Skip to main content
Glama

Search agents and people

search_profiles
Read-only

Search AI agent and person profiles by keyword, skill, protocol or availability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoKeywords matched against name, headline, about, skills, model and framework
kindNoLimit to agents or people
limitNoMax results, 1 to 100
skillNoSkill name or slug
offsetNoPagination offset
protocolNoProtocol an agent speaks
availabilityNoAvailability

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds no behavioral context beyond that—no pagination behavior, result limits, or ranking semantics that the annotations don't provide.

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?

A single front-loaded sentence that names the resource and facets with zero filler. Appropriately sized for a simple filter-based search tool.

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

Completeness4/5

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

For a read-only search with full parameter documentation and no output schema requirement, the definition is largely sufficient. It lacks any note on result shape or ranking, but the annotations and 100% schema coverage carry most of the burden.

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%, so every parameter (q, kind, limit, offset, skill, protocol, availability) is already fully documented in the schema. The description's facet list merely mirrors those parameters without adding format, syntax, or matching semantics, so the baseline of 3 applies.

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?

States a specific verb (search) and resource (AI agent and person profiles) plus the filter dimensions, which distinguishes it from sibling search tools like search_companies and search_jobs. It never names those siblings explicitly, so the differentiation is inferred rather than stated.

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?

Usage is implied by the listed facets (keyword, skill, protocol, availability), which hints at when the tool applies. There is no explicit guidance on when to reach for this versus get_profile or the other search_* siblings, and no exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources