this tool before creating new notes to ensure tag consistency, giving a concrete when-to-use scenario. It does not explicitly name alternatives or state when not to use it, but the context is clear for a simple zero-parameter getter.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_get_cluster_reportA
Get pending cluster analysis for structure note creation.
Clusters are groups of notes sharing tags but lacking a structure note. High-scoring clusters are good candidates for new structure notes.
Uses cached analysis by default. Set refresh=true to regenerate. Cluster analysis runs automatically via cron if configured.
Scoring factors:
Note count (7-15 is ideal, >15 is overdue)
Orphan ratio (more orphans = more urgent)
Internal link density (fewer links = needs structure)
Recency (recent activity = active domain)
Args: min_score: Minimum cluster score 0.0-1.0 (default: 0.5) limit: Maximum clusters to return (default: 5) include_notes: Include full note list per cluster (default: false) refresh: Force regeneration of cluster analysis (default: false)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| refresh | No | ||
| min_score | No | ||
| include_notes | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses caching (default) and refresh behavior, automatic cron execution, and the scoring factors that influence results. It does not explicitly state that the operation is read-only (aside from the word 'get'), nor does it mention any auth or rate-limit requirements. Still, the disclosure of caching, refresh side effects, and scoring logic goes well beyond the schema, so a 4 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured: a one-sentence purpose, a brief explanation, a bulleted list of scoring factors, and a clear Args block. It is not bloated, but the scoring factors could arguably be moved to a separate section without harming clarity. It is front-loaded with the core purpose, so it earns a 4.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (which covers return values) and the fact that all four parameters are fully explained in the description, the tool is complete. The description covers purpose, behavior, scoring, and parameter semantics. No critical missing pieces like error handling or timeouts are necessary because the output schema and the tool's simple nature make them non-essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It does: the 'Args' section explains each parameter with meaning and range (min_score 0.0-1.0), behavior (limit max clusters), and implications (include_notes, refresh). This adds significant value beyond the bare schema types and defaults, making it clear how each parameter affects the result.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific statement: 'Get pending cluster analysis for structure note creation.' It then explains what clusters are and how they relate to structure notes, distinguishing this tool from siblings like slipbox_refresh_clusters and slipbox_create_structure_from_cluster. The verb 'get' and the resource 'cluster analysis' are unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides strong contextual guidance: it explains that high-scoring clusters are candidates for structure notes, and mentions the caching behavior and automatic cron runs. However, it does not explicitly compare this tool to siblings like slipbox_refresh_clusters or slipbox_dismiss_cluster, nor does it state when to use an alternative. The guidance is implied rather than explicit, so it earns a 4 rather than a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_get_linked_notesA
Get notes linked to or from a specific note.
Use this to explore the knowledge graph around a note.
Directions:
outgoing: Notes this note links TO
incoming: Notes that link TO this note
both: All connected notes in either direction
Args: note_id: ID of the note to explore from direction: One of outgoing/incoming/both (default: both)
| Name | Required | Description | Default |
|---|---|---|---|
| note_id | Yes | ||
| direction | No | both |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the behavioral disclosure burden. It explains what the tool returns (linked notes), how direction affects the result set, and the default 'both' behavior. The imperative 'Get' implies a read-only operation, and no conflicting destructive behavior is suggested.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose, followed by a usage hint, a compact direction list, and an Args block. Every sentence adds useful information; there is no filler or over-elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema available and only two parameters, the description covers the behavioral purpose, parameter semantics, directions, and default value. The only minor gap is the absence of explicit guidance on when to prefer sibling graph-analysis tools, but this does not block correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so parameter documentation falls entirely on the description. It explains note_id as the starting point and direction with its allowed values and default. It could add more constraints for note_id, but the provided semantics are sufficient for a two-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with a precise verb-resource pair: 'Get notes linked to or from a specific note.' It defines outgoing/incoming/both directions and frames the tool as knowledge-graph exploration, clearly distinguishing it from single-note retrieval or search tools like slipbox_get_note or slipbox_search_notes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
'Use this to explore the knowledge graph around a note' gives a clear context for when to call it, and the direction definitions clarify the kind of traversal intended. It does not explicitly say when not to use it or name a sibling alternative, but the intended use is evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_get_noteA
Retrieve a note by ID or title.
