ai_quote_sellQuote how much HYPE a given amount of $AI returns right now, net of the on-chain sell fee.
| Name | Required | Description | Default |
|---|---|---|---|
| ai | Yes | $AI amount as a decimal string, e.g. "1000" (max 1000000000) |
| Name | Required | Description | Default |
|---|---|---|---|
| hypeOut | Yes | ||
| disclosure | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "disclosure": {
+ "type": "string"
+ },
+ "hypeOut": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "hypeOut",
+ "disclosure"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds value by disclosing that the quote is real-time ('right now') and that the result is net of the on-chain sell fee, which are behavioral details not present in the structured data.
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?
A single sentence with zero filler. It front-loads the action ('Quote') and the object, and each qualifier ('right now', 'net of the sell fee') earns its place by adding essential meaning.
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 the tool's simplicity (one parameter, read-only, idempotent), the output schema covers return values, annotations cover side effects, and the description covers purpose, timing, and fee treatment. Nothing an agent needs to call it correctly is missing.
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% with the parameter fully documented as a decimal string with max value. The description adds no extra parameter semantics beyond restating 'given amount of $AI', so the baseline 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 states a specific verb ('Quote') and resource ('how much HYPE a given amount of $AI returns'), and adds crucial qualifiers: 'right now' (real-time) and 'net of the on-chain sell fee' (fee-inclusive result). This distinguishes it from siblings like ai_quote_buy (buy side) and the tx builders.
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 description clearly implies this tool is for sell-side quotes, giving the agent context on when to use it. However, it does not explicitly name alternatives like ai_quote_buy or state when not to use it, so it stops short of full exclusion guidance.
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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