ai_consultation
AI consultation with a senior strategist. Price: $5.00/call (x402, USDC on Base).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The task, question, or input for this AI service. |
AI consultation with a senior strategist. Price: $5.00/call (x402, USDC on Base).
| Name | Required | Description | Default |
|---|---|---|---|
| prompt | Yes | The task, question, or input for this AI service. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose a genuine behavioral trait the schema cannot express: a $5.00 per-call cost paid via x402 in USDC on Base. That is real value. However it says nothing about latency, output format, rate limits, or what happens on payment failure.
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 short sentences, purpose first, payment constraint second. Every clause earns its place with no filler or restatement of the title.
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 one simple parameter and no output schema, the description is nearly sufficient, and the pricing disclosure is a meaningful addition. It still leaves the agent unable to predict what comes back from the "senior strategist," which matters for a paid call.
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?
There is a single parameter with 100% schema description coverage, so the schema already explains "prompt" adequately. The description adds no meaning beyond it (no guidance on prompt length, framing, or what a good strategist prompt looks like), 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?
"AI consultation with a senior strategist" gives a general verb+resource, but "consultation" and "strategist" are vague about what actually happens — is it advice, analysis, or a chat reply? Against siblings like chatbot, longform_qa, and negotiation_advisor, an agent cannot tell precisely which to pick.
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 states no conditions for use, no exclusions, and never references any alternative tool. The only guidance is implicit in the price tag. An agent must guess when this beats chatbot or longform_qa.
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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