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Worthune Verified Financial Models

get_model_contract

Read-onlyIdempotent

Get a model's machine-readable contract: required inputs with types and valid domains, cross-field constraints, sentinel-value meanings, and the government constants (with sources) the model uses. Set include_spec to also receive the full specification markdown (exact formulas, assumptions, exclusions, known issues).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYesModel name from list_models, e.g. 'relocation'
api_keyNoWorthune Pro API key (wk_…) — required for include_spec on non-sample models.
include_specNoAlso return the full spec markdown (default false). Public for the free-sample models; other models need api_key.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, lowering the bar. The description adds useful behavioral context by explaining the composition of the contract (cross-field constraints, sentinel values, constants with sources) and the api_key requirement for include_spec, which is not fully covered by annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loads the core purpose, and adds optional context in the second sentence. Every word earns its place with no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema, the description takes on the burden of describing the return value and does so thoroughly: required inputs, types, valid domains, cross-field constraints, sentinel values, and constants with sources. The include_spec flag and its access rule are also covered, making the tool self-sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description does not add significant parameter-specific meaning beyond the schema; it mentions include_spec but the schema already describes its behavior and the api_key prerequisite. The extra content (government constants, sentinel values) describes outputs, not parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and object: 'Get a model's machine-readable contract' and enumerates the contents (inputs, constraints, sentinel values, constants). This clearly distinguishes it from siblings like list_models, run_model, and verify_claim.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on what the tool is for and how to extend its output via include_spec, but it does not explicitly state when to use this tool over its siblings or mention any exclusions. This meets the 'clear context, no exclusions' bar.

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

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TDQS

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: household CRUD, bulk import/mapping, projection/decision, model contract/run/verify, and narrative generation. Even the superficially similar pairs (project_household vs decide_household; run_model vs verify_claim) are clearly separated by their descriptions.

Naming Consistency5/5

All tool names use lowercase snake_case with imperative verb-first naming (create_, get_, patch_, replace_, run_, verify_). Pluralization follows natural semantics (list_models, import_households) without breaking the overall verb_noun pattern.

Tool Count5/5

13 tools is within the ideal range for a domain server. Each tool earns its place: household lifecycle, import tooling, model contract/run/verify, projection/decision, and narration form coherent clusters without redundancy.

Completeness4/5

Core workflows are well covered: create/read/update households, project and decide, list/get/run/verify models, and narrate decisions. Minor gaps remain: there is no delete_household or list_households, and no dedicated get_decision tool for retrieving a stored decision object independently.

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