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get_onboarding_status

Checks whether first-time onboarding is complete in .env before a Bedtime Book Studio session, then prompts the agent to collect character details and configure the studio.

Instructions

Call this FIRST when starting a session. Checks whether the user has completed first-time onboarding in .env (main character name, reference photo(s) and/or text appearance description, outfit, art style, and default book mode). If is_onboarded is false, follow agent_onboarding_instructions to ask the user for their main character details and call configure_studio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.7/5.0
Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses that the tool reads `.env`, returns an `is_onboarded` flag and `agent_onboarding_instructions`, and what onboarding fields are checked. However, it does not explicitly state that the operation is read-only or has no side effects, which is a minor gap for a no-annotation tool.

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?

Three tightly written sentences, front-loaded with the most important instruction ('Call this FIRST'). Every sentence adds necessary information: the check, the fields examined, and the conditional follow-up. No waste.

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 the tool has an output schema, the description need not explain return values. It still provides the conditional logic for acting on the result and names the relevant sibling tool, making it complete for an agent to invoke and follow up correctly.

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?

The tool has zero parameters, so per the rubric the baseline is 4. There are no parameter semantics to clarify, and the description appropriately focuses on behavior rather than nonexistent inputs.

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?

States a specific verb and resource ('Checks whether the user has completed first-time onboarding in `.env`') and front-loads the invocation priority ('Call this FIRST when starting a session'). It clearly distinguishes itself from the conditional next-step sibling `configure_studio`, so an agent can tell what this tool is for without opening the schema.

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

Usage Guidelines5/5

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

Explicitly says when to use it ('Call this FIRST when starting a session') and provides a conditional alternative: if `is_onboarded` is false, follow `agent_onboarding_instructions` and call `configure_studio`. This gives the agent a clear decision path and names the alternative tool.

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