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Glama

Quarterback

Lies das Feld. Sag den Spielzug an.

Strategische Aufgabenpriorisierung und Agenten-Orchestrierung für Multi-Projekt-Betreiber.

PyPI Python License: MIT CI bobbyrgoldsmith/quarterback MCP server


Jeder andere KI-Aufgabenmanager unterteilt ein Projekt in Teilaufgaben. Quarterback hilft dir zu entscheiden, welches deiner zehn Projekte du gerade priorisieren solltest — unter Verwendung einer gewichteten 5-Faktoren-Bewertungs-Engine, organisatorischem Kontext und zeitbewusster Planung. Es läuft lokal, kostet nichts und funktioniert sowohl als eigenständige CLI als auch als MCP-Server für Claude.

Was Quarterback anders macht

Funktion

Quarterback

TaskMaster AI

Shrimp Task Manager

Multi-Projekt-Priorisierung

Gewichtete 5-Faktoren-Engine

Einzelprojekt-Unterteilung

Einzelprojekt

Beratungsdokumenten-System

Analysiert Artikel anhand deiner Ziele

Nein

Nein

Agenten-Orchestrierung

Autonomie-Level + Webhooks

Nein

Nein

Zeitbewusste Planung

Arbeitszeiten, Mittagspause, Pufferzeit

Nein

Nein

Organisatorischer Kontext

Ziele, Einschränkungen, Workflows

Nein

Nein

Wissens-Wiki (Playbook)

LLM-gepflegtes Wiki für Konsistenz über Sitzungen hinweg

Nein

Nein

Konflikterkennung

Projektübergreifende Terminüberschneidungen

Nein

Nein

Eigenständige CLI

Vollständige CLI ohne KI-Laufzeit

Erfordert KI

Erfordert KI

Kosten

Kostenlos (MIT)

Kostenlos

Kostenlos

Related MCP server: Kanban MCP

Schnellstart

# 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-day

LLM-gestützte Einrichtung (via MCP)

Wenn du Quarterback als MCP-Server verwendest, frage dein LLM: "Richte Quarterback für mich ein" — es ruft das Tool setup_quarterback auf, führt ein Gespräch mit dir über dein Unternehmen, deine Ziele, Workflows, Projekte, Einschränkungen und deine Wissensdatenbank (Playbook) und schreibt dann alle Konfigurationsdateien und Datenbankeinträge in einem Rutsch. Kein manuelles YAML-Editieren erforderlich.

MCP-Server

Quarterback funktioniert mit jedem MCP-kompatiblen Client — Claude Desktop, Claude Code, Cursor, Windsurf, Cline, OpenAI-Agenten und anderen. Alle 23 Tools verwenden das Standard-MCP-Protokoll (JSON-RPC über stdio) ohne LLM-spezifische Abhängigkeiten.

# Install with MCP support
pip install quarterback[mcp]

Füge dies zu deiner Claude Desktop-Konfiguration hinzu (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "quarterback": {
      "command": "quarterback-server"
    }
  }
}

Oder für Claude Code (~/.claude/settings.json):

{
  "mcpServers": {
    "quarterback": {
      "command": "quarterback-server"
    }
  }
}

Der gleiche quarterback-server-Befehl funktioniert mit jedem MCP-Client — füge ihn einfach zur Serverkonfiguration deines Clients hinzu.

Frage dann dein LLM: "Woran sollte ich heute arbeiten?" — es wird alle 23 Quarterback-Tools verwenden, um deine Prioritäten zu analysieren.

Funktionen

5-Faktoren-Priorisierungs-Engine

Jede Aufgabe wird anhand von fünf Dimensionen bewertet:

Faktor

Gewichtung

Was es misst

Auswirkung

30%

Aufgaben-Auswirkung + Projektumsatz/strategischer Wert

Dringlichkeit

25%

Nähe des Fälligkeitsdatums + Blockierungsstatus

Strategisch

25%

Projektpriorität + Meilenstein-Status

Aufwand

15%

Invertierter Aufwandswert (schnelle Aufgaben werden höher bewertet)

Quick Win

5%

Hohe Auswirkung + geringer Aufwand Bonus

Beratungsdokumenten-System

Analysiere externe Artikel, Bücher und Ratschläge anhand deines organisatorischen Kontexts:

# 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

Der Analysator prüft jede Empfehlung gegen deine Ziele und Einschränkungen und markiert Konflikte sowie Synergien.

