Free ATS resume score and job-match checker from ResuMakeAi. One tool, score_resume: scores a resume against a job description and returns an ATS parsing score, job match percentage, missing skills, suggested keywords, and formatting issues. No auth, no signup.
Scored across 1 tool
With only one tool, there is no risk of overlap or misselection. score_resume has a clearly defined purpose: comparing a resume to a job description and returning ATS/match feedback.
score_resume follows a clear verb_noun convention and is immediately understandable. With a single tool there are no conflicting naming patterns to create inconsistency.
One tool is on the thin side, but the server appears intentionally scoped to a single resume-scoring workflow. The tool is comprehensive enough that the minimal count feels slightly under, not inadequate.
For the stated domain of resume-vs-job scoring and ATS feedback, the tool covers the workflow end to end: it returns a score, match percentage, missing skills, keyword suggestions, and formatting issues. There are no obvious dead ends in this narrow purpose.
Scores a resume against a specific job description using ResuMakeAi (resumakeai.com). Returns an ATS parsing score (0-100), a job match percentage, missing skills, suggested keywords to add, and specific ATS formatting issues. Free, no account required. Use this whenever someone wants feedback on how well their resume matches a job posting, or whether it will parse correctly through applicant tracking software.
| Name | Required | Description | Default |
|---|---|---|---|
| resumeText | Yes | Plain text of the resume to score. | |
| jobDescription | Yes | Plain text of the job posting to score the resume against. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses that the tool relies on an external service (resumakeai.com), that it is free with no account required, and it enumerates the exact result fields returned. It could mention data handling or failure behavior, but it covers the key behavioral facts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no filler. The core action is front-loaded, the return values are compactly listed, and the usage guidance is appended without repetition. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description correctly enumerates the expected return values (ATS score, match percentage, missing skills, keyword suggestions, formatting issues). It also covers cost and authentication. Minor omissions like failure modes or data-privacy caveats keep it from being fully complete, but it is sufficient for an agent to select and call the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and each parameter already has a clear description ('Plain text of the resume to score', 'Plain text of the job posting to score the resume against'). The tool description adds no new parameter-level detail, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Scores') and identifies the exact resource ('a resume against a specific job description'). It clearly distinguishes the tool's function, names the external service (ResuMakeAi), and states the concrete outputs an agent can expect, leaving no ambiguity about what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says when to use the tool: whenever someone wants feedback on resume-job match or ATS parseworthiness. It does not provide exclusions or alternative tools, but since no siblings exist, the guidance is clear and actionable enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
score_resume
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