Quarterback
Quarterback
フィールドを読み、プレイをコールせよ。
複数プロジェクトを抱えるオペレーター向けの戦略的タスク優先順位付けおよびエージェントオーケストレーションツール。
他のAIタスクマネージャーは、1つのプロジェクトをサブタスクに分解するだけです。Quarterbackは、5要素の加重スコアリングエンジン、組織のコンテキスト、および時間認識型プランニングを使用して、10個のプロジェクトのうちどれを今優先すべきかを決定する手助けをします。ローカルで動作し、無料で利用でき、スタンドアロンのCLIとしても、Claude用のMCPサーバーとしても機能します。
Quarterbackが他と異なる点
機能 | Quarterback | TaskMaster AI | Shrimp Task Manager |
複数プロジェクトの優先順位付け | 5要素加重エンジン | 単一プロジェクト分解 | 単一プロジェクト |
アドバイザリー文書システム | 目標に対する記事の分析 | なし | なし |
エージェントオーケストレーション | 自律レベル + Webhook | なし | なし |
時間認識型プランニング | 勤務時間、昼食、バッファ時間 | なし | なし |
組織のコンテキスト | 目標、制約、ワークフロー | なし | なし |
ナレッジWiki (Playbook) | セッション間の一貫性を保つLLM管理Wiki | なし | なし |
競合検出 | プロジェクト間のスケジュール競合 | なし | なし |
スタンドアロンCLI | AIランタイムなしのフルCLI | AIが必要 | AIが必要 |
コスト | 無料 (MIT) | 無料 | 無料 |
Related MCP server: Kanban MCP
クイックスタート
# Install
pip install quarterback
# Initialize (creates ~/.quarterback/)
quarterback init
# Interactive setup wizard — walks you through org, goals, workflows, projects, constraints
quarterback setup
# Add your first project and tasks
quarterback add "Launch landing page" --project "My Startup" --priority 4 --effort 3 --impact 5
quarterback add "Write blog post" --project "Content" --priority 3 --effort 2 --impact 3
# See what to work on
quarterback priorities
# Find quick wins
quarterback quick-wins
# Plan your day with time awareness
quarterback plan-dayLLMによるセットアップ (MCP経由)
QuarterbackをMCPサーバーとして使用する場合、LLMに「Quarterbackをセットアップして」と伝えてください。setup_quarterbackツールが呼び出され、ビジネス、目標、ワークフロー、プロジェクト、制約、ナレッジベース(Playbook)について対話形式でヒアリングを行い、すべての設定ファイルとデータベースレコードを一括で作成します。手動でのYAML編集は不要です。
MCPサーバー
Quarterbackは、Claude Desktop、Claude Code、Cursor、Windsurf、Cline、OpenAIエージェントなど、MCP互換のあらゆるクライアントで動作します。23個のツールすべてが標準のMCPプロトコル(stdio経由のJSON-RPC)を使用しており、LLM固有の依存関係はありません。
# Install with MCP support
pip install quarterback[mcp]Claude Desktopの設定(~/Library/Application Support/Claude/claude_desktop_config.json)に追加します:
{
"mcpServers": {
"quarterback": {
"command": "quarterback-server"
}
}
}またはClaude Code(~/.claude/settings.json)の場合:
{
"mcpServers": {
"quarterback": {
"command": "quarterback-server"
}
}
}同じquarterback-serverコマンドがどのMCPクライアントでも動作します。クライアントのサーバー設定に追加するだけです。
その後、LLMに「今日取り組むべきことは?」と尋ねれば、23個のQuarterbackツールすべてを使用して優先順位を分析します。
機能
5要素優先順位付けエンジン
すべてのタスクは5つの次元でスコアリングされます:
要素 | 重み | 測定内容 |
インパクト | 30% | タスクの影響度 + プロジェクトの収益/戦略的価値 |
緊急度 | 25% | 期日の近さ + ブロッキング状態 |
戦略的 | 25% | プロジェクトの優先度 + マイルストーン状態 |
労力 | 15% | 反転労力スコア(短いタスクほど高スコア) |
クイックウィン | 5% | 高インパクト + 低労力ボーナス |
アドバイザリー文書システム
外部の記事、書籍、アドバイスを組織のコンテキストと照らし合わせて分析します:
# Import and auto-analyze an article
quarterback advisory-add --title "Growth Strategy" --url https://example.com/article
# Review the analysis
quarterback advisory-view --id 1
# Approve recommendations (optionally create tasks)
quarterback advisory-approve --id 1 --approve 1,3,5 --create-tasksアナライザーはすべての推奨事項を目標や制約と照らし合わせ、競合や相乗効果をフラグ立てします。
エージェントオーケストレーション
設定可能な自律レベルで、自律エージェント実行用のタスクをマークします:
ドラフト: エージェントがレビュー用のドラフトを作成
チェックポイント: エージェントが重要な決定ポイントで承認のために一時停止
自律: エージェントが完了まで実行
