Sentiment analysis of a supplied block of text, or of current coverage of a named topic. $0.05/call via x402.
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | Text to score directly | |
| topic | No | Topic to gather and score instead of text |
Changes observed during successful MCP inspections.
Input schema / properties / text / examplesAdded value: +[
+ "Settlement volume on Base doubled this quarter while prices held."
+]Input schema / properties / topic / descriptionPrevious value: -"Topic to gather and score instead"New value: +"Topic to gather and score instead of text"Input schema / properties / topic / examplesAdded value: +[
+ "agent payments"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It usefully discloses the cost model ('$0.05/call via x402'), which is real behavioral context, but says nothing about return format, latency, or what 'coverage of a topic' actually entails (fetching, sourcing, etc.).
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?
Two tight sentences with the purpose front-loaded and the pricing appended. There is no redundancy or filler, though the pricing detail is the only thing beyond the one-sentence core.
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?
With no annotations and no output schema, the description should do more to describe what comes back (a score, a label, confidence, aggregation over a topic). The dual-mode operation and pricing are covered, but the return contract is left entirely undefined.
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 description coverage is 100% - both text and topic have descriptions plus examples - so the baseline is 3. The description only loosely restates the two modes and adds no format, length, or language constraints beyond what the schema already provides.
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?
States a specific verb+resource ('Sentiment analysis') and covers both operating modes (supplied text or named topic). It does not, however, differentiate itself from nearby siblings like classify_text or summarize_text, which an agent could plausibly confuse it with.
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?
The phrase 'of a supplied block of text, or of current coverage of a named topic' implies when to pass text vs topic, but there is no explicit when-to-use guidance, no exclusions, and no mention of alternatives such as classify_text. Usage is only implied.
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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