Returns full note content including metadata, tags, and links. Use this to read note contents before creating links or updates.
Args: identifier: Either the note ID (e.g. "20251217T172432480464000") or exact title
| Name | Required | Description | Default |
|---|---|---|---|
| identifier | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It effectively communicates read-only behavior and details what the response contains ('full note content including metadata, tags, and links'), which goes beyond the schema. It does not cover failure modes such as missing identifiers, but this is a minor gap for a simple retrieval tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded, and every line earns its place: purpose, return contents, usage guidance, and parameter meaning. No filler or irrelevant detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read tool with an output schema present, the description covers the essential aspects: what the tool does, how to identify the note, and when to use it. It lacks explicit not-found or error behavior, but that is not critical for normal invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the bare 'identifier' parameter. It does so by explaining that the identifier can be a note ID or exact title and gives a concrete ID format example. Ambiguity handling between the two forms is not addressed, but the compensation is strong for a single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific action ('Retrieve a note') with resource and lookup method ('by ID or title'), and clarifies the result includes full content, metadata, tags, and links. This clearly differentiates it from sibling read tools like search_notes or get_linked_notes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use this tool 'to read note contents before creating links or updates,' which is a clear usage context tied to relevant siblings. It does not mention when NOT to use it or name alternatives, so it stops short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_list_notes_by_dateA
List notes by creation or update date.
Useful for reviewing recent work or finding notes from a specific period.
Args: start_date: Start date in ISO format YYYY-MM-DD (optional) end_date: End date in ISO format YYYY-MM-DD (optional) use_updated: If true, filter by updated_at instead of created_at (default: false) limit: Maximum results (default: 10)
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| end_date | No | ||
| start_date | No | ||
| use_updated | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It explains filtering by created_at or updated_at, optional date bounds, and the default limit. However, it does not disclose result ordering, how date boundaries are handled, or pagination behavior, leaving some uncertainty about exact behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact, front-loaded with the primary action, and organized with a clear Args block. It is slightly redundant with the schema's property definitions, but since the schema lacks descriptions, the explicit parameter documentation is justified and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only listing tool with an output schema, the description covers the essential invocation details and parameter semantics. It does not discuss ordering or edge cases, but the output schema and the simplicity of the operation make the definition sufficiently complete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must fully compensate. It explains every parameter beyond the raw schema: ISO date format for start_date/end_date, the true/false semantics of use_updated, and the default limit. This is exactly the kind of parameter-level guidance an agent needs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'List notes by creation or update date.' This makes the tool's purpose immediately clear and distinguishes it from content-based or similarity-based sibling tools. It also gives practical use cases, reinforcing what the tool is for.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states when the tool is appropriate: 'Useful for reviewing recent work or finding notes from a specific period.' It provides clear context, though it does not explicitly point to alternatives such as slipbox_search_notes for content-based lookup or when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_rebuild_indexA
Rebuild the database index from markdown files.
Use this if notes were edited outside the MCP server or if the database seems out of sync with the filesystem.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states what the tool does (rebuild index) but does not reveal any side effects, such as whether it overwrites the existing index, if it destroys data, if it requires exclusive access, or if it is safe to run concurrently. For a maintenance operation that modifies state, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero wasted words. The action is front-loaded, and the usage context is delivered in the second sentence. It is appropriately concise for a zero-parameter maintenance tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and an output schema present, the description provides the essential trigger conditions. However, it omits behavioral details like whether the operation is destructive, if it locks the database, or if it can be run while other operations are in progress. Given no annotations, the description should disclose more about the operation's impact, so a 3 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so according to the scoring rule the baseline is 4. The description adds no parameter-specific information, but none is needed; the schema already confirms an empty parameter set. The description's clarity about the action suffices.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('rebuild'), resource ('database index'), and source ('from markdown files'), which clearly distinguishes it from sibling tools that handle notes, links, clusters, or searches. There is no other rebuild-oriented sibling, so the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to use the tool: when notes were edited outside the MCP server or the database seems out of sync with the filesystem. It provides clear context for invocation but does not mention alternatives or exclusions, which is acceptable since this is a unique maintenance operation with no direct sibling alternative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_refresh_clustersA
Regenerate cluster analysis and save report.