タスクの準備が整うと、Webhookが自動化レイヤー(n8n、Zapier、カスタム)に通知します。
Playbook — ナレッジWiki
PlaybookはQuarterbackのコンパイル済みナレッジレイヤーです。これはLLMが管理するMarkdown Wikiであり、ローカルCLI、MCP、自律エージェントなど、すべてのセッションにプロジェクト、決定事項、戦略に関する同一の標準コンテキストを提供します。
解決する問題: Playbookがない場合、AIセッションは毎回ゼロから開始され、断片的なシグナルから組織のコンテキストを再導出します。同じクエリを実行しても、セッションごとに理解を個別に再構築するため、異なる結果が生じることがあります。Playbookは、すべてのセッションが読み取る蓄積された知識を提供します。
仕組み:
~/playbook/ (or ~/.quarterback/playbook/)
├── CLAUDE.md # Schema — how the LLM reads/writes pages
├── raw/ # Drop zone for source material
└── wiki/
├── index.md # Master catalog — read this first
├── entities/ # Companies, products, clients, tools
├── concepts/ # Patterns, strategies, recurring themes
├── decisions/ # Decisions with rationale and alternatives
├── compiled/ # QB-compatible files for task scoring
│ ├── goals.md # Read by QB's prioritization engine
│ └── constraints.md # Read by QB's conflict detection
└── log.md # Append-only operations recordセットアップ: Playbookはquarterback setup(またはMCPセットアップウィザード)中に自動的に作成されます。インタビューで主要なエンティティ、概念、決定事項について尋ねられ、初期のWikiページが生成されます。
Playbookなしの場合: Quarterbackはこれまで通り、~/.quarterback/org-context/ファイルから目標と制約を読み取ります。Playbookはオプトインです。
Playbookありの場合: QuarterbackはまずPlaybookからcompiled/goals.mdとcompiled/constraints.mdを読み取り、Playbookが初期化されていない場合はorg-context/ファイルにフォールバックします。LLMは組織のコンテキスト全体を把握するためにwiki/index.mdを読み取ります。
# Check Playbook status
quarterback playbook status
# Browse the index
quarterback playbook index
# List pages by category
quarterback playbook list --category entities
# Read a specific page
quarterback playbook read entities/my-product.md
# Search across all pages
quarterback playbook search "budget"Obsidian統合(オプション): セットアップ中に、PlaybookをObsidianボルトとして設定することを選択できます。ObsidianでPlaybookフォルダを開くと、グラフの可視化や視覚的な編集が可能です。プログラムによるアクセスのためにObsidian MCPサーバーをインストールしてください。Obsidianへの依存は必須ではありません。PlaybookはプレーンなMarkdownファイルとして機能します。
CI/CDパイプライン統合
QuarterbackのCLIとWebhookシステムは、自動化されたパイプラインに最適です。タスクステータスの更新、成果物のログ記録、ダウンストリーム作業のトリガーを人間を介さずに行えます。
パイプラインでの直接CLI
CI/CDの任意のステップにQuarterbackコマンドを追加します。CLIはステートレスでスクリプト可能です:
# GitHub Actions example: auto-update task on deploy
- name: Mark deploy task complete
run: |
pip install quarterback
export QUARTERBACK_HOME=${{ runner.temp }}/.quarterback
quarterback update 42 --status completed --notes "Deployed via CI, SHA: ${{ github.sha }}"# After test suite passes, log results to a task
- name: Report test results
run: |
quarterback update 38 --notes "Tests passed: 106/106, coverage 87%. Build #${{ github.run_number }}"# Nightly: check for overdue deliverables and alert
- name: Nightly priority check
run: |
quarterback alert-check
quarterback priorities today --limit 5Webhookによるエージェント型CI/CD
Webhookを登録し、自動化レイヤーがタスクイベントにリアルタイムで反応するようにします:
# Register a webhook pointing at your n8n/Zapier/custom endpoint
quarterback-server # MCP tools available, or use CLI:# In your automation script: mark a task agent-ready after PR merge
import subprocess
subprocess.run([
"quarterback", "update", "55",
"--status", "completed",
"--notes", f"PR #{pr_number} merged. Deployed to staging."
