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ryaker

day-planner-mcp

by ryaker
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TypeScript
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: one handles specific user actions in the Day Planner UI, while the other loads the entire interactive dashboard. There is no overlap or ambiguity between them, as they serve different functions in the user workflow.

    Naming Consistency5/5

    Both tools follow a consistent snake_case naming pattern with clear verb_noun structure: 'handle_day_planner_action' and 'load_day_planner'. The naming is predictable and readable, making it easy for an agent to understand their roles.

    Tool Count2/5

    With only 2 tools, the server feels too thin for its stated purpose of day planning, which involves calendar events, emails, documents, and interactive actions. A more comprehensive set would be expected to cover operations like creating events, managing tasks, or updating priorities, rather than just handling actions and loading a dashboard.

    Completeness2/5

    The tool surface is severely incomplete for day planning. While it covers loading a dashboard and handling some UI actions, it lacks core CRUD operations for managing calendar events, emails, or documents. There are significant gaps that would cause agent failures, such as no ability to create or modify events, send emails, or organize tasks beyond the provided actions.

  • Average 3.9/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

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  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    Annotations already declare readOnlyHint=false and destructiveHint=false, so the agent knows this is a non-destructive mutation tool. The description adds useful context about the UI interaction context and specific action types, but doesn't disclose additional behavioral traits like side effects, authentication needs, rate limits, or what happens after processing each action type.

    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?

    The description is perfectly structured with a clear purpose statement followed by a bulleted list of action types. Every sentence earns its place, there's zero waste, and the information is front-loaded with the most important context first.

    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?

    For a mutation tool with no output schema, the description provides good context about what actions it handles but lacks information about return values, error conditions, or what constitutes successful processing. The annotations cover basic safety but additional behavioral context would be helpful given this is an interactive UI action processor.

    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?

    With 100% schema description coverage, the schema already documents all three parameters thoroughly. The description adds value by explaining what 'actionType' values represent with concrete examples, but doesn't provide additional semantic context for 'payload' or 'currentDataJson' beyond what the schema already states.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool 'processes an interactive action triggered by the user in the Day Planner UI' with specific action types listed. It distinguishes from the sibling tool 'load_day_planner' by focusing on action processing rather than data loading, providing a specific verb+resource+scope combination.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides clear context about when to use this tool ('interactive action triggered by the user in the Day Planner UI') and implicitly references the sibling tool 'load_day_planner' through the 'currentDataJson' parameter. However, it doesn't explicitly state when NOT to use this tool or provide alternative tools for similar actions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the dashboard shows and interactive features, which adds useful context about the tool's behavior. However, it doesn't address important behavioral aspects like whether this is a read-only operation, if it requires specific permissions, or any rate limits. The description doesn't contradict annotations (none exist).

    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?

    The description is appropriately sized and well-structured with clear bullet points listing dashboard components. It's front-loaded with the core purpose. Some minor verbosity exists in the bullet descriptions, but overall it's efficient and each sentence adds value.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's moderate complexity (interactive dashboard with multiple data sources), no annotations, and no output schema, the description does a reasonably complete job. It explains what the tool does, what the dashboard contains, and how to use it. However, it could be more complete by addressing the lack of output schema (what exactly gets returned) and providing more behavioral context.

    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?

    Schema description coverage is 100%, so the schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose5/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Opens an interactive day planning dashboard showing your calendar, emails, and docs.' It uses specific verbs ('Opens', 'showing') and resources ('dashboard', 'calendar', 'emails', 'docs'), and distinguishes from the sibling tool 'handle_day_planner_action' by focusing on loading/displaying rather than handling actions.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides clear context for when to use this tool: 'Use this to give the user a holistic view of their day.' It implies usage for day planning but doesn't explicitly state when NOT to use it or mention alternatives beyond the sibling tool, which is only referenced implicitly through differentiation.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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