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ecidk

Research Insights MCP Server

by ecidk

identify_emotional_triggers

Analyze user research data to identify what causes positive or negative emotional reactions, using sentiment filtering and intensity thresholds.

Instructions

What causes positive/negative reactions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sentimentYes
min_intensityNo
context_windowNo
Behavior1/5

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

The description discloses no behavioral traits. With no annotations provided, the description carries full burden but fails to mention any side effects, permissions, or operational details (e.g., what triggers are identified, how intensity is used).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (one phrase), but this is under-specification rather than conciseness. It lacks essential details and is not front-loaded with actionable information.

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

Completeness1/5

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

Given the tool has 3 parameters, no annotations, and no output schema, the description is severely incomplete. It provides almost no context for correct invocation or interpretation of results.

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 coverage is 0%, meaning the description must explain parameter meanings. It does not mention sentiment, min_intensity, or context_window at all, leaving the agent to infer from parameter names alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

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

The description is a vague question ('What causes positive/negative reactions') rather than a clear statement of the tool's action. It does not specify a verb or resource, and fails to distinguish from sibling tools like analyze_sentiment_shifts.

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?

No guidance is provided on when to use this tool vs alternatives. There is no mention of context, prerequisites, or exclusions, leaving the agent without decision support.

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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