])ユースケース:
パイプラインイベント | Quarterbackアクション | 発生すること |
PRマージ |
| タスク完了、SlackへWebhook通知 |
デプロイ成功 |
| 監査証跡付きで成果物を追跡 |
夜間Cron |
| チームに期限切れタスクのデイリーサマリーを送信 |
テスト失敗 |
| バグを自動起票し、プロジェクトにリンク |
スプリント開始 |
| 作業開始前にスケジュールの競合を表面化 |
エージェント作業完了 |
| Webhookがオーケストレーターに通知、次のタスクをディスパッチ |
リリースにタグ付け |
| プロジェクト目標と照らし合わせて変更ログを分析 |
環境間でのデータベース共有
複数の環境を同じQuarterbackインスタンスに向けることができます:
# All CI runners share one database via mounted volume or network path
export QUARTERBACK_HOME=/shared/quarterback
# Or per-environment with migration
quarterback migrate /path/to/sourceこれにより、ローカルCLI、CIパイプライン、MCP接続エージェントのすべてが同じタスクグラフを読み書きでき、手動および自動ワークフロー全体で単一の信頼できる情報源(Single Source of Truth)が得られます。
時間認識型プランニング
quarterback plan-day勤務時間、昼食休憩、会議のバッファ時間、現在時刻を考慮し、残りの時間内に実際に収まるタスクを提案します。
設定
組織のコンテキスト
quarterback initの後、quarterback setupを実行して対話型ウィザードを使用するか、MCP経由でClaudeにセットアップウィザードを実行させてください。~/.quarterback/org-context/で手動でコンテキストを設定することも可能です:
~/.quarterback/org-context/
├── goals.md # Your strategic, workflow, and project goals
├── projects.yaml # Active projects with metadata
├── workflows.yaml # Groups of related projects
└── constraints.md # Time, budget, and strategic boundariesサンプルテンプレートが含まれています。.exampleファイルからコピーしてカスタマイズしてください。
セットアップ中にPlaybookを有効にすると、goals.mdとconstraints.mdはWikiのcompiled/ディレクトリから自動的に維持されます。引き続きorg-contextファイルを手動で編集することも可能です。Playbookは追加機能であり、必須ではありません。
アラート設定
~/.quarterback/config/alerts.yamlで通知を設定します:
静かな時間帯(夜間の通知なし)
優先度しきい値(P4以上のタスクのみ通知)
時間に敏感なプロジェクト(請求書、税金などは常に通知)
勤務時間と昼食休憩の設定
CLIコマンド
コマンド | 説明 | ||
| Quarterbackの初期化 | ||
| 対話型セットアップウィザード | ||
| task-managerからの移行 | ||
`quarterback priorities [today | week | all]` | 優先順位付きタスクリスト |
| タスクの追加 | ||
| タスクの更新 | ||
| タスク一覧 | ||
| クイックウィンを見つける | ||
| 優先順位の競合を検出 | ||
| プロジェクト一覧 | ||
| 組織のサマリー | ||
| 時間認識型デイリープラン | ||
| アドバイザリー文書の追加 | ||
| アドバイザリー文書一覧 | ||
| 文書詳細の表示 | ||
| 文書の分析 | ||
| 推奨事項の承認/拒否 | ||
| アラートの確認 | ||
| デイリーサマリーの送信 | ||
| Playbook初期化ステータス | ||
| Playbookマスターカタログの表示 | ||
| Wikiページ一覧( | ||
| Wikiページの読み取り | ||
| ページ全体の全文検索 |
MCPツール(合計27個)
MCPサーバーとして使用する場合、QuarterbackはClaudeに以下のツールを公開します:
タスク管理: get_priorities, add_task, update_task, get_quick_wins, detect_conflicts, assess_task_value, get_blocking_tasks
プロジェクト管理: add_project, list_projects, update_project, get_organizational_summary
アドバイザリーシステム: add_advisory_document, list_advisory_documents, get_advisory_document, analyze_advisory_document, discuss_advisory_recommendations, adopt_advisory_recommendations
Playbook: playbook_read, playbook_write, playbook_search, playbook_ingest
Webhook: register_webhook, list_webhooks, update_webhook, delete_webhook
エージェントオーケストレーション: mark_task_agent_ready, get_agent_ready_tasks, update_agent_status
セットアップ: setup_quarterback
環境変数
変数 | デフォルト | 説明 |
|
| データディレクトリ |
|
| Playbook Wikiの場所(または |
| なし | Pro機能用に予約 |
貢献
開発セットアップ、コードスタイル、PRプロセスについてはCONTRIBUTING.mdを参照してください。
ライセンス
MIT - LICENSEを参照
Built by NodeBridge Automation Solutions | GitHub Sponsors
Available Tools
24 toolsadd_advisory_documentC
Add a new advisory document for review and analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| content | Yes | ||
| source | No | ||
| source_type | No | ||
| project_name | No | ||
| workflow_name | No | ||
| tags | No | ||
| priority | No | ||
| auto_analyze | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions documents are for 'review and analysis' but omits critical behavioral details like auto_analyze default behavior, workflow triggers, or side effects.
