AI Applyd

Score Resume

aiapplyd_score_resume

Score a resume for ATS compatibility, receiving overall and section scores, matched and missing keywords, and rewrite suggestions. Optionally compare against a job description for a targeted score.

Instructions

Score a resume for ATS compatibility. Returns an overall score, section scores, the keywords the resume matches and the ones it is missing, and specific rewrite suggestions. Pass job_description to score against a posting, or omit it for a general ATS readiness score. Requires a connected AI Applyd account and uses the user's credits. Do not use it to rewrite the resume; use aiapplyd_optimize_resume. Next: aiapplyd_optimize_resume rewrites the resume against the same posting.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`resume_text`	Yes	Full text of the resume
`job_description`	No	Full text of the job description (optional, omit for a general ATS readiness score)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`suggestions`	Yes
`overallScore`	Yes
`sectionScores`	Yes
`keywordMatches`	Yes
`missingKeywords`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.8.0Sep 25, 2026

removedInput schema / additionalProperties
```
Removed value: -false
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "keywordMatches": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "missingKeywords": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "overallScore": {
+      "type": "number"
+    },
+    "sectionScores": {
+      "additionalProperties": false,
+      "properties": {
+        "education": {
+          "type": "number"
+        },
+        "experience": {
+          "type": "number"
+        },
+        "formatting": {
+          "type": "number"
+        },
+        "keywords": {
+          "type": "number"
+        },
+        "skills": {
+          "type": "number"
+        }
+      },
+      "required": [
+        "skills",
+        "experience",
+        "education",
+        "formatting",
+        "keywords"
+      ],
+      "type": "object"
+    },
+    "suggestions": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "overallScore",
+    "sectionScores",
+    "keywordMatches",
+    "missingKeywords",
+    "suggestions"
+  ],
+  "type": "object"
+}

First observedv1.3.0Sep 7, 2026

TDQS

A4.7/5.0

Behavior5/5

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

With annotations indicating readOnlyHint=false, destructiveHint=false, and idempotentHint=false, the description adds critical context: it requires a connected AI Applyd account and uses the user's credits, implying a cost. It also discloses the action is non-idempotent (credits spent) and not destructive. This goes beyond the annotations by explaining the account requirement and credit consumption.

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 efficient, with each sentence serving a purpose: defining outputs, explaining usage options, noting prerequisites, and routing to the sibling. It front-loads the core purpose and then the usage, and the sibling routing is placed at the end, helpful for flow.

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

Completeness5/5

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

Given the tool's moderate complexity, the output schema exists to document return values, and parameters are fully covered in schema, the description is complete: it states the inputs, the optionality, the account requirement, credit usage, and the boundary with the optimization tool. Nothing essential is missing for an agent to call it correctly.

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%, so both parameters (resume_text and job_description) are documented in the schema. The description adds the distinction between omitting job_description for a general score, which aligns with the schema's optional note. However, it doesn't add syntax or format details beyond that, so baseline 3 is appropriate.

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 tool scores a resume for ATS compatibility, lists the specific outputs (overall score, section scores, keywords, suggestions), and differentiates it from the sibling aiapplyd_optimize_resume by explicitly stating it does not rewrite. The verb 'Score' and resource 'resume' are specific, and the mention of optional job_description clarifies variants.

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 provides clear guidance on when to use it: pass job_description to score against a posting, or omit for general ATS readiness. It explicitly states 'Do not use it to rewrite the resume; use aiapplyd_optimize_resume' and names the alternative. This directly addresses selection among siblings and gives a next-step recommendation.

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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