Validates and returns the complete stock-and-flow model supplied by the caller, enabling MCP hosts to confirm model structure and retrieve the accepted version in a stateless workflow.
Validate and return the complete model supplied by the caller. This server is stateless.
| Name | Required | Description | Default |
|---|---|---|---|
| model | Yes |
Changes observed during successful MCP inspections.
v0.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description does useful work by disclosing that the server is stateless, so no server-side state is created or mutated. It does not say what happens when validation fails (error shape, rejection vs. partial return) or how the 1,000,000-character limit is enforced.
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 short sentences with no waste, and the core action is front-loaded before the stateless qualifier. It is efficient, though its brevity is partly the cause of the disambiguation gap rather than a sign of completeness.
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 one-parameter, non-mutating tool with no output schema, the description covers the essentials of action and side effects. It still leaves the agent unsure how this differs from model_validate and what a validation failure looks like, which matters for correct selection.
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 0% for the single 'model' string, so the description carries the burden. Saying 'the complete model' adds meaning by implying a full document rather than a partial one or an identifier, but it never states the expected encoding (JSON string? raw text?) or what 'complete' structurally requires.
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 names a specific verb pair (validate and return) and resource (the model), but the name 'model_get' implies retrieval of a server-held entity while the description describes an echo/validate operation on caller-supplied input. It also overlaps heavily with the sibling model_validate, which is never distinguished.
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?
There is no statement of when to use this instead of model_validate, model_create, or model_update, all of which appear as siblings. The only contextual hint is the 'stateless' remark, which implies nothing is persisted, but the agent must infer that on its own.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.