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?
Brief and front-loaded, but undersized for 9-parameter complexity; single sentence fails to justify its existence given schema gaps.
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?
Incomplete given rich sibling ecosystem (analyze, discuss, adopt); misses opportunity to explain advisory workflow integration and document lifecycle.
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?
Adds zero parameter context despite 0% schema description coverage; critical parameters like workflow_name, source_type, and auto_analyze lack semantic explanation.
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 basic action (add advisory document) and purpose (review/analysis) but fails to distinguish from sibling analysis tools or define 'advisory document' concept.
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?
No guidance on when to use vs. siblings like analyze_advisory_document, or workflow sequence (add before analyze?).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_projectD
Add a new project.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| path | No | ||
| workflow_name | No | ||
| description | No | ||
| priority | No | ||
| status | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, description carries full burden but reveals nothing about side effects, idempotency, or what happens upon success/failure.
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?
Brief and front-loaded, but the single sentence fails to earn its place by adding any informational value beyond the tool name.
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?
Insufficient for a tool with 6 parameters including enums and constraints; misses opportunity to explain required vs optional fields or return behavior.
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 has 0% description coverage and description fails to compensate, providing no context for path, workflow_name, priority scale (1-5), or status enum values.
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?
Tautology that restates the tool name ('Add a new project' = add_project) without distinguishing from siblings like update_project or add_task.
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?
No guidance on when to use this tool versus alternatives (e.g., add_project vs update_project) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_taskC
Add a new task with full metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| description | Yes | ||
| project_name | No | ||
| priority | No | ||
| effort | No | Estimated hours | |
| impact | No | ||
| due_date | No | ||
| notes | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose side effects, idempotency, or what 'full metadata' actually encompasses.
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?
While brief at six words, it is insufficiently informative for a tool with seven diverse parameters and no output schema; brevity here creates ambiguity rather than clarity.
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 rich input schema with dates, scales, and effort estimates, the description is inadequate—it doesn't hint at required fields, validation rules, or the relationship between parameters.
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?
Mentions 'full metadata' which loosely corresponds to the seven parameters, but with only 14% schema coverage, it fails to clarify priority versus impact or due_date formatting requirements.
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 the basic action (add task) but 'full metadata' is vague and fails to distinguish from sibling tools like add_project or add_advisory_document.
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?
Provides no guidance on when to use this versus update_task or other task management tools, nor when adding is inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
adopt_advisory_recommendationsC
Approve or reject recommendations, optionally creating tasks.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes | ||
| approved_recommendation_ids | No | ||
| rejected_recommendation_ids | No | ||
| create_tasks | No | ||
| adoption_notes | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions optional task creation but lacks critical details: no annotation contradictions, but missing info on state changes, failures, or auth requirements given no annotations provided.
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?
Single sentence is appropriately terse but arguably too minimal for 5-parameter complexity; no structural issues.
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?
Insufficient for the tool's complexity; omits advisory document workflow context, return behavior, and relationship between document_id and recommendation_ids.
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?
With 0% schema description coverage, the description fails to explain document_id, adoption_notes, or the mutual exclusivity logic between approved/rejected arrays; only implicitly maps to create_tasks.
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?
Clearly states the core action (approve/reject) and side effect (task creation), though 'advisory' context from the tool name is omitted.
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?
Provides no guidance on when to use versus siblings like discuss_advisory_recommendations or workflow prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
analyze_advisory_documentC
Analyze an advisory document against organizational context.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks disclosure of side effects, return format, or whether analysis results are persisted; 'analyze' implies read-only but this is 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?
Single sentence is brief but not information-dense; front-loading is moot due to lack of actionable 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?