Agenten-Orchestrierung

Markiere Aufgaben für die autonome Agentenausführung mit konfigurierbarer Autonomie:

  • Entwurf: Der Agent erstellt einen Entwurf zur Überprüfung durch dich

  • Prüfpunkt: Der Agent pausiert bei wichtigen Entscheidungen zur Genehmigung

  • Autonom: Der Agent führt die Aufgabe bis zum Abschluss aus

Webhooks benachrichtigen deine Automatisierungsebene (n8n, Zapier, benutzerdefiniert), wenn Aufgaben bereit sind.

Playbook — Wissens-Wiki

Playbook ist die kompilierte Wissensebene von Quarterback. Es ist ein LLM-gepflegtes Markdown-Wiki, das jeder Sitzung — lokale CLI, MCP oder autonomer Agent — denselben kanonischen Kontext über deine Projekte, Entscheidungen und Strategien gibt.

Das Problem, das es löst: Ohne Playbook beginnt jede KI-Sitzung von vorne und leitet deinen organisatorischen Kontext aus spärlichen Signalen neu ab. Zwei Sitzungen, die dieselbe Abfrage ausführen, können unterschiedliche Ergebnisse liefern, da sie das Verständnis unabhängig voneinander rekonstruieren. Playbook bietet akkumuliertes Wissen, aus dem alle Sitzungen lesen.

Wie es funktioniert:

~/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

Einrichtung: Playbook wird automatisch während quarterback setup (oder dem MCP-Einrichtungsassistenten) erstellt. Das Interview fragt nach deinen wichtigsten Entitäten, Konzepten und Entscheidungen und erstellt dann erste Wiki-Seiten.

Ohne Playbook: Quarterback funktioniert genau wie zuvor — es liest Ziele und Einschränkungen aus ~/.quarterback/org-context/-Dateien. Playbook ist optional.

Mit Playbook: Quarterback liest zuerst compiled/goals.md und compiled/constraints.md aus dem Playbook und greift auf org-context/-Dateien zurück, falls Playbook nicht initialisiert ist. Dein LLM liest wiki/index.md für den vollständigen organisatorischen Kontext.

# 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-Integration (optional): Während der Einrichtung kannst du wählen, Playbook als Obsidian-Vault zu konfigurieren. Öffne den Playbook-Ordner in Obsidian für Graph-Visualisierung und visuelle Bearbeitung. Installiere einen Obsidian MCP-Server für den programmatischen Zugriff. Keine Obsidian-Abhängigkeit erforderlich — Playbook funktioniert als einfache Markdown-Dateien.

CI/CD-Pipeline-Integration

Die CLI und das Webhook-System von Quarterback machen es zu einer natürlichen Ergänzung für automatisierte Pipelines — aktualisiere den Aufgabenstatus, protokolliere Ergebnisse und löse nachgelagerte Arbeit aus, ohne dass ein Mensch eingreifen muss.

Direkte CLI in Pipelines

Füge Quarterback-Befehle zu jedem CI/CD-Schritt hinzu. Die CLI ist zustandslos und skriptbar:

# 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 5

Agentische CI/CD mit Webhooks

Registriere einen Webhook und lass deine Automatisierungsebene in Echtzeit auf Aufgabenereignisse reagieren:

# 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."
])

Anwendungsfälle:

Pipeline-Ereignis

Quarterback-Aktion

Was passiert

PR zusammengeführt

update_task status=completed

Aufgabe als erledigt markiert, Webhook an Slack gesendet

Bereitstellung erfolgreich

update_task mit SHA + Umgebungsnotizen

Ergebnis mit Audit-Trail nachverfolgt

Nächtlicher Cron

get_priorities + alert-check

Team erhält tägliche Zusammenfassung überfälliger Aufgaben

Test-Suite schlägt fehl

add_task mit Fehlerdetails

Fehler automatisch gemeldet, mit Projekt verknüpft

Sprint beginnt

get_priorities + detect_conflicts

Terminüberschneidungen aufdecken, bevor die Arbeit beginnt

Agent schließt Arbeit ab

update_agent_status status=completed

Webhook benachrichtigt Orchestrator, nächste Aufgabe zugewiesen

Release getaggt

advisory-add mit Release-Notizen

Changelog anhand von Projektzielen analysiert

Gemeinsame Datenbank über Umgebungen hinweg

Verweise mehrere Umgebungen auf dieselbe Quarterback-Instanz:

# 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

Dies ermöglicht es deiner lokalen CLI, CI-Pipelines und MCP-verbundenen Agenten, alle denselben Aufgabengraphen zu lesen und zu schreiben — was dir eine einzige Quelle der Wahrheit über manuelle und automatisierte Workflows hinweg gibt.

