Get Behavioural Model

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

With no annotations, the description carries the full burden and does so: it declares the call read-only with no side effects, enumerates the status state machine (none / needs_answers / extracted / confirmed / stale) including what 'stale' means, and explains background-job polling semantics. This is behavioral context that neither the annotations (absent) nor the schema provide.

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?

Long but dense and front-loaded: purpose first, then return semantics ordered by field importance (status, questions, pending_answers, ir_hash, extraction.job). Nearly every clause carries usable information, though the return-value catalogue edges toward verbose given an output schema exists.

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?

Despite an output schema existing, the description goes further by explaining the status lifecycle, which fields drive follow-up sibling calls, and how to poll a running extraction — everything an agent needs to act on the result. Nothing material is missing for a two-parameter read 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?

Schema description coverage is only 50% and the description never mentions either parameter. 'server_version' is undocumented in both places, and 'model_id' is left to the schema's terse 'ID of the threat model.' — which the description also never confirms or constrains. For a 50%-coverage schema, the description fails to compensate.

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+resource ('Read a model's behavioural model') and immediately defines the resource as 'what the system does, as elements, actions and zones taken from its description'. It separates itself from the sibling extractor by noting 'extract_behavioural_model gives it one' when status is none, so an agent can choose between them without opening schemas.

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?

Routes the agent through the sibling graph: extract_behavioural_model when status is 'none', answer_behavioural_questions for open questions, confirm_behavioural_model to use ir_hash, and polling extraction.job until null. There is no explicit 'do not use this when…' exclusion, but the state-driven routing is clearer than most tools provide.

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