Absence of output schema requires description to specify return values (structured analysis? narrative? recommendations?), but it provides no indication of output.
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?
Fails to compensate for 0% schema description coverage; does not explain document_id semantics, valid ranges, or how to obtain valid IDs.
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 basic function (analyze document against context) but is vague on analysis specifics and fails to differentiate from siblings like get_advisory_document or discuss_advisory_recommendations.
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?
Provides no guidance on when to use this versus retrieving, listing, or adopting recommendations from advisory documents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
assess_task_valueC
Assess whether a proposed task aligns with organizational goals.
| Name | Required | Description | Default |
|---|---|---|---|
| task_description | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks critical behavioral details given no annotations: does not specify output format (score, boolean, text?), side effects, or if the assessment is persisted.
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?
Single sentence is appropriately terse and front-loaded, though extreme brevity leaves functional gaps.
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?
Critical omission: no output schema exists, yet description fails to explain what the assessment returns (rating, analysis, recommendation).
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?
Mentions 'proposed task' which loosely maps to the task_description parameter, but fails to compensate for 0% schema coverage by specifying expected content, format, or length.
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?
Clearly states the tool evaluates task alignment with organizational goals, distinguishing it from sibling CRUD operations like add_task or update_task.
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?
Provides no guidance on when to use this assessment versus directly adding tasks or using get_priorities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_webhookC
Delete a registered webhook.
| Name | Required | Description | Default |
|---|---|---|---|
| webhook_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fails to disclose that deletion is permanent, irreversible, or whether pending deliveries are affected.
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?
Extremely terse (4 words) which is concise but undersized for a destructive operation; lacks structural elements like warnings or parameter hints.
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?
Adequate for a single-parameter tool but missing critical context: parameter semantics, error cases (e.g., non-existent ID), and permanence warnings expected for delete operations.
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 has 0% description coverage; description compensates poorly by not mentioning webhook_id, how to obtain it, or that it refers to the ID from list_webhooks.
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?
Clear verb (Delete) + resource (registered webhook) distinguishes from siblings (register/update/list) via the action word, though 'registered' adds minimal qualification.
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?
Provides no guidance on when to use versus alternatives (e.g., update_webhook for modifications) or warnings about permanent deletion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_conflictsC
Detect conflicting priorities and resource constraints.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the 5-word description fails to disclose scope, side effects, return format, or data sources analyzed.
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?
Extremely brief and front-loaded, but overly terse to the point of omitting necessary operational context.
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?
Lacks output schema and description fails to compensate by explaining return values, scope (project vs organization-wide), or conflict detection criteria.
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?
Zero parameters present; meets baseline expectation with no additional parameter context needed or provided.
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 the basic action (detect) and targets (priorities/resource constraints) but lacks specificity about conflict types and doesn't differentiate from sibling tools like get_blocking_tasks or assess_task_value.
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?
Provides no guidance on when to invoke this tool versus alternatives or what conditions warrant its use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
discuss_advisory_recommendationsD
Facilitate discussion about advisory recommendations.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes | ||
| recommendation_ids | No | ||
| user_feedback | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose any behavioral traits, side effects, or what 'facilitating discussion' actually entails (e.g., notifications, storage, threading).
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?
Extremely brief (6 words) and front-loaded, but the brevity results from emptiness rather than efficient information density.
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?
Incomplete given the lack of output schema and parameter descriptions; fails to explain return values or the advisory workflow context.
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 has 0% description coverage, yet the description adds no meaning for document_id, recommendation_ids, or user_feedback parameters.
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?
Tautologically restates the tool name ('discuss' → 'facilitate discussion') without specifying mechanism or distinguishing from siblings like adopt_advisory_recommendations.
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?
Provides no guidance on when to use this versus adopting, analyzing, or retrieving advisory documents.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_advisory_documentC
Get full details of a specific advisory document.
| Name | Required | Description | Default |
|---|---|---|---|
| document_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description discloses only basic retrieval action without read-only confirmation, error conditions, or side effects.
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?
Extremely brief (7 words) with no fluff, though arguably too terse to be fully informative.
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?
Minimal but sufficient for a single-parameter retrieval tool, though parameter context 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 has 0% description coverage and description fails to compensate by explaining document_id semantics or format.
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 basic function ('get full details') but fails to differentiate from siblings like analyze_advisory_document or list_advisory_documents.
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?
