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body_search_guide

Find entries in Norton Guide files containing a search text anywhere in the body; returns the complete entry content.

Instructions

Search all entries in a Norton Guide for a query string anywhere in the body.

This is similar to line_search_guide but returns the entire entry content for any entry that contains a match, rather than just the matching lines.

The search is also done on the whole body, with lines joined using a space.

Args: path: Absolute path to the .ng file. query: The text string to search for. case_sensitive: When True, the search is case-sensitive. Defaults to False.

Returns: A list of match dictionaries. Each dictionary contains:

- ``offset`` (int): Byte offset of the matching entry.
- ``type`` (str): ``"short"`` or ``"long"``.
- ``lines`` (list[str]): Plain-text lines of the entry.

Raises: FileNotFoundError: If path does not point to an existing file.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
queryYes
case_sensitiveNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses search behavior (case sensitivity, joining lines with a space), return structure (offset, type, lines as list of strings), and raised exception (FileNotFoundError). It also mentions the tool returns entire entry content, which is a behavioral trait. No contradictory or missing critical information for a read-only search tool.

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 well-structured with clear sections (Args, Returns, Raises) and uses bold formatting for emphasis. It is concise without unnecessary words, though the comparison to line_search_guide could be slightly more condensed. Overall, it earns its place.

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

Completeness5/5

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

Given the tool's moderate complexity, the description is complete: it explains the search scope, return format, and error conditions. An output schema exists that details the return structure, so the description doesn't need to elaborate further. It covers all relevant aspects for an AI agent to correctly invoke the tool.

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

Parameters4/5

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

Input schema coverage is 0% (no descriptions in schema). The description compensates by explaining each parameter: path as 'Absolute path to the .ng file', query as 'The text string to search for', and case_sensitive with its default value and behavior. This adds significant meaning beyond the schema's property names and types.

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's purpose: searching all entries in a Norton Guide for a query string anywhere in the body. It explicitly distinguishes itself from the sibling tool line_search_guide by contrasting the return type (entire entry vs. matching lines) and search scope (whole body vs. lines). The verb 'search' and resource 'entries in a Norton Guide' are specific.

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

Usage Guidelines4/5

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

The description provides clear guidance on when to use this tool vs. line_search_guide: 'This is similar to line_search_guide but returns the entire entry content... rather than just the matching lines.' It implies that if you need only matching lines, use line_search_guide. However, it does not explicitly mention when not to use this tool or provide alternatives for other siblings.

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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