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reading-companion

reading-companion

by aby0
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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add_book_connection

Add links between books by specifying relationship type, reason, and strength to build personalized reading recommendations.

Instructions

Add a connection between two books for future recommendations.

Args: from_book: Title of the first book to_book: Title of the second book relationship: Type of connection: - "similar_theme": Similar themes or topics - "complements": Different angles on same topic - "next_step": Natural progression from first to second - "contrast": Interesting contrast/counterpoint reason: Why these books are connected strength: "strong" | "moderate" | "weak"

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "from_book": "<from_book>",
      "to_book": "<to_book>",
      "relationship": "<relationship>",
      "reason": "<reason>"
    },
    "name": "add_book_connection"
  }
}

Input Schema

NameRequiredDescriptionDefault
from_bookYes
to_bookYes
relationshipYes
reasonYes
strengthNomoderate

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must convey behavioral traits. It states the tool adds a connection but does not disclose side effects (e.g., is it idempotent? does it overwrite existing connections?), permissions required, or error conditions. The behavior is straightforward, but additional transparency would be helpful.

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 concise: a one-sentence purpose followed by a clear, structured list of arguments with explanations. Every sentence adds value, and the front-loaded purpose helps the agent quickly understand the tool's function.

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?

The tool has no output schema, and the description does not mention what the tool returns (e.g., confirmation, connection ID). It also lacks details on side effects, such as whether connections are unique or can be duplicated. For a tool with 5 parameters and no output schema, this omission reduces completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, but the description provides detailed semantics for all parameters. It explains from_book and to_book as titles, relationship with four enumerated values and their meanings, reason, and strength with three allowed values. This adds significant meaning beyond the schema's bare type declarations.

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 adds a connection between two books for future recommendations. The verb 'add' and resource 'connection between two books' are specific. This distinguishes it from sibling tools like add_book_to_stack (which adds a book to a stack) and get_similar_books (which retrieves existing recommendations).

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

Usage Guidelines3/5

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

The purpose is clear, but the description does not explicitly state when to use this tool versus alternatives (e.g., when to add a connection vs. using get_similar_books). No when-not or alternative guidance is provided, relying on the user to infer context from the purpose.

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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