No guidance on when to use versus alternatives (list vs analyze vs discuss) or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_agent_ready_tasksC
Get tasks queued for agent execution.
| Name | Required | Description | Default |
|---|---|---|---|
| agent_type | No | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description provides minimal behavioral disclosure beyond identifying it as a getter; omits ordering, pagination behavior, and empty state handling.
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?
Extremely terse (5 words) and front-loaded, but insufficient given the lack of schema descriptions and output schema; brevity creates information gaps.
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?
Missing return value specification (no output schema exists) and fails to explain parameter semantics or relationship to mark_task_agent_ready workflow.
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?
Fails to compensate for 0% schema description coverage; omits that agent_type filters by capability domain and limit controls result count.
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?
Clear verb+resource pairing that defines 'agent_ready' as 'queued for agent execution', distinguishing from sibling getters like get_blocking_tasks.
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?
No guidance on when to use this versus get_priorities, get_blocking_tasks, or get_quick_wins; no workflow context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_blocking_tasksC
Get tasks that are blocking other work.
| Name | Required | Description | Default |
|---|---|---|---|
| project_name | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, yet description fails to explain what constitutes 'blocking' or expected result volume.
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?
Single sentence is appropriately concise and front-loaded, though minimal content leaves gaps.
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?
Incomplete for the schema richness level; fails to compensate for undocumented parameter and lacks output expectations.
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 has 0% description coverage and description text doesn't mention project_name parameter at all.
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?
Clear specific verb and resource ('Get tasks that are blocking'), distinguishes from sibling tools like get_agent_ready_tasks and get_quick_wins.
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?
No guidance on when to use vs alternatives (detect_conflicts, get_priorities) or when to specify project_name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_organizational_summaryC
Get comprehensive organizational state summary.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Implies read-only operation via 'Get' but provides no details on performance, scope, or whether it aggregates data from all sibling domains.
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?
Single sentence is appropriately concise but lacks necessary detail for a broad retrieval 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?
Without an output schema, fails to describe what the summary contains or its structure, leaving return values undefined.
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?
No parameters exist; baseline score applies.
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 it retrieves a summary but 'organizational state' remains vague and doesn't specify what data is included (projects, tasks, advisories).
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?
Provides no guidance on when to use this versus specific retrieval tools like get_priorities or get_quick_wins.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_prioritiesC
Get prioritized list of tasks based on organizational context.
| Name | Required | Description | Default |
|---|---|---|---|
| timeframe | No | today | |
| project_name | No | ||
| status | No | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist to contradict, but description adds minimal behavioral context beyond 'Get'—omitting how prioritization is calculated, side effects, or return format.
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?
Single sentence avoids bloat, but extreme brevity leaves critical gaps; not structured to front-load key distinctions from siblings.
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?
Insufficient for the tool's complexity (4 parameters, 2 enums) and crowded sibling namespace; lacks output guidance or prioritization logic explanation.
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 has 0% description coverage and description fails to compensate, mentioning none of the four parameters (timeframe, project_name, status, limit) or their interactions.
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?
Restates tool name tautologically ('get_priorities' → 'Get prioritized list') and fails to distinguish from siblings like get_quick_wins, get_blocking_tasks, or get_agent_ready_tasks.
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?
Provides no guidance on when to use this versus sibling task-querying tools or what constitutes 'organizational context'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_quick_winsC
Identify quick win tasks (high impact, low effort).
| Name | Required | Description | Default |
|---|---|---|---|
| project_name | No | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the selection criteria (high impact, low effort) but omits output format, side effects, or whether results are ranked; no annotations provided to supplement this.
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?
Extremely concise single sentence with no fluff, though arguably too brief for the tool's contextual complexity given numerous siblings.
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?
Insufficient for the task management domain complexity; missing output schema description, differentiation from 5+ sibling retrieval tools, and parameter details.
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?
Adds no parameter context despite 0% schema description coverage; fails to clarify that project_name scopes the search or that limit defaults to 5.
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?
Clearly defines 'quick wins' as high impact, low effort tasks, but doesn't clarify if it filters existing tasks or generates suggestions, nor how it differs from siblings like assess_task_value or get_priorities.
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?
Provides no guidance on when to use this versus alternatives like get_priorities or get_agent_ready_tasks, nor when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_advisory_documentsC
List advisory documents with filtering.
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | all | |
| project_name | No | ||
| workflow_name | No | ||
| source_type | No | ||
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, yet description omits behavioral details like pagination, sorting order, or result limits.
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?
Brief and front-loaded, but content is too thin to earn its place; appropriately sized yet uninformative.
