describe_ai_infrastructure_trade_v1Describe valid filters, groupings, metrics, detail fields, and citation fields for ai_infrastructure.trade.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and idempotentHint=true, so the read-only nature is covered. The description adds meaningful behavioral context beyond the annotations by listing the specific categories of metadata returned (valid filters, groupings, metrics, detail fields, citation fields), which is exactly what an agent needs to know before querying. No contradictions with annotations.
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 a single, front-loaded sentence that precisely states what the tool does. No wasted words; every element ('valid filters, groupings, metrics, detail fields, and citation fields') earns its place by specifying the tool's full scope.
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?
For a describe tool with no parameters and an existing output schema, this description is complete. It tells the agent exactly what metadata will be described and explicitly names the target dataset. The presence of an output schema covers the return structure, so no additional explanation is needed.
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?
The tool has zero parameters and the schema is empty with 100% schema description coverage. The baseline for zero parameters is 4, and the description does not need to add parameter semantics since none exist. It correctly focuses on the output behavior.
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 uses a specific verb ('describe') and explicitly names the resource ('ai_infrastructure.trade') and the exact categories of information it returns (filters, groupings, metrics, detail fields, citation fields). This clearly distinguishes it from the many sibling describe tools for other datasets.
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 implies that this tool is a metadata/describe companion to query_ai_infrastructure_trade_v1, but it does not explicitly state when to use it versus alternatives or provide any 'when not to use' guidance. The purpose is clear from the verb and resource, but the usage context is only implied by the sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each capability has a clearly named describe/query pair, and domains like power, AI infrastructure, robotics, and space are distinct. The generic describe_capability_v1/query_capability_v1 could be confused with the named variants, and the many ISO-specific interconnection queues share similar names, but descriptions explicitly disambiguate them.
All tools follow a consistent lowercase snake_case verb_noun pattern: describe_<capability>_v1 and query_<capability>_v1, with a few utility tools like list_capabilities_v1 and get_source_evidence_v1. There is no mixing of conventions.
At 62 tools, the set is far too large for typical server scope. The describe/query pairs inflate the count even though each is justified, and the generic capabilities plus per-ISO variants make it feel heavy and hard to navigate.
The server covers each domain thoroughly with describe, query, and evidence verification, plus generic fallbacks for capabilities not yet in the client's tool list. Minor gaps exist (e.g., no county/state attribution for some data, no load types in ISO queues) but they are explicitly documented and workable.