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record_reaction

Capture user reactions to movie or TV titles and optionally link them to a recommendation run for tracking feedback.

Instructions

Record a reaction and optionally link it to a recommendation run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNo
run_idNo
audienceYes
reactionYes
title_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions that a reaction can optionally be linked to a run, but does not state whether this is a write operation, whether it is idempotent, what errors may occur, or the format of the response. This is a minimal disclosure insufficient for safe invocation.

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?

The description is a single, clear sentence with no wasted words. It front-loads the primary purpose and quickly mentions the optional linking. It is appropriately concise for the information it conveys, though it is so short that it sacrifices depth.

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?

With five parameters, no annotations, and zero schema description coverage, the description is far too sparse. It does not explain what constitutes a 'reaction', how to specify an audience, or the meaning of 'run_id' and 'note'. An agent would need to infer most usage context from parameter names alone, making correct invocation risky.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate by explaining parameter meanings. It does not mention any of the five parameters (audience, title_id, reaction, run_id, note) or their roles. Even the enum values for 'reaction' and 'audience' are left unexplained, providing no added value over the raw schema.

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 action ('Record a reaction') and the optional extension ('link it to a recommendation run'). It is specific and distinct from siblings like 'record_recommendations' and 'get_recommendation_history'. The purpose is unambiguous and not a tautology.

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?

The description provides no guidance on when to use this tool versus alternatives. It only mentions the optional linking to a recommendation run, implying a use case but without stating prerequisites, exclusions, or comparisons to sibling tools. An agent cannot determine when to choose this over other recording/history tools.

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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