Analyzes all notes for emergent clusters based on:
Tag co-occurrence (tags that frequently appear together)
Connection patterns (notes that link to each other)
Structure note coverage (which clusters already have structure notes)
Results saved to cluster-analysis.json next to the vault's SQLite index (or SLIPBOX_CLUSTER_REPORT_PATH when set)
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral disclosure burden. It clearly states the tool scans all notes, uses three clustering signals, and writes results to cluster-analysis.json or SLIPBOX_CLUSTER_REPORT_PATH. It does not explicitly say whether the existing report is overwritten or whether the SQLite index must exist, but the 'regenerate' and 'saved to' language covers the primary side effect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The first sentence is a crisp summary, followed by a scannable bulleted list of analysis criteria and a clear statement of the output location. Every sentence adds necessary information with no repetition or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter command with an output schema available, the description provides the essential execution facts: what is analyzed, how clusters are formed, and where the report is written. It would be slightly stronger with an explicit pointer to slipbox_get_cluster_report for reading the saved report, but that gap does not block correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the empty schema is fully self-documenting, so the baseline of 4 applies. The description enhances understanding by explaining what the analysis is based on, even though there are no parameter meanings to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The opening sentence names a specific operation ('Regenerate cluster analysis and save report'), and the bulleted list defines the analysis scope. This distinguishes it from siblings like slipbox_get_cluster_report and slipbox_dismiss_cluster by focusing on regeneration and report writing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this should be used when refreshed cluster analysis is needed, and it states the analysis dimensions. However, it does not explicitly contrast it with slipbox_get_cluster_report for reading existing reports or mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_remove_linkB
Remove a link between two notes.
Args: source_id: ID of the source note target_id: ID of the target note bidirectional: If true, removes links in both directions
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes | ||
| target_id | Yes | ||
| bidirectional | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral disclosure burden. It states the removal operation and the bidirectional option, but does not disclose idempotency, behavior when the link does not exist, side effects, or whether the operation is reversible—important gaps for a destructive action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: one clear purpose sentence followed by a scannable argument list. There is no filler or repetition beyond the necessary parameter explanations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple three-parameter scalar tool with an output schema, the core invocation is understandable. However, the lack of sibling differentiation and the absence of behavioral guidance around a destructive operation make the description incomplete for a fully informed tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds definitions for source_id, target_id, and bidirectional, which is helpful. However, the definitions are minimal and mostly restate the parameter names; they do not specify ID formats, lookup semantics, or additional constraints beyond what the schema already shows.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and resource: 'Remove a link between two notes.' However, it does not differentiate this tool from the sibling slipbox_delete_link, which appears to have an overlapping purpose, so it stops short of full sibling-level clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool instead of slipbox_delete_link or any other alternative. It only explains parameters, leaving the agent to infer the intended context from the tool name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_search_notesA
Search for notes by text, tags, or type.
Searches across titles and content. Combine parameters for precise filtering.
