nmlp_identify_first_edition

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

No annotations are provided, so the description carries full burden. It explains what the tool returns (points of issue, precedence, tells, publisher, year, page URL, citation) and cites the dataset with licensing (CC BY 4.0, DOI). It does not mention side effects, rate limits, or failure handling, but as a read-only query tool, the disclosure is sufficient for typical use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single focused paragraph. It front-loads the purpose, lists key outputs, emphasizes the tool's role, and cites the data source. Every sentence earns its place with no redundancy or fluff.

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

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

Given no output schema, the description sufficiently explains return fields and data provenance. It covers the two parameters with practical guidance. The tool is straightforward, and the description addresses all necessary context for an AI agent to invoke it correctly.

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

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

Schema coverage is 100%, so both parameters are described. The description adds useful context beyond the schema: for 'title' it notes 'series/subtitle suffixes are fine', and for 'author' it states 'strongly improves match accuracy for common titles'. This helps the agent understand when to provide the optional parameter.

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

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

The description clearly states the tool's purpose: 'Identify whether a specific book is a first edition.' It uses a specific verb ('identify') and resource ('first edition'), and distinguishes itself from siblings by claiming to be 'THE tool' for that question, which sets it apart from related tools like nmlp_decode_number_line.

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

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

The description indicates when to use: given a title and optionally author. It emphasizes it's the primary tool for first-edition identification. However, it lacks explicit when-not-to-use guidance or references to alternative tools (e.g., when to use nmlp_check_coverage or nmlp_decode_number_line), leaving some ambiguity for edge cases.

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