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pylon_search_users

Find team members and support agents by name, email, or department to assign issues or check availability in Pylon's customer support platform.

Instructions

Search for team members and support agents in Pylon. Use this to find colleagues by name, email, or department when assigning issues or checking availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch term to find users by name, email, or department. Examples: "john", "support@company.com", "technical team"
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. It mentions searching by name, email, or department, but lacks details on behavioral traits such as permissions needed, rate limits, pagination, or what the search returns (e.g., partial matches, case sensitivity). 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 concise and front-loaded, with two sentences that efficiently convey purpose and usage. Every sentence adds value without redundancy, making it easy to scan and understand quickly.

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?

Given the tool's moderate complexity (search function with one parameter), no annotations, and no output schema, the description is adequate but incomplete. It covers the basic purpose and usage but lacks details on behavioral aspects and output format, which are important for effective tool invocation.

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?

The schema description coverage is 100%, with the 'query' parameter well-documented in the schema. The description adds minimal value by restating searchable fields (name, email, department) without providing additional semantics like search logic or examples beyond the schema. 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.

Purpose5/5

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

The description clearly states the specific action ('Search for team members and support agents in Pylon') and distinguishes it from siblings like 'pylon_get_users' by specifying search functionality. It identifies the resource ('team members and support agents') and the context ('Pylon'), making the purpose explicit and differentiated.

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 context for when to use this tool ('when assigning issues or checking availability'), which helps guide usage. However, it does not explicitly state when not to use it or name alternatives (e.g., 'pylon_get_users' for listing all users without search), missing full differentiation.

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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