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careerpro_resume_get

Read-onlyIdempotent

Tailored resume for one opening as PDF (base64) and text 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

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": {
      "job_id": "<job_id>"
    },
    "name": "careerpro_resume_get"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesjob_id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, and the description is consistent with them. It adds genuine value beyond the annotations by disclosing the return encoding (base64 PDF plus plain text) and the cost/quota profile (free, 200 calls per day per IP), which an agent needs before invoking a paid-style API.

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 purpose and return formats are front-loaded and clear, but the trailing pricing JSON blob (including a URL) is noise for tool selection and is likely identical boilerplate across all siblings. It also spills into a second sentence fragment without a clear delimiter before 'Pricing:'.

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 single-parameter read tool with no output schema and strong annotations, the description covers the essential unknowns: what is returned and in what encoding. It omits edge cases such as behavior for an invalid or unknown job_id, which keeps it from a 5.

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 coverage is 100%, but the single property's schema description is just the tautology 'job_id'. The prose does not say where job_id comes from or what it identifies. With full schema coverage the baseline of 3 applies, and the description adds nothing further.

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?

States the specific resource ('Tailored resume for one opening') and the two return formats (PDF base64 and text), which distinguishes it from siblings like careerpro_letter_get and careerpro_pack_get by artifact type. The verb is only implied by the name, and it never explicitly contrasts itself with those siblings.

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 when-to-use guidance: nothing says to call this after careerpro_jobs_list, nor when to prefer a letter or pack instead. The only guidance-like content is pricing boilerplate, which says nothing about invocation conditions.

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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