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 5 undocumented parameters and no output schema, description lacks necessary context about advisory document lifecycle and filter meanings.
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 has 0% description coverage; description mentions 'filtering' but fails to explain semantics of specific parameters like source_type or workflow_name.
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?
Restates tool name with minimal addition ('with filtering'); fails to distinguish from sibling 'get_advisory_document' (singular vs plural retrieval).
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?
Provides no guidance on when to use filtering vs retrieving a specific document via get_advisory_document.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_projectsD
List all projects.
| Name | Required | Description | Default |
|---|---|---|---|
| status | No | active |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, description fails to disclose default behavior (returns only 'active' projects), pagination limits, or return value structure.
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?
While brief (3 words), it is inappropriately sized for a tool with parameters and many siblings; the single sentence adds no value beyond the tool name.
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 lack of output schema and presence of filtering logic, description fails to explain what constitutes a 'project' or what data is returned.
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 has 0% description coverage and description completely omits the 'status' parameter, its enum values, and the 'active' default, leaving agents unaware of filtering capabilities.
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?
Tautology that restates the tool name ('List all projects') without distinguishing from siblings like add_project or list_advisory_documents.
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?
No guidance on when to use versus alternatives like get_organizational_summary, or when to filter by specific statuses versus 'all'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_webhooksB
List all registered webhooks.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description minimally discloses behavior by specifying 'all' webhooks are returned (matching empty input schema), but lacks details on rate limits, pagination, or return structure.
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?
Extremely concise at 4 words; appropriate length for a parameterless tool with no extraneous content.
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?
Lacks description of return values (no output schema exists to compensate), leaving gap in understanding what webhook data is returned.
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?
Input schema has 0 parameters; baseline score applies.
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?
Specific verb (List) and resource (registered webhooks) clearly stated; implicitly distinguishes from sibling tools register_webhook, update_webhook, and delete_webhook through the 'List' 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?
No guidance provided on when to use this tool versus alternatives or specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mark_task_agent_readyC
Mark a task for autonomous agent execution.
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes | ||
| agent_config | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description fails to disclose if this triggers immediate execution, queues the task, or sets a flag.
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?
Extremely brief (6 words) and front-loaded, though excessive brevity harms completeness.
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 nested agent_config object with 5+ sub-properties and no output schema, description lacks necessary detail for correct configuration.
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 has 0% description coverage with complex enums (autonomy_level, agent_type); description adds zero parameter context.
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?
Clear verb (Mark) and resource (task for autonomous execution) but doesn't differentiate from update_task sibling.
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?
No guidance on when to use vs update_task or prerequisites for marking ready.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
register_webhookC
Register a webhook endpoint to receive task events.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| url | Yes | ||
| events | Yes | ||
| secret | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose return values, idempotency behavior, or what happens if a webhook with the same URL exists.
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?
Extremely concise and front-loaded, though arguably too brief given the information gaps; the single sentence efficiently conveys the core action.
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?
Insufficient for the medium complexity (4 params, enum values, no output schema); omits critical context like webhook authentication mechanisms and event filtering options.
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?
Given 0% schema description coverage, the description inadequately compensates by leaving name, secret, and the wildcard '*' event unexplained.
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?
Clearly states the action (register) and resource (webhook endpoint) with a specific purpose (receive task events), though it omits that project events are also supported.
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?
Provides no guidance on when to use this versus update_webhook, or prerequisites like checking existing webhooks via list_webhooks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_agent_statusC
Update agent execution status of a task.
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes | ||
| agent_status | Yes | ||
| agent_output | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, description fails to disclose side effects, idempotency, state transition rules, or what triggers when status changes (e.g., notifications).
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?
Extremely concise at 6 words with no fluff, though arguably too minimal given the complexity of the state machine implied by the enum.
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 a state machine (5 enum values) and sibling workflow tools, description inadequately explains the lifecycle or transition constraints (e.g., can you go from completed back to processing?).
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 has 0% description coverage, yet the description adds no explanation for agent_output (optional string) or the semantic meaning of status enum values (checkpoint, queued implications).
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 the basic action (update status) and target (task), but 'agent execution status' is vague and doesn't differentiate from sibling update_task or clarify the agent workflow.
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?
Provides no guidance on when to use this versus update_task or mark_task_agent_ready, nor when to use specific status enum values (queued vs processing vs completed).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_projectD
Update a project's properties.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| status | No | ||
| priority | No | ||
| description | No | ||
| context | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose critical behavioral traits such as whether this performs partial updates (PATCH) or full replacements (PUT), or what happens to unspecified fields.
