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vector_list_visible_faces

Check which faces Vector currently sees. Returns a list of recognized faces visible to the robot for awareness and interaction.

Instructions

Return the list of faces currently visible to Vector.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.1

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It essentially restates the tool name and does not explain what a returned face looks like, whether an empty list is possible, whether this triggers detection, or whether the operation has side effects. The temporal scope 'currently visible' adds minimal value but not enough for real transparency.

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?

A single, direct sentence that front-loads the action and the resource. There is no filler, repetition, or unnecessary detail, making it efficiently scannable for an agent.

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?

For a zero-parameter query tool, the description is minimally adequate: an agent can invoke it without arguments. However, since there is no output schema, the description should clarify what the returned list contains (e.g., face IDs, names, confidence scores) and whether an empty list is a valid result. This missing return-value context leaves a moderate gap.

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?

The tool has zero parameters and the schema is empty, so the baseline is 4 because there is nothing for the description to clarify. The description correctly implies that no arguments are needed, and no further parameter-level meaning is required.

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 verb ('Return') and resource ('list of faces currently visible to Vector'). It is unambiguous about what the tool does, but it does not explicitly differentiate itself from similar siblings like vector_list_visible_objects or vector_find_faces, so it misses the full sibling-differentiation bar.

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?

There is no stated guidance on when to use this tool versus alternatives. For example, it does not explain when to prefer this over vector_find_faces (which likely actively searches) or vector_face_detection. The phrase 'currently visible' implies a passive snapshot, but no explicit context or exclusions 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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