Plan Fiber Leadin

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses critical behavioral traits: 'INDICATIVE auto-routed road corridors — NOT engineered alignments; subject to survey, DBYD and carrier confirmation.' This warns about the nature of the output and limitations, which is exactly the kind of context that adds value beyond structured fields.

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 fairly extensive but well-structured: it starts with the core purpose, then gives an example, parameter summary, return summary, limitations, and exclusions. Each sentence adds information; no filler. The length is justified by the tool's complexity.

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?

The description covers all key contexts: what it does, example usage, input parameters, output structure, limitations, and alternatives. Even though an output schema exists, the description still summarizes the return fields (length_km, diversity, cost) and caveats, making it complete for an AI agent to decide when and how to invoke this tool.

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 schema already has 100% coverage, including descriptions for each parameter. However, the description adds extra meaning by clarifying roles ('candidate data-center site', 'carrier hotel/POP'), providing concrete example addresses, and stating defaults (n default 4). This is a useful supplement even though the schema carries most of the burden.

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 purpose: 'Plan N diverse, road-following fibre lead-in routes from a candidate data-center site to a carrier hotel / POP, with indicative build cost and a route-diversity read.' It uses a specific verb ('Plan'), names the resource ('fibre lead-in routes'), and distinguishes itself from siblings by explicitly referencing analyze_site and get_fiber_intel as alternatives for different needs.

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 gives explicit usage guidance: it answers a concrete question ('can I get N diverse fibre routes into this site, how far, how much, and where do they share a corridor?'), provides a working example, and explicitly states what not to use it for: 'Do NOT use for a single site-suitability score (use analyze_site) or fibre-provider footprints (use get_fiber_intel).' This is clear when-to-use vs alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.