Full data for a single FCC license by call sign — licensee, locations with coordinates, antennas, paths, frequencies. Returns Markdown.
| Name | Required | Description | Default |
|---|---|---|---|
| call_sign | Yes | FCC call sign, e.g. KAC75 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the output format (Markdown) but fails to mention read-only nature, potential errors, prerequisites (e.g., valid call sign), or rate limits. For a simple query tool, key behavioral traits are missing.
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 concise sentence, front-loaded with key information, no wasted words. Efficiently conveys purpose and output.
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 one-parameter tool with no output schema, the description covers what data is returned and the output format. Minor gaps in behavioral details prevent a higher score.
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 coverage is 100% with one parameter (call_sign) described as 'FCC call sign, e.g. KAC75'. The description adds no extra meaning beyond listing data types returned; the schema already provides the format example.
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 retrieves full data for a single FCC license by call sign, listing specific data types (licensee, locations with coordinates, antennas, paths, frequencies) and output format (Markdown). This distinguishes it from sibling tools like path_profile or tower_detail.
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 when full license details by call sign are needed, but does not explicitly state when not to use or provide alternatives. Sibling tool names offer some context, but no direct exclusions.
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.