Search the full corpus for a word or phrase and get the matching lines with their chapter numbers. Use this when the user half-remembers a line and you need to find where it is.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses the scope ('full corpus') and the return format ('matching lines with their chapter numbers'), which adds useful context. However, it does not state whether the operation is read-only, explain limit behavior, or mention any potential variations such as case sensitivity or sorting. The basics are covered, but deeper behavioral traits are missing.
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 only two sentences, with the action and result front-loaded in the first sentence and usage guidance in the second. Every sentence serves a purpose, with no unnecessary repetition or filler.
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?
The tool is relatively simple with two parameters and no output schema. The description covers the core purpose and usage, but omits parameter semantics for 'limit' and does not mention any constraints on the search (e.g., minimum query length is in schema but not described). It is adequate for a basic search tool but not fully complete given the absence of annotations and output schema.
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?
The schema descriptions cover 0% of parameters, so the description must compensate. It does explain that 'query' is a word/phrase to search for, which aligns with the schema, but it completely omits any explanation of the 'limit' parameter and its effect on results. This is a significant gap for a two-parameter tool.
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 uses the specific verb 'Search' with the resource 'full corpus', and clearly states the output (matching lines with chapter numbers). It distinguishes the tool from sibling tools such as get_chapter and list_chapters by emphasizing corpus-wide search rather than retrieving a specific chapter or listing chapters.
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?
Provides a clear usage scenario: 'when the user half-remembers a line and you need to find where it is.' This tells the agent when to use it, though it does not explicitly mention alternatives or when-not-to-use conditions. The context is clear enough for most cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose: consult matches situations to chapters, get_chapter retrieves by number, list_chapters provides an overview, and search_chapters finds text. The description explicitly contrasts consult with search, eliminating ambiguity.
Three tools follow a verb_noun pattern (get_chapter, list_chapters, search_chapters), while 'consult' is a bare verb without an object. All names are lowercase with underscores, so the inconsistency is minor and readability is high.
Four tools is a well-scoped count for a niche server: it covers consultation, retrieval, listing, and searching without redundancy or unnecessary bloat. This falls squarely within the ideal 3-15 range.
The tool surface covers the full domain lifecycle: orient (list), retrieve (get), find by text (search), and get situational guidance (consult). No obvious gaps exist for a textual study server.