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aic0t

AI Coach MCP Server

by aic0t

Prepare AI Coach care

prepare_ai_coach_care
Read-only

Check which care actions are available for your mascot, then confirm them in the dashboard. See feed, sleep, wake, walk, or nurse options before deciding.

Instructions

Show which care actions (feed, sleep, wake, walk, nurse) are currently possible for a mascot. Changes nothing; the user must confirm in the dashboard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
localeNoDisplay language (BCP 47).
actionsNoCare actions to check. Defaults to every action currently possible for that mascot.
mascotIdNoA mascotId returned by status. Defaults to the primary mascot when omitted.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
mascotsYes
previewNo
appLocaleNo
updatedAtYes
appVersionNo
careResultNo
connectionYes
capabilitiesYes
protocolVersionYes
viewPreferencesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.4
    • changedInput schema / properties / locale / description
      Previous value: -"Display language hint (BCP 47). The dashboard view passes hostContext.locale through unchanged."New value: +"Display language (BCP 47)."
  2. First observedv0.1.2

TDQS

A4.1/5.0
Behavior4/5

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

The description reinforces the readOnlyHint by saying 'Changes nothing' and adds a workflow detail: the user must confirm in the dashboard. That goes beyond the annotation by explaining where the follow-up action occurs. Error/edge behavior is not discussed, but the output schema and annotations cover much of the remaining context.

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?

Two short sentences front-load the core purpose and the side-effect constraint with no filler. Every phrase earns its place by helping an agent decide when to call the tool and what to expect.

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?

For a simple read-only tool with no required parameters, a fully documented input schema, an output schema, and annotations, the description is complete enough. An agent has sufficient structured and textual context to select and invoke it correctly.

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 the schema already explains locale, actions, and mascotId; the description adds little parameter-level meaning. The listed 'walk' action is a slightly loose label for the schema enum 'toggle_walk', but the enum remains the authoritative value source.

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 ('Show') and a clear resource (care actions currently possible for a mascot), and it enumerates the action types. The sentence 'Changes nothing; the user must confirm in the dashboard' clarifies that this is a read-only preflight tool, distinguishing it from state-changing siblings like commit_ai_coach_care.

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 when to use it: to discover which care actions are possible before the user confirms. It does not explicitly name alternatives or state exclusions, though 'the user must confirm in the dashboard' hints that confirmation/commit happens elsewhere. This leaves some sibling differentiation to inference.

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