Zeitbewusste Planung

quarterback plan-day

Berücksichtigt deine Arbeitszeiten, Mittagspause, Pufferzeit für Meetings und die aktuelle Uhrzeit, um Aufgaben vorzuschlagen, die tatsächlich in deinen verbleibenden Tag passen.

Konfiguration

Organisatorischer Kontext

Führe nach quarterback init den Befehl quarterback setup für einen interaktiven Assistenten aus oder bitte Claude, den Einrichtungsassistenten via MCP auszuführen. Du kannst deinen Kontext auch manuell in ~/.quarterback/org-context/ konfigurieren:

~/.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

Beispielvorlagen sind enthalten — kopiere sie aus den .example-Dateien und passe sie an.

Wenn du Playbook während der Einrichtung aktivierst, werden goals.md und constraints.md automatisch aus dem compiled/-Verzeichnis des Wikis gepflegt. Du kannst die org-context-Dateien weiterhin manuell bearbeiten — Playbook ist additiv, nicht erforderlich.

Alarmkonfiguration

Konfiguriere Benachrichtigungen in ~/.quarterback/config/alerts.yaml:

  • Ruhezeiten (keine Benachrichtigungen nachts)

  • Prioritätsschwellenwerte (nur für P4+-Aufgaben benachrichtigen)

  • Zeitkritische Projekte (immer für Rechnungen, Steuern usw. benachrichtigen)

  • Einstellungen für Arbeitszeiten und Mittagspause

CLI-Befehle

Befehl

Beschreibung

quarterback init

Initialisiert Quarterback

quarterback setup

Interaktiver Einrichtungsassistent

quarterback migrate <dir>

Migration von task-manager

`quarterback priorities [today

week

all]`

Priorisierte Aufgabenliste

quarterback add "task" [options]

Aufgabe hinzufügen

quarterback update <id> [options]

Aufgabe aktualisieren

quarterback list [-s status]

Aufgaben auflisten

quarterback quick-wins

Quick Wins finden

quarterback conflicts

Prioritätskonflikte erkennen

quarterback projects

Projekte auflisten

quarterback summary

Organisatorische Zusammenfassung

quarterback plan-day

Zeitbewusster Tagesplan

quarterback advisory-add

Beratungsdokument hinzufügen

quarterback advisory-list

Beratungsdokumente auflisten

quarterback advisory-view --id N

Dokumentdetails anzeigen

quarterback advisory-analyze --id N

Dokument analysieren

quarterback advisory-approve --id N

Empfehlungen genehmigen/ablehnen

quarterback alert-check

Auf Alarme prüfen

quarterback alert-summary

Tägliche Zusammenfassung senden

quarterback playbook status

Playbook-Initialisierungsstatus

quarterback playbook index

Playbook-Masterkatalog anzeigen

quarterback playbook list

Wiki-Seiten auflisten (mit --category-Filter)

quarterback playbook read <path>

Wiki-Seite lesen

quarterback playbook search <query>

Volltextsuche über Seiten hinweg

MCP-Tools (insgesamt 27)

Wenn Quarterback als MCP-Server verwendet wird, stellt es Claude diese Tools zur Verfügung:

Aufgabenverwaltung: get_priorities, add_task, update_task, get_quick_wins, detect_conflicts, assess_task_value, get_blocking_tasks

Projektmanagement: add_project, list_projects, update_project, get_organizational_summary

Beratungssystem: 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

Webhooks: register_webhook, list_webhooks, update_webhook, delete_webhook

Agenten-Orchestrierung: mark_task_agent_ready, get_agent_ready_tasks, update_agent_status

Einrichtung: setup_quarterback

Umgebungsvariablen

Variable

Standard

Beschreibung

QUARTERBACK_HOME

~/.quarterback

Datenverzeichnis

PLAYBOOK_PATH

~/.quarterback/playbook

Speicherort des Playbook-Wikis (oder in config/playbook.yaml festlegen)

QUARTERBACK_API_URL

Keine

Reserviert für Pro-Funktionen

Mitwirken

Siehe CONTRIBUTING.md für die Entwicklungseinrichtung, den Code-Stil und den PR-Prozess.

