sentiment_score
Lightweight sentiment polarity
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Input text |
Lightweight sentiment polarity
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Input text |
Changes observed during successful MCP inspections.
Input schema / properties / argsRemoved value: -{
- "description": "Tool arguments",
- "properties": {
- "text": {
- "description": "Primary input text",
- "type": "string"
- }
- },
- "type": "object"
-}Input schema / properties / textAdded value: +{
+ "description": "Input text",
+ "type": "string"
+}Input schema / requiredPrevious value: -[]New value: +[
+ "text"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must carry the full disclosure burden. It only says 'Lightweight' and 'polarity' but does not disclose output format, range, or whether it handles neutral text. This is a significant transparency gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief, but it is under-specified rather than concise. It uses only a fragment without an active verb and omits critical information, so it does not earn its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should at least indicate the return shape (e.g., a score between -1 and 1 or a label). It does not, leaving the tool's behavior incomplete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'text' described as 'Input text'. The description adds no additional meaning or constraints beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Lightweight sentiment polarity' lacks a verb and directly restates the tool's name ('sentiment_score' → 'sentiment polarity'). It fails to specify what action the tool performs or how it differs from siblings like 'text_similarity' or 'keyword_extract'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance is provided. The description does not mention alternatives or contexts where this tool should be preferred, leaving the agent without decision criteria.
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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