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KhushalB25

resume-scorer-mcp

by KhushalB25

score_resume_from_freeform

Scores free-form resume text by extracting email, GitHub, project names, and tech keywords using regex, then applies an engineering rubric to produce a numeric score.

Instructions

Score a resume passed as free-form text. The server makes best-effort regex extraction of email, GitHub, project names, and tech keywords. Less accurate than score_resume with structured input.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesFull resume text (plain text, no formatting).
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool uses 'best-effort regex extraction' and acknowledges lower accuracy. However, it does not mention potential failure modes, output format, or what happens when extraction fails, which would improve transparency. Still, the stated limitations are valuable.

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 two sentences, each earning its place: the first states the core purpose, the second adds a critical limitation and comparison. It is front-loaded and concise with no redundancy.

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 simplicity (single parameter, no output schema, no annotations), the description covers purpose, usage guidelines, and behavioral transparency adequately. However, it omits details about the output (e.g., score range or format), which would enhance completeness. Still, it is largely sufficient.

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% (one parameter with a description). The tool description does not add meaning beyond the schema's parameter description; it merely restates 'Full resume text (plain text, no formatting.)' as present in the schema. Thus, the baseline of 3 applies.

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 the action 'Score a resume' and specifies the resource as 'free-form text'. It distinguishes from the sibling tool by noting it is less accurate and for free-form input versus structured input, satisfying the requirement for specific verb and resource with sibling differentiation.

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?

The description explicitly advises that this tool is less accurate than score_resume, which implies it should be used when only free-form text is available, and the sibling is preferred for structured input. This provides clear when-to-use and when-not-to-use guidance with an alternative named.

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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