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Trainzilla Coach MCP

by io.github.Trainzilla
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offer_ai_coach_to_client

Offer Tzilla AI Coach to a client (they get the invitation in-app). (confirm-gated: previews until confirm: true)

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "clientId": "<clientId>"
    },
    "name": "offer_ai_coach_to_client"
  }
}

Input Schema

NameRequiredDescriptionDefault
confirmNoMust be true to actually execute. If false/omitted, returns a preview only.
clientIdYesClient's User _id (from list_clients)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=false; the description adds the crucial behavioral trait that the call is confirm-gated and returns a preview until confirm:true, preventing accidental execution. It also discloses the side effect (client gets an in-app invitation). It still omits permission requirements and what the preview contains.

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?

Two short clauses, front-loaded with the action and resource, with the gating rule appended. Minimal waste, though the double parenthetical construction is slightly clunky.

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?

For a 2-parameter mutation with full schema coverage and no output schema, the definition covers the action, side effect, and the confirm/preview protocol. Only post-execution behavior and any preconditions are unstated.

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% and both parameters are documented in-schema, including confirm's preview semantics and clientId's source (list_clients). The description mostly restates the confirm gating rather than adding new parameter meaning, so the baseline 3 applies.

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?

Names a specific verb (offer) and resource (Tzilla AI Coach) plus the target (a client), with the added note that the client receives an in-app invitation. That is concrete enough to distinguish it from adjacent tools such as get_ai_coach_engagement or trigger_ai_coach_run, though it does not explicitly differentiate itself.

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?

Usage is implied — this is how you grant a client access to the AI Coach. But there are no explicit conditions, prerequisites (e.g. whether the coach must have AI plans enabled, cf. set_ai_plans_enabled), or named alternatives for related actions.

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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