describe_power_interconnection_queue_pjm_cycle_v1Describe valid filters, groupings, metrics, detail fields, and citation fields for power.interconnection_queue_pjm_cycle.
| Name | Required | Description | Default |
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No arguments | |||
| Name | Required | Description | Default |
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No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds context about the specific output aspects (filters, groupings, metrics, detail fields, citation fields) but does not disclose any additional behavioral traits beyond what annotations and the tool name imply. This is adequate but not exceptional.
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, focused sentence that is front-loaded with the verb 'Describe' and immediately identifies the resource and the specific aspects covered. Every word earns its place; there is no redundancy or extraneous content.
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 (0 params, output schema present, annotations provided), the description is complete for its purpose. It clearly states what the tool describes and for which dataset. The resource name includes 'cycle', aligning with the title, and the output schema covers return values, so no further 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, so the input schema is already fully covered (100%). The description does not need to elaborate on parameters. The baseline for 0 params is 4, and the description adds no unnecessary parameter information, which is appropriate.
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 tool's function: to describe valid filters, groupings, metrics, detail fields, and citation fields for a specific dataset. The resource 'power.interconnection_queue_pjm_cycle' is precisely identified, and the verb 'describe' distinguishes it from query tools. The explicit list of what is described adds specificity and differentiates it from other describe tools.
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 a clear usage context: when an agent needs to know the valid filters, groupings, metrics, detail fields, or citation fields for this dataset, use this tool. It does not explicitly name alternatives, but the distinction between describe and query tools and the dataset-specific naming provide sufficient context. No exclusions are given, but the purpose is clear.
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.