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get_cv

Read-onlyIdempotent

Retrieve a CV in markdown, PDF, LaTeX, HTML, or Typst format for analysis, rendering, or typeset generation. Choose the desired format to get raw content or a self-contained interactive document.

Instructions

Data-layer tool: retrieves raw CV content in markdown, PDF, LaTeX, HTML, or Typst source.

When the cv-analyst skill is available, prefer invoking that skill instead of calling this tool directly — the skill orchestrates retrieval with proper formatting, artifact delivery, and summarization.

format='markdown' (default): LLM-readable text for analysis. format='pdf': original PDF binary for inline rendering. format='latex': full CV as LaTeX source (moderncv package) for typeset PDF generation. format='html': self-contained interactive HTML with theme switching and expandable cards. format='typst': full CV as Typst source (moderner-cv package) for typeset PDF generation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
enrichNoInclude semantic enrichments (cross-references, skill levels)
formatNo'markdown' returns LLM-readable text (default). 'pdf' returns the original binary PDF document for inline rendering. 'latex' returns the full CV as LaTeX source (moderncv package). 'html' returns a self-contained interactive HTML document. 'typst' returns the full CV as Typst source (moderner-cv package).markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.9

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, covering side-effect safety. The description adds format-specific behavioral details—such as 'original PDF binary for inline rendering' and 'self-contained interactive HTML with theme switching'—which go beyond the structured data. It does not discuss rate limits or errors, but these are less critical for a read-only retrieval tool.

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

Conciseness4/5

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

The description is front-loaded with a concise summary, then gives the skill-preference guidance, then enumerates formats line-by-line. It is slightly redundant with the schema’s format descriptions but remains tight and scannable; no sentence is wasted.

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?

With no output schema, the description compensates by specifying the return type for each format and noting the default. Annotations cover the safety profile. The only notable omission is any mention of payload size or pagination, but for a raw retrieval tool this is a minor gap, and the description is otherwise complete enough for correct invocation.

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%: both parameters are fully described in the input schema. The description largely restates the format parameter’s schema text and adds no additional meaning for the `enrich` parameter. Since the schema already does the heavy lifting, the description adds no extra value, which aligns with the baseline of 3.

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 opens with a specific verb ('retrieves'), a clear resource ('raw CV content'), and an explicit list of output formats. It distinguishes itself from siblings like get_cv_sections or get_cv_pdf_link by framing this as a low-level data-layer retrieval rather than a derived view or link.

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

Usage Guidelines5/5

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

It explicitly tells the agent when NOT to call this tool: when the cv-analyst skill is available, prefer that skill, and it explains why (orchestration, formatting, artifact delivery, summarization). This is direct routing guidance with a named alternative and condition.

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