describe_power_interconnection_queue_spp_v1Describe valid filters, groupings, metrics, detail fields, and citation fields for power.interconnection_queue_spp.
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No arguments | |||
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, providing a safe-read profile. The description adds context by specifying exactly what categories of metadata will be returned (filters, groupings, metrics, detail fields, citation fields), which goes beyond the annotations without contradicting them.
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 wastes no words. It clearly begins with the verb and resource, then lists the content categories. No unnecessary detail or repetition.
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 that this is a describe tool with an output schema and strong annotations, the description is sufficiently complete. It names the dataset and enumerates the fields it documents, which is all an agent needs to decide whether to call it. However, it does not explicitly state that this is a preliminary step before querying, though that is strongly implied.
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 takes zero parameters, so schema description coverage is trivially 100%. Per the rubric, a null-parameter tool gets a baseline of 4. The description does not need to explain parameters and does not add anything misleading.
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 clearly states the verb 'Describe' and the specific resource 'power.interconnection_queue_spp', and enumerates the types of information covered (filters, groupings, metrics, detail fields, citation fields). This distinguishes it from 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 usage: call this tool to learn the valid fields before querying the SPP dataset. However, it does not explicitly state when to use this tool versus alternatives (e.g., the generic describe_power_interconnection_queue_v1 or other region-specific describe tools), nor does it provide any exclusion guidance.
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.