ofp_models

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

Annotations already establish readOnly, idempotent, and non-destructive behavior. The description adds useful context beyond annotations: the exact scope of the return (eight domains, DDL dialect availability) and the fact that the content is 'free.' It does not contradict annotations and enriches the agent's expectations of the tool's output content.

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?

Two sentences, each earning its place: the first precisely defines the function, the second gives a meaningful usage cue. No fluff, no repetition of annotations, and the key scope detail is front-loaded.

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 tells the agent what the output covers (domains and DDL dialects) and when to use it, which is sufficient for a zero-parameter list overview. It does not describe the exact output structure, but the absence of an output schema and the simple list-like nature make this a minor gap rather than a critical one.

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 tool has zero parameters, so parameter documentation is unnecessary. The description correctly focuses on output scope rather than inputs, and the 100% schema coverage baseline for parameters is trivially satisfied.

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 verb ('List'), a precise resource ('the eight Open Footprint canonical model domains'), and adds a distinctive detail ('which database dialects have published DDL'). The sibling context includes entity- and sector-specific tools, so this description clearly sets the tool apart as a model-level overview rather than an entity lookup.

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 instructs 'Start here when building an app on the Open Footprint standard' and positions the tool as a preface to looking up individual entities. This provides a clear when-to-use context and an implicit when-not (for individual entity details), though it does not name an alternative sibling tool explicitly.

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