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maestro_answer

Submit an answer to a MAESTRO interview question and receive the next question or the final design decision.

Instructions

Submit an answer to the current MAESTRO question.

Call this tool to answer each question during the MAESTRO interview. Returns either the next question or a design decision if the interview is complete.

Args: session_id: Active session ID from maestro_start_session question_id: ID of the question being answered (from question.id) selected_options: List of selected option IDs (e.g., ["opt_landing_page"]). Most questions require exactly one selection. free_text: Optional free text input for text-type questions

Returns: Dict containing EITHER: - question: Next question (if interview continues) - progress: Updated interview progress (0.0 to 1.0) - status: "interviewing"

OR:
- decision: Final design decision with mode, confidence, parameters
- progress: 1.0
- status: "decided"

Example: # Answer a question result = await maestro_answer( session_id="maestro_abc123", question_id="q_intent_main", selected_options=["opt_new_design"] ) if result["status"] == "decided": # Ready to execute! decision = result["decision"] else: # More questions to answer next_question = result["question"]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
free_textNo
session_idYes
question_idYes
selected_optionsYes
Behavior3/5

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

Annotations are absent, so the description carries full burden. It explains the return structure (next question or final decision) but does not disclose side effects, state changes, or whether the tool is idempotent. It does not mention prerequisites beyond having a valid session_id. While the output behavior is clear, the behavioral traits beyond output are not fully transparent.

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

Conciseness4/5

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

The description is well-structured with sections for Args, Returns, and Example. It is front-loaded with the purpose. However, it is somewhat verbose; the Returns section could be more concise. Overall, it is organized and readable.

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?

Given the tool's complexity (interview flow with two possible outcomes) and no output schema, the description provides a thorough Returns section explaining both cases. It covers parameters and usage context. Minor omission: no mention of error handling or invalid session/ID cases.

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

Parameters4/5

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

With 0% schema description coverage, the description effectively adds meaning. It documents all four parameters in the Args section, explaining where to obtain each (e.g., session_id from 'maestro_start_session', question_id from 'question.id'). It also includes an example and notes about 'selected_options' typically requiring exactly one. This compensates well for the schema gap.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Submit an answer to the current MAESTRO question.' It identifies the verb ('submit') and resource ('MAESTRO question'), and explains its role in the interview flow. However, it does not explicitly differentiate it from sibling tools like 'maestro_get_decision' or 'maestro_get_progress', which reduces clarity slightly.

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 says 'Call this tool to answer each question during the MAESTRO interview.' It provides an example and explains two possible outcomes. However, it does not specify when NOT to use the tool (e.g., after interview is complete) or mention alternative tools from the sibling list. This leaves room for ambiguity in choosing the correct tool.

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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