Examples:
Search by topic: query="poetry revision"
Filter by tag: tags="craft,poetry"
Find structure notes: note_type="structure"
Combined: query="metaphor" tags="poetry" limit=5
Args: query: Text to search in titles and content (optional) tags: Comma-separated tags to filter by, e.g. "poetry,craft" (optional) note_type: Filter by type: fleeting/literature/permanent/structure/hub (optional) limit: Maximum results to return (default: 10)
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | ||
| limit | No | ||
| query | No | ||
| note_type | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention any side effects, permissions, ordering, pagination, or behavior when no query is supplied (e.g., returns all notes). It only states the action, not the consequences or edge cases. This is a significant gap for a search tool that could return unexpected results if called with empty parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening sentence, followed by explanatory text and a formatted Args section. It uses examples to illustrate usage without being verbose. It could be slightly more concise in the intro, but the structure is logical and front-loaded with the core purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 optional parameters and no required ones, the description covers each parameter's semantics well. However, it omits edge-case behavior such as what happens with no parameters (does it return all notes?) or how results are ordered. Since an output schema exists, return format is covered, but behavioral edge cases are not. It's adequate for basic usage but leaves some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does this thoroughly: query searches titles and content, tags are comma-separated, note_type lists allowed values (fleeting/literature/permanent/structure/hub), and limit has a default of 10. Examples illustrate parameter combinations. This adds substantial meaning beyond the schema's minimal type/default information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Search for notes by text, tags, or type' and elaborates that it searches across titles and content. This is specific and distinct from sibling tools like slipbox_get_note (retrieves a single note) or slipbox_list_notes_by_date (lists by date). The verb 'search' and resource 'notes' are explicit, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete examples for each parameter combination, demonstrating when to use query, tags, note_type, and limit. It implies usage scenarios clearly. While it doesn't explicitly mention alternatives or when not to use this tool, the sibling tools have distinct purposes, so an agent can infer appropriate usage. It's strong but lacks explicit exclusion guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slipbox_update_noteA
Update an existing note.
Only provided fields are updated; omitted fields remain unchanged. Pass empty string for tags to clear all tags. Pass empty string for references to clear all references.
Constraint: notes with note_type='literature' must have at least one reference. If you are promoting a note to 'literature', pass the citation in references in the same call.
Args: note_id: The ID of the note to update title: New title (optional) content: New content (optional) note_type: New type: fleeting/literature/permanent/structure/hub (optional) tags: New comma-separated tags, or empty string to clear (optional) references: New newline-separated citations, or empty string to clear (optional)
| Name | Required | Description | Default |
|---|---|---|---|
| tags | No | ||
| title | No | ||
| content | No | ||
| note_id | Yes | ||
| note_type | No | ||
| references | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden and does well: it discloses that omitted fields remain unchanged, that empty strings clear tags/references, and that literature notes require at least one reference. It does not cover error behavior for missing note_ids or response details, but the key behavioral traits are surfaced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well organized: behavioral notes come first, followed by a compact Args list. There is minor redundancy between the prose and the Args section regarding empty-string clearing, but no wasted sentences overall.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no schema descriptions, the description covers all six parameters plus the critical literature-reference constraint. An output schema exists, so return-value documentation is not required. It could add behavior for nonexistent notes, but the description is substantially complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the Args section fully compensates by explaining every parameter's meaning, allowed note_type values, comma-separated tags, newline-separated references, and empty-string clearing behavior. This is exactly the kind of parameter-level detail an agent needs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Update' and the resource 'existing note', so it is unambiguous that this tool mutates an existing slipbox note. It does not explicitly differentiate from siblings like slipbox_create_note or slipbox_delete_note, but the verb+resource combination leaves little room for confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description conveys when to use the tool by explaining partial-update semantics and the promotion constraint to literature notes. It does not explicitly say 'use this instead of create/delete' or provide when-not-to-use guidance, but the context is clear enough that an agent can route appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
