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CoachingPortal by Cotlet

Get ai credit balance in CoachingPortal

coachingportal_get_ai_credit_balance
Read-onlyIdempotent

Get ai credit balance in the user's own CoachingPortal account from ChatGPT, Claude or any AI agent. Returns how to do it in CoachingPortal step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's CoachingPortal Cloud Browser. CoachingPortal's official API: CoachingPortal publishes no public API.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "coachingportal_get_ai_credit_balance"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavioral facts beyond that: the output is procedural guidance (screens, buttons, fields), no browser action is performed, and CoachingPortal has no public API so a browser path is required. It does not describe the shape or length of the returned guidance, which keeps it from a 5.

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

Conciseness3/5

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

The core instruction is front-loaded and nothing is padded with marketing language, but the middle sentence is a run-on that packs return format, side-effect guarantee and hand-off into one clause chain, and 'CoachingPortal's official API: CoachingPortal publishes no public API' repeats the subject needlessly. It would read better as three short sentences.

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 zero-parameter, read-only instruction tool with an annotation set that already covers safety, the description supplies everything needed to call it and act on the result: what it returns, that it performs no browser action itself, and which tool family to use to carry out the steps.

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 takes zero parameters, so there is no parameter meaning for the description to add; the baseline for a parameterless tool is 4. Nothing in the description misrepresents the (empty) input contract.

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 states a specific resource (AI credit balance) and scope (the user's own CoachingPortal account), and importantly clarifies that the tool returns step-by-step instructions rather than the balance itself. That distinction from an actual data-fetching call is the key disambiguation an agent needs, though the phrasing 'Get ai credit balance' in the name still invites a moment of confusion before the clarification lands.

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

Usage Guidelines4/5

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

It gives a usable workflow context: call this to learn the procedure, then execute it with the cotlet_browser_* tools in the user's Cloud Browser, and it explicitly notes the tool 'opens nothing by itself.' What is missing is an explicit exclusion — e.g., a direct statement of when to prefer a dedicated balance tool such as cotlet_balance over this instruction-generating one.

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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