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mjyoo2
by mjyoo2

search_text

Find specific text within an HWP document and get the number of matches. Accepts document ID, search query, and case sensitivity option.

Instructions

Search for text in the document.

Args: doc_id: Document ID from open_document query: Text to search for case_sensitive: Whether the search is case sensitive

Returns: Number of matches found

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
doc_idYes
case_sensitiveNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the return count and does not mention whether the operation is read-only, whether it alters the cursor/selection, what query syntax is accepted, or whether doc_id must reference a currently open document.

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 compact and front-loaded, with a single purpose sentence followed by a clean Args/Returns block. There is no filler, though a bit more practical guidance would improve it.

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?

The basic input and output shape is covered, and an output schema is present. However, given the crowded sibling set and absence of annotations, the lack of usage context and behavioral detail leaves noticeable gaps for an agent selecting and invoking the tool.

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

Parameters2/5

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

Schema description coverage is 0%, so the description needed to compensate. It adds marginal value by noting doc_id comes from open_document and query is the text to search, but the parameter descriptions mostly restate the parameter names and omit meaningful details like case_sensitive's default behavior being true.

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

Purpose4/5

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

The description clearly states the operation: 'Search for text in the document' and specifies the return value as 'Number of matches found'. It is easy to tell what the tool does, though it does not explicitly differentiate itself from sibling tools such as replace_text, get_document_text, or select_text.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With many text-related siblings like search/select/replace, the absence of any 'use this instead when...' context leaves selection to inference. No exclusions or alternative tool references are provided.

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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