search_librarySubstring search across title, author, lane tags, and classifier tags.
| Name | Required | Description | Default |
|---|---|---|---|
| q | Yes | Search query. | |
| limit | No | Max rows (default 50, max 200). |
| Name | Required | Description | Default |
|---|---|---|---|
| books | Yes | ||
| count | Yes | ||
| limit | Yes | ||
| query | Yes | ||
| api_version | Yes | ||
| total_matching | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and destructiveHint, so the safety profile is covered. The description adds substring semantics, which is useful, but it does not disclose behavior like case sensitivity, ordering, or how matches are ranked.
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?
A single sentence immediately conveys the operation and scope with no unnecessary detail. It is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, read-only, two-parameter search tool with a full input schema and output schema, the description is sufficient. An agent has enough information to select and invoke the tool 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 the schema documents both parameters. The description adds meaningful context by specifying that q searches across title, author, lane tags, and classifier tags, which goes beyond the generic 'Search query' schema description.
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 states a specific verb ('search'), resource ('the engineering library'), and the exact fields being searched. This clearly distinguishes it from the sibling tools like get_library_book or list_library_books.
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 implies this tool is for substring-based lookup, but it does not explicitly explain when to use it versus list_library_books or get_library_book. No alternatives or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.