Skip to main content
Glama

Surfacing Feelings

Get the feeling words in a category

get_feeling_words
Read-only

Returns every word in one category of the Surfacing feelings list, such as "Sadness", "Fear & Anxiety", "Contempt & Malice", or "Calm & Grounded". Relevant when someone wants a more precise word for a feeling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryYesCategory name, for example "Overwhelmed" or "Relational Hurt".

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 and openWorldHint=false, so the safety profile is covered. The description adds a genuinely useful trait ('every word' in the category, i.e. complete enumeration, no filtering or paging), but says nothing about behavior on an invalid or misspelled category, which is a real risk for a free-text input.

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?

Two compact sentences with zero waste: the core behavior is front-loaded and the usage cue follows. Nothing is padded or repeated from the title.

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 one-parameter read-only tool with no output schema, the description covers what is returned at a high level. However, it omits how to obtain a valid category value (the sibling list_categories) and any error behavior, leaving a meaningful gap for correct 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?

Schema description coverage is 100% and the single parameter already carries its own examples in the schema. The description's sample category names ('Sadness', 'Fear & Anxiety', 'Contempt & Malice', 'Calm & Grounded') supplement rather than duplicate the schema examples, giving marginal extra value — baseline 3 fits.

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 gives a specific verb+resource ('Returns every word in one category of the Surfacing feelings list') and enumerates concrete category examples, so the scope is unambiguous. It does not explicitly contrast itself with siblings like list_categories or search_words, which is the only thing separating it from a 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?

'Relevant when someone wants a more precise word for a feeling' gives a clear situational trigger, but there are no exclusions or named alternatives. Notably, it never points to list_categories as the way to discover valid category names, which is the most likely upstream need given the required enum-less category parameter.

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