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Kav-png

quantjobs

by Kav-png

generate_cv

Create a CV PDF tailored to a job by reordering experience and flagging missing skills as pending projects.

Instructions

Generate a CV PDF — base (job_id=0) or tailored to a job. Tailoring only reorders/selects your real experience; missing skills become pending projects + flags rather than fabricated bullets. stretch_level: conservative | balanced | aggressive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idNo
stretch_levelNo
Behavior4/5

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

The description discloses key behaviors: it reorders/selects experience, handles missing skills by adding pending projects and flags, and offers stretch_level options. However, it omits details about output format (e.g., how the PDF is returned) and potential side effects like saving or modifying state.

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?

The description is exceptionally concise, using two sentences to cover purpose, behavior, and parameters. No redundant information; every sentence adds value.

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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description provides a solid understanding. Missing elements include the format of the output PDF and prerequisites (e.g., having a profile or jobs). Still, it adequately covers the core functionality.

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?

With 0% schema description coverage, the description adds critical meaning: job_id determines base vs tailored, and stretch_level is explained with its values (conservative, balanced, aggressive). It could be improved by specifying that job_id refers to a job in the user's saved jobs list.

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

Purpose5/5

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

The description clearly states 'Generate a CV PDF' and distinguishes between base (job_id=0) and tailored to a job. This specificity differentiates it from sibling tools like cv_draft_create, which likely handle different aspects of CV creation.

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?

The description implies usage contexts (base vs tailored) but does not explicitly guide the agent on when to choose this tool over alternatives like cv_draft_create or cv_draft_update. No exclusions or when-not-to-use guidance is provided.

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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