CareerProAI

careerpro_pricing

Read-onlyIdempotent

Where prices live and what costs nothing Pricing: {"unit": "call", "price_usd": 0, "free_quota": "200 per day per IP", "note": "Keyed volume pricing is published at https://careerpro.tech/pricing.json"}.

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": "careerpro_pricing"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

C2.9/5.0

Behavior3/5

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

Annotations already declare readOnly, idempotent, and non-destructive, so safety is covered. The description does add genuinely new behavior information — free quota of 200 calls per day per IP and a link for keyed volume pricing — but it presents these as raw embedded JSON rather than explaining what the call returns.

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

Conciseness2/5

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

The lead sentence and the inline JSON blob are jammed together without clear separation, and the framing "Where prices live and what costs nothing" is rhetorical rather than informative. The readable substance is brief, but the structure is poor.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only tool with no output schema, the description should say what the response looks like (unit, price, free quota). It lists those fields inside the snippet but never frames them as return values, leaving a modest completeness gap.

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 the baseline is 4. The description adds auxiliary context (the external pricing.json URL and the free-quota rule) that is not expressible in an empty schema.

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

Purpose3/5

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

The description conveys that this tool concerns pricing ("Where prices live and what costs nothing"), but the phrasing is awkward and never says plainly that the tool returns pricing/quota information. An agent can infer the purpose, but it is not stated as a clean verb+resource.

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

Usage Guidelines2/5

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

There is no guidance on when to call this versus related metadata tools such as careerpro_about or usage_get. The only implicit cue is that it is the pricing-oriented endpoint, which the agent must deduce from the name and snippet.

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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