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detonnate

careerproof-mcp

by detonnate

Export interview preparation pack

careerproof_export_preparation_pack

Assembles a complete evidence-backed preparation pack for a job, matching requirements to cited evidence, identifying gaps, and generating interview questions. Returns JSON or Markdown.

Instructions

Assembles the complete evidence-backed preparation pack for a job: requirement matches, evidence gaps, and generated interview questions. Returns either JSON or a Markdown report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdYesJob ID returned by careerproof_analyse_job_description
formatNojson
candidateIdNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden, and it does disclose the output medium ('Returns either JSON or a Markdown report'), which is genuinely useful. However, it says nothing about side effects (is anything persisted?), cost/latency implied by generating interview questions, or whether it requires prior analysis state, so the disclosure is partial.

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 tightly written sentences: the first front-loads what is assembled and its components, the second covers the return format. No filler, no restatement of the tool name, every clause earns its place.

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 three-parameter aggregation tool with no output schema and no annotations, the description covers purpose and output medium but leaves the candidateId parameter unexplained and gives no usage routing against the many sibling tools that perform the same sub-tasks. Adequate but with clear gaps.

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 only 33%, so the description should compensate, and it partially does by explaining the output format choice (JSON vs Markdown) that the 'format' parameter controls. It adds nothing about 'candidateId' (unlabeled in schema and absent from the description) and only implicitly covers jobId via the task framing.

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 gives a specific verb ('Assembles') and a well-defined artifact ('complete evidence-backed preparation pack for a job'), then enumerates the three contents: requirement matches, evidence gaps, and generated interview questions. That enumerates capabilities that map onto sibling tools (match_requirements, find_evidence_gaps, generate_interview_questions), implicitly distinguishing this aggregator from them, but it never names those siblings or states the distinction explicitly.

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 whether to reach for this aggregate pack versus calling careerproof_match_requirements, careerproof_find_evidence_gaps, and careerproof_generate_interview_questions individually, nor whether a candidate profile must exist first. The only prerequisite information (jobId coming from careerproof_analyse_job_description) lives in the schema, not the description.

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