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?
While brief at only four words, it is inappropriately sized—too short to be useful—and the single sentence fails to earn its place by adding no actionable 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 an update operation with five parameters including status enums and priority scales, the description lacks essential context about required fields, update semantics, and success behavior.
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?
Given 0% schema description coverage, the description fails to compensate by explaining parameter semantics (e.g., whether 'name' is an identifier, what 'context' means, or the significance of priority levels 1-5).
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 'Update a project's properties' is a tautology that merely restates the tool name without distinguishing it from sibling tools like update_task or update_webhook.
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?
Provides no guidance on when to use this versus add_project, update_task, or other alternatives, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_taskD
Update an existing task.
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes | ||
| status | No | ||
| priority | No | ||
| effort | No | ||
| impact | No | ||
| notes | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose critical behavioral traits like partial vs full update semantics, side effects, or field preservation rules.
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?
While appropriately brief and front-loaded, the single sentence fails to earn its place by providing minimal information beyond the tool name itself.
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 6 parameters with no schema descriptions and no annotations, the description is insufficiently complete to support 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 has 0% description coverage yet the description adds no meaning for parameters like impact/effort scales, notes purpose, or status enum implications.
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?
Tautological description 'Update an existing task' merely restates the tool name without distinguishing from sibling tools like add_task or mark_task_agent_ready.
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?
Provides no guidance on when to use this versus alternatives (e.g., mark_task_agent_ready for status changes) or when-not-to-use conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
update_webhookD
Update a webhook configuration.
| Name | Required | Description | Default |
|---|---|---|---|
| webhook_id | Yes | ||
| name | No | ||
| url | No | ||
| events | No | ||
| secret | No | ||
| active | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose critical behavioral traits such as PATCH vs PUT semantics, idempotency, or error handling for invalid webhook_ids.
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?
While appropriately brief at four words, the single sentence fails to earn its place by adding no informational value beyond the tool name itself.
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 six parameters, zero schema descriptions, and no output schema, the description is grossly incomplete—missing critical context about partial updates, required permissions, and return values.
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?
Given 0% schema description coverage, the description completely fails to compensate by explaining parameter semantics like the 'secret' authentication mechanism, 'events' format, or 'active' state transitions.
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 'Update a webhook configuration' is a tautology that restates the tool name without distinguishing from sibling register_webhook or clarifying the update 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?
No guidance provided on when to use update_webhook versus register_webhook, or whether unspecified parameters retain existing values versus being reset.
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.
24 tool updates
v0.1.0- First observed
add_advisory_document - First observed
add_project - First observed
add_task - First observed
adopt_advisory_recommendations - First observed
analyze_advisory_document - First observed
assess_task_value - First observed
delete_webhook - First observed
detect_conflicts - First observed
discuss_advisory_recommendations - First observed
get_advisory_document - First observed
get_agent_ready_tasks - First observed
get_blocking_tasks - First observed
get_organizational_summary - First observed
get_priorities - First observed
get_quick_wins - First observed
list_advisory_documents - First observed
list_projects - First observed
list_webhooks - First observed
mark_task_agent_ready - First observed
register_webhook - First observed
update_agent_status - First observed
update_project - First observed
update_task - First observed
update_webhook
TDQS
Scored across 24 tools
Tools are well-differentiated across distinct domains: advisory document workflows (analyze/discuss/adopt), task intelligence (assess/value vs. priorities vs. quick wins), and agent orchestration (mark ready vs. update status). While several tools operate on tasks, their purposes—assessment, prioritization, blocking detection, and agent handoff—are clearly distinct.
Follows verb_noun convention consistently (add_task, analyze_advisory_document, detect_conflicts). Minor deviations exist: register_webhook breaks the add_* pattern used for other resources, and mark_task_agent_ready uses 'mark' instead of 'update' compared to update_agent_status, but these are readable exceptions rather than chaos.
With 24 tools, this pushes into the 'heavy' category (16-25 range) for a single server. While the domain (project orchestration + advisory workflows + agent execution + webhooks) justifies complexity, the surface area is large enough that agents may struggle to navigate the full set without careful prompting.
Strong coverage of advisory document lifecycles and agent orchestration, but notable gaps in basic CRUD: missing get_project and get_task (forcing reliance on list operations with filtering), and no delete operations for projects, tasks, or advisory documents. Webhooks also lack individual retrieval.
Maintenance
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