Lizenz

MIT - siehe LICENSE


Erstellt von NodeBridge Automation Solutions | GitHub Sponsors

Available Tools

24 tools
add_advisory_documentC

Add a new advisory document for review and analysis.

ParametersJSON Schema
NameRequiredDescriptionDefault
titleYes
contentYes
sourceNo
source_typeNo
project_nameNo
workflow_nameNo
tagsNo
priorityNo
auto_analyzeNo

TDQS

C2.2/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYes
pathNo
workflow_nameNo
descriptionNo
priorityNo
statusNo

TDQS

D1.8/5.0
Behavior1/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
descriptionYes
project_nameNo
priorityNo
effortNoEstimated hours
impactNo
due_dateNo
notesNo

TDQS

C2.5/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters3/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
document_idYes
approved_recommendation_idsNo
rejected_recommendation_idsNo
create_tasksNo
adoption_notesNo

TDQS

C2.6/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
document_idYes

TDQS

C2.4/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
task_descriptionYes

TDQS

C2.9/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters3/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
webhook_idYes

TDQS

C2.7/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness3/5

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.

Parameters2/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

C2.7/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters4/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
document_idYes
recommendation_idsNo
user_feedbackNo

TDQS

D1.8/5.0
Behavior1/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
document_idYes

TDQS

C2.6/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness3/5

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.

Parameters2/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
agent_typeNo
limitNo

TDQS

C2.4/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
project_nameNo

TDQS

C2.6/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

C2.8/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters4/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
timeframeNotoday
project_nameNo
statusNo
limitNo

TDQS

C2.1/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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).

ParametersJSON Schema
NameRequiredDescriptionDefault
project_nameNo
limitNo

TDQS

C2.9/5.0
Behavior3/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
statusNoall
project_nameNo
workflow_nameNo
source_typeNo
limitNo

TDQS

C2.1/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
statusNoactive

TDQS

D1.9/5.0
Behavior2/5

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.

Conciseness2/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

B3.4/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness3/5

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.

Parameters4/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
task_idYes
agent_configYes

TDQS

C2.6/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYes
urlYes
eventsYes
secretNo

TDQS

C2.7/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose4/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
task_idYes
agent_statusYes
agent_outputNo

TDQS

C2.4/5.0
Behavior2/5

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.

Conciseness4/5

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.

Completeness2/5

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.

Parameters2/5

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.

Purpose3/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
nameYes
statusNo
priorityNo
descriptionNo
contextNo

TDQS

D1.7/5.0
Behavior1/5

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.

Conciseness2/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
task_idYes
statusNo
priorityNo
effortNo
impactNo
notesNo

TDQS

D1.8/5.0
Behavior1/5

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.

Conciseness3/5

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.

Completeness2/5

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.

Parameters1/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
webhook_idYes
nameNo
urlNo
eventsNo
secretNo
activeNo

TDQS

D1.9/5.0
Behavior2/5

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.

Conciseness3/5

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.

Completeness1/5

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.

Parameters1/5

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.

Purpose2/5

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.

Usage Guidelines2/5

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.

  1. 24 tool updatesv0.1.0
    • First observedadd_advisory_document
    • First observedadd_project
    • First observedadd_task
    • First observedadopt_advisory_recommendations
    • First observedanalyze_advisory_document
    • First observedassess_task_value
    • First observeddelete_webhook
    • First observeddetect_conflicts
    • First observeddiscuss_advisory_recommendations
    • First observedget_advisory_document
    • First observedget_agent_ready_tasks
    • First observedget_blocking_tasks
    • First observedget_organizational_summary
    • First observedget_priorities
    • First observedget_quick_wins
    • First observedlist_advisory_documents
    • First observedlist_projects
    • First observedlist_webhooks
    • First observedmark_task_agent_ready
    • First observedregister_webhook
    • First observedupdate_agent_status
    • First observedupdate_project
    • First observedupdate_task
    • First observedupdate_webhook

TDQS

C2.5/5.0

Scored across 24 tools

Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count3/5

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.

Completeness3/5

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

ActivityStale
ResponsivenessNo issues

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