AI Applyd

Set Resume

aiapplyd_set_resume

Destructive

Instructions

Put the user's resume on their AI Applyd account as the base every application is tailored from. Pass exactly one: resume_text (the full text), resume_url (an https link to a PDF, DOCX or plain text file, up to 10 MB), or document_id (one of their saved resumes, from aiapplyd_get_account). A new upload is read by AI and uses the user's AI credits; switching to a saved resume with document_id is free. It also finishes account setup, so AI Applyd starts finding jobs for them. Use it when aiapplyd_get_account shows no resume on file, or when the user gives a new one. Do not use it to rewrite or score a resume; use aiapplyd_optimize_resume or aiapplyd_score_resume. Next: aiapplyd_get_matches. In ChatGPT the user can attach a resume file; pass it as resume_file. It replaces the user's current base resume (the old one stays in their documents), so call it only when the user wants this resume used.

Input Schema

TableJSON Schema

Name	Required	Description
`resume_url`	No	An https link to the resume file: PDF, DOCX or plain text, up to 10 MB. Pass this OR resume_text OR document_id.
`document_id`	No	One of the user's saved resumes to make the base (an id from aiapplyd_get_account). Free. Pass this OR resume_text OR resume_url.
`resume_file`	No	In ChatGPT the user can attach a resume file; pass it as resume_file. It is downloaded once, right away: PDF, DOCX or plain text, up to 10 MB.
`resume_text`	No	The full text of the resume. Pass this OR resume_url OR document_id.

Output Schema

TableJSON Schema

Name	Required	Description
`parsed`	Yes	False when the resume is still being read; call aiapplyd_get_account in a minute.
`source`	Yes
`fullName`	Yes
`documentId`	Yes	The resume now used as the base for every application.
`skillsCount`	Yes
`currentJobTitle`	Yes
`preferencesSeeded`	Yes	True when empty job preferences were filled from this resume.
`suggestedJobTitles`	Yes
`onboardingCompleted`	Yes	True when the account setup is finished, so AI Applyd searches for this user.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.9.0Oct 14, 2026

addedInput schema / properties / resume_file

Added value: +{
+  "additionalProperties": false,
+  "description": "In ChatGPT the user can attach a resume file; pass it as resume_file. It is downloaded once, right away: PDF, DOCX or plain text, up to 10 MB.",
+  "properties": {
+    "download_url": {
+      "format": "uri",
+      "type": "string"
+    },
+    "file_id": {
+      "type": "string"
+    },
+    "file_name": {
+      "type": "string"
+    },
+    "mime_type": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "download_url",
+    "file_id"
+  ],
+  "type": "object"
+}

changedOutput schema / properties / source / enum

Previous value: -[
-  "text",
-  "url",
-  "document"
-]New value: +[
+  "text",
+  "url",
+  "file",
+  "document"
+]

Changed4 schema fields changedv1.8.5Oct 12, 2026
- removedOutput schema / properties / currentJobTitle / anyOf
```
Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / currentJobTitle / type
```
Added value: +[
+  "string",
+  "null"
+]
```
- removedOutput schema / properties / fullName / anyOf
```
Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / fullName / type
```
Added value: +[
+  "string",
+  "null"
+]
```
Addedv1.8.0Sep 25, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already flag destructive=true and non-idempotent, and the description corroborates rather than contradicts: it warns the call replaces the current base resume while the old one stays in documents, notes that a new upload consumes AI credits whereas document_id is free, and discloses the side effect of finishing account setup and starting job discovery. That is a rich behavioral disclosure beyond the annotation flags.

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?

It is long, but the structure is front-loaded: purpose, then the exactly-one rule, then costs, then usage, then next step. A couple of sentences (the resume_file attachment note) largely restate the schema, which is the only waste.

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?

For a destructive, four-parameter tool with a nested object and an output schema, the description covers the selection rule, cost trade-offs, prerequisite lookup, replacement semantics, and follow-up tool. Nothing needed to call it correctly is missing, and return values are correctly left to the output schema.

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?

Schema coverage is 100%, so the baseline would be 3, but the description adds real meaning: it states the mutual-exclusivity rule ('Pass exactly one') that the schema does not enforce via oneOf/anyOf, plus per-option cost implications and the ChatGPT file-attachment path. Minor gap: the 10 MB / 50k-char limits are already in the schema and are simply repeated.

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?

States a specific verb and resource ('Put the user's resume on their AI Applyd account as the base every application is tailored from') and explicitly distinguishes itself from aiapplyd_optimize_resume and aiapplyd_score_resume. An agent can tell it apart from siblings without opening any schema.

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?

Gives an explicit trigger ('when aiapplyd_get_account shows no resume on file, or when the user gives a new one'), an explicit exclusion ('Do not use it to rewrite or score a resume'), named alternatives, and a next step (aiapplyd_get_matches). This is textbook when/when-not/alternatives guidance.

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