Full data for an antenna structure by ASR registration number — owner, location, height, declared licensees on the tower, microwave paths terminating there, and licensees within 50 m by spatial proximity. Returns Markdown.
| Name | Required | Description | Default |
|---|---|---|---|
| asr_number | Yes | 7-digit ASR registration number |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present, so description fully describes behavior: returns comprehensive data in Markdown format. Discloses exactly what fields are included, which is good for transparency. Could mention read-only nature or potential errors, but still solid.
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 efficiently conveys purpose, content, and output format. No wasted words, front-loaded with key action.
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?
No output schema, but description covers return format (Markdown) and lists included data. For a simple lookup tool with one parameter, this is nearly complete. Missing error handling details, but not critical.
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?
Schema already describes 'asr_number' as '7-digit integer' with 100% coverage. Description does not add beyond that, but parameter is simple and schema is sufficient, so baseline 3 is exceeded due to clarity.
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?
Description clearly states 'Full data for an antenna structure by ASR registration number' and lists specific content types (owner, location, height, licensees), making the tool's purpose unambiguous and distinguishing from sibling 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?
No explicit guidance on when to use vs. alternatives like license_detail or path_profile; context is implied by content listing but not stated. Agent must infer use case.
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 entity: license by call sign, path by USI/path number, free-text search, and tower by ASR number. No functional overlap.
All names use snake_case with a consistent structure: noun_detail or noun_profile. 'search' is a single word but fits the pattern.
With four tools, the surface is well-scoped: a search tool to locate identifiers, then three detail tools for licenses, paths, and towers. No extraneous tools.
The set covers the core querying needs for FCC data: search, license details (including paths), and tower details. Lacks direct spatial or frequency-range search, but the free-text search suffices for most uses.