resolve_utilityResolve the serving electric utility for a ZIP with provenance and honest confidence.
| Name | Required | Description | Default |
|---|---|---|---|
| zip | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, open-world, idempotent, non-destructive. The description adds value by mentioning 'provenance and honest confidence', hinting at output metadata. No contradictions.
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?
Single sentence, front-loaded with verb and resource. No unnecessary words. Highly efficient.
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 simple lookup with output schema, the description covers the input and hints at output (provenance, confidence). Could mention invalid ZIP handling, but overall adequate.
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?
With 0% schema description coverage, the description must explain the 'zip' parameter. It only says 'for a ZIP', missing details like required 5-digit format, examples, or validation. Minimal added meaning.
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 resolves the serving electric utility for a ZIP code, with specific verb 'resolve' and resource 'electric utility'. It is distinct from siblings like 'check_rebates' and 'get_energy_profile'.
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?
Usage context is implied but not explicitly stated. No guidance on when to choose this over sibling tools or when not to use it. The description assumes the user knows to use it for utility lookup.
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 tool targets a distinct ZIP-level question: utility resolution, energy profile, rebate screening, and program status. There is some overlap between check_rebates and get_program_status, and get_energy_profile also mentions rebate potential, but the descriptions clarify the boundaries enough for an agent to choose correctly.
All tool names follow a clean snake_case verb_noun pattern: check_rebates, get_energy_profile, get_program_status, resolve_utility. The verbs vary by action but the structure is fully consistent and predictable.
Four tools is well within the ideal range for a focused ZIP-level energy data server. Each tool earns its place and covers a distinct aspect of the domain without redundancy or bloat.
The tool set forms a coherent workflow: resolve the utility, get an energy profile, screen rebates, and check program status. It lacks deeper per-rebate or eligibility-detail endpoints, but that appears consistent with the stated screening-only purpose.