19 tool updates
v1.5.4- Changed
slipbox_create_link1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_create_linkOutput", + "type": "object" +}
- Changed
slipbox_create_note1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_create_noteOutput", + "type": "object" +}
- Changed
slipbox_create_structure_from_cluster1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_create_structure_from_clusterOutput", + "type": "object" +}
- Changed
slipbox_delete_link1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_delete_linkOutput", + "type": "object" +}
- Changed
slipbox_delete_note1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_delete_noteOutput", + "type": "object" +}
- Changed
slipbox_dismiss_cluster1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_dismiss_clusterOutput", + "type": "object" +}
- Changed
slipbox_find_central_notes1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_find_central_notesOutput", + "type": "object" +}
- Changed
slipbox_find_orphaned_notes1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_find_orphaned_notesOutput", + "type": "object" +}
- Changed
slipbox_find_similar_notes1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_find_similar_notesOutput", + "type": "object" +}
- Changed
slipbox_get_all_tags1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_get_all_tagsOutput", + "type": "object" +}
- Changed
slipbox_get_cluster_report1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_get_cluster_reportOutput", + "type": "object" +}
- Changed
slipbox_get_linked_notes1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_get_linked_notesOutput", + "type": "object" +}
- Changed
slipbox_get_note1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_get_noteOutput", + "type": "object" +}
- Changed
slipbox_list_notes_by_date1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_list_notes_by_dateOutput", + "type": "object" +}
- Changed
slipbox_rebuild_index1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_rebuild_indexOutput", + "type": "object" +}
- Changed
slipbox_refresh_clusters1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_refresh_clustersOutput", + "type": "object" +}
- Changed
slipbox_remove_link1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_remove_linkOutput", + "type": "object" +}
- Changed
slipbox_search_notes1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_search_notesOutput", + "type": "object" +}
- Changed
slipbox_update_note1 field changed- changed
Output schema / (root)Previous value: -nullNew value: +{ + "properties": { + "result": { + "title": "Result", + "type": "string" + } + }, + "required": [ + "result" + ], + "title": "slipbox_update_noteOutput", + "type": "object" +}
19 tool updates
v0.1.0- First observed
slipbox_create_link - First observed
slipbox_create_note - First observed
slipbox_create_structure_from_cluster - First observed
slipbox_delete_link - First observed
slipbox_delete_note - First observed
slipbox_dismiss_cluster - First observed
slipbox_find_central_notes - First observed
slipbox_find_orphaned_notes - First observed
slipbox_find_similar_notes - First observed
slipbox_get_all_tags - First observed
slipbox_get_cluster_report - First observed
slipbox_get_linked_notes - First observed
slipbox_get_note - First observed
slipbox_list_notes_by_date - First observed
slipbox_rebuild_index - First observed
slipbox_refresh_clusters - First observed
slipbox_remove_link - First observed
slipbox_search_notes - First observed
slipbox_update_note
TDQS
Scored across 19 tools
Most tools target a distinct resource/action, but slipbox_delete_link and slipbox_remove_link are near-duplicates that differ only in error behavior, and get_cluster_report with refresh=true overlaps with refresh_clusters. The descriptions clarify the differences, but an agent could still easily select the wrong tool.
Names consistently follow a slipbox_verb_noun pattern with clear domain vocabulary. Minor inconsistencies remain: delete_link vs remove_link use different verbs for the same logical operation, and search_notes sits alongside find_similar_notes, find_central_notes, and find_orphaned_notes.
At 19 tools, this is above the typical well-scoped range, but the extra surface is justified by distinct note CRUD, link management, graph analytics, and cluster maintenance features. It feels slightly heavy rather than bloated.
The server covers note and link lifecycles, search and tag discovery, graph analysis, and cluster-driven structure creation, so core Zettelkasten workflows are supported. Minor gaps exist, such as no dedicated list-all-notes tool and link edits requiring delete/recreate, but agents can work around them.
Maintenance
Related MCP Connectors
Markdown-based note-taking with a hosted MCP server. Your notes serve you and your AI.
Google Keep-style notes app with an MCP server for AI agents to read/write notes.
One memory, every AI. A shared, user-owned markdown memory your AI clients read and write over MCP.
Serve a folder of Markdown notes as an MCP server: hybrid search, reading, and sourced answers.
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