ofp_semantics

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, so the bar is lower. The description adds useful behavioral context: every code includes fieldCount, a high count signals a generic fallback, and maxFieldCount filters to more specific alignment targets. This goes beyond the annotations without contradicting them.

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?

Three sentences, each earning its place: the first states the action, the second provides the use case, and the third explains the key parameter with a concrete recommendation. Front-loaded and free of filler.

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 small tool with one optional parameter and no output schema, the description covers purpose, use case, return-field meaning, and filtering strategy. It doesn't fully enumerate the response shape, but it gives enough for an agent to call it correctly in the intended scenario.

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 describes maxFieldCount, so the baseline is 3, but the description adds significant meaning: it explains why a high fieldCount is undesirable, recommends '10 is a good start,' and frames the parameter as a way to get codes specific enough to be real alignment targets. This is actionable guidance beyond the raw schema.

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?

States a specific action ('List the O-DEF semantic codes carried by the canonical model') with a clear resource target. The use case (mapping external systems like SAP or ERP feeds onto Open Footprint) further distinguishes it from sibling tools, especially ofp_semantic_code, which is likely for a single code.

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?

Explicitly says when to use: 'Use this when mapping fields from another system — SAP, an ERP, a supplier feed — onto Open Footprint.' It gives clear context but does not explicitly state when not to use it or name an alternative tool.

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