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BACH-AI-Tools

Rchilli Resume Parser MCP Server

resume_parser_binary_api

Parse resumes from binary data in base64 format to extract structured information for recruitment and HR applications.

Instructions

Resume Parser Binary API allows you to parse the resume using binary data in base64 format.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure but fails to mention output format (structured JSON, raw text?), side effects (logging, storage), idempotency, or error conditions. It only describes the input modality.

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 single sentence wastes words restating the tool name concept ('Resume Parser Binary API allows you to') before getting to the action. It could be more direct (e.g., 'Parse a resume from base64-encoded binary data').

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

Completeness2/5

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

Given the lack of annotations, output schema, and defined input parameters, the description is insufficient. It omits what the tool returns (parsed fields, confidence scores?), error handling, and whether the operation is read-only or creates resources.

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?

Per the rubric, 0 parameters establishes a baseline of 4. The description adds critical context that base64-encoded binary data is expected as input, which the empty schema cannot convey. However, there is a concerning disconnect between the described base64 input and the empty parameter schema.

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 clearly states the tool parses resumes and specifies the input method (binary data in base64 format), distinguishing it from the sibling 'resume_parser_url_api'. However, it uses filler words ('allows you to') instead of a direct verb, slightly weakening clarity.

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 mention of 'binary data in base64 format' implies usage when file content is available locally, contrasting with the URL-based sibling. However, there is no explicit guidance on when to choose this tool versus the URL alternative or prerequisites like file size limits.

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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