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natural_language_search

Search ServiceNow data using plain English queries to find information without technical knowledge of the platform's structure.

Instructions

Search ServiceNow using plain English (experimental)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesPlain English query
limitNoMax results (default: 10)
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it's 'experimental', which hints at potential instability. It doesn't disclose behavioral traits like whether it's read-only, how results are returned, error handling, rate limits, or authentication needs. This leaves significant gaps for a 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.

Conciseness5/5

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

The description is a single, efficient sentence with zero waste. It's front-loaded with key information (action, target, method) and includes a useful qualifier ('experimental'). Every word earns its place.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., result format, types of records), behavioral constraints, or error conditions. For a search tool with two parameters, this leaves too much unspecified.

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

Parameters3/5

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

Schema description coverage is 100%, with parameters 'query' and 'limit' well-documented in the schema. The description adds no additional parameter semantics beyond implying 'query' accepts natural language. Baseline 3 is appropriate as the schema does the heavy lifting.

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 action ('Search') and target ('ServiceNow'), and specifies the method ('using plain English'). It distinguishes from other search tools like 'ai_search' or 'query_records' by emphasizing natural language input. However, it doesn't explicitly contrast with all sibling tools, keeping it at 4 instead of 5.

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

Usage Guidelines3/5

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

The description implies usage context through 'using plain English' and marks it as 'experimental', suggesting it's for users preferring conversational queries. However, it lacks explicit guidance on when to choose this over alternatives like 'ai_search' or 'search_catalog', and doesn't mention prerequisites or exclusions.

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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