Toofi Dental Planning MCP

Generate treatment-plan draft

generate_treatment_plan_draft

Idempotent

Generate a structured no-memory Toofi treatment-plan draft with visits, estimate, presentation outline, billing metadata, audit receipt shape, and dentist approval boundary.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	No	Natural-language clinical request for a treatment-plan draft.
`patient`	No
`agent_id`	No	Calling agent identifier.
`clinic_id`	No	Clinic identifier for mandate-scoped production execution.
`intent_id`	No	Root agent intent id.
`mandate_id`	No	Clinic or agent mandate id. Optional in public demo mode.
`procedures`	No
`request_id`	No	Idempotency and correlation id echoed in Toofi responses.
`patient_ref`	No	Agent-scoped patient reference.
`principal_id`	No	Human or clinic principal on whose behalf the agent acts.
`chief_complaint`	No	Patient chief complaint, no PHI required in public demo mode.
`clinical_request`	No	Structured or natural-language clinical request.
`clinical_findings`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`ok`	No
`mode`	No
`status`	No
`endpoint`	No
`timestamp`	No

TDQS

A4/5.0

Behavior4/5

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

Annotations already cover readOnly=false, destructive=false, and idempotent=true. The description adds 'no-memory' (stateless behavior) and 'dentist approval boundary' (workflow constraint), which go beyond the annotations. It does not detail failure modes or side effects, but the idempotency hint mitigates retry concerns.

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 a single sentence that front-loads the tool's purpose and lists all key output facets without filler. It is dense but concise, and every element contributes to understanding the tool's scope.

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

Completeness4/5

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

The description captures the tool's output shape (visits, estimate, presentation outline, billing metadata, audit receipt, approval boundary) and 'no-memory' behavior. An output schema exists, so detailed return structure is covered there. It could mention failure cases or required inputs, but it is sufficient for tool selection.

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 77%, and several parameters have individual descriptions (request_id, clinic_id, patient_ref, chief_complaint). The tool description does not add parameter-specific detail, but the baseline 3 applies because the schema handles most parameter semantics. 'No-memory' hints at request-scoped data but not tied to any parameter.

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 uses a specific verb and resource: 'Generate a structured no-memory Toofi treatment-plan draft'. It enumerates the draft's contents (visits, estimate, presentation outline, billing metadata, audit receipt shape, dentist approval boundary), which distinguishes it from sibling tools like generate_price_estimate and generate_dental_treatment_plan_pdf.

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

Usage Guidelines3/5

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

The description implies usage when a full treatment-plan draft is required, but it does not explicitly state when to use this tool versus alternatives such as generate_price_estimate or generate_patient_presentation. No exclusions or alternative guidance are provided.

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

B3.3/5.0

Disambiguation3/5

Several tools have overlapping purposes, particularly example_en, example_pl, example_ru, example_sk, example_ua, example_uk, and get_example_result, which all return example PDFs. Also, example_ua and example_uk are explicitly aliases for the same Ukrainian example, creating direct ambiguity. Core clinical tools are distinct, but the example/demo cluster muddies the boundary.

Naming Consistency4/5

Most tools follow a snake_case verb_noun pattern (e.g., list_patients, create_agent_checkout_session, generate_price_estimate), but a few deviations exist: example_en/pl/ru/sk/ua/uk lack a verb prefix, and get_example_result seems to duplicate example_en. The 'pano' abbreviation in start_pano_markup is also slightly inconsistent. Overall, the pattern is mostly predictable.

Tool Count2/5

With 32 tools, the count is too high for the apparent scope of dental planning. Many tools are redundant example/demo variants (e.g., 6 language-specific example tools plus get_example_result, and multiple demo getters/listers). This bloat suggests the tool set could be consolidated to a more focused 15-20 tools without losing core functionality.

Completeness3/5

The core workflow is covered: generating plans, retrieving patients/plans, pricing, and billing. However, there are notable gaps such as no update or delete operations for plans or patients, no create patient tool, and no way to modify pricing beyond import_price_csv. The demo tools partially compensate by offering sample data, but the production lifecycle is incomplete.

Resources

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