Compass OS: Career

tailor material

tailor_material

Destructive

Draft a resume or cover letter tailored to one tracked role (company and title as the pipeline lists them) from the user's profile, and save it on the job as its current draft. Use it when there's no tailored version yet or the user wants a fresh one; to change a saved one use edit_resume or edit_material, and to read it use get_material. It asks the user first, uses their AI and counts toward their plan's tailored documents for the month; every claim is checked against the profile and unbacked ones are counted in the reply. Returns a link to the draft. Once it's saved, undo can put it back within 24 hours.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "company": "<company>",
      "kind": "<kind>"
    },
    "name": "tailor_material"
  }
}

Input Schema

Name	Required	Description
`kind`	Yes	Which document: resume or cover_letter
`title`	No	The role's title as the pipeline lists it; leave it empty when the user named only the company
`company`	Yes	The employer's name, e.g. "Stripe"

Output Schema

Name	Required	Description
`text`	Yes	The answer, or what was done, in plain words for the user: the same text as content
`undo`	No	On a saved write: its undo handle, for undo within 24 hours
`widget`	No	The card the host draws with it, e.g. "pipeline"; "confirm" means a write waits for the user's Yes and nothing is saved yet

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 5, 2026

addedOutput schema / properties / undo

Added value: +{
+  "description": "On a saved write: its undo handle, for undo within 24 hours",
+  "type": "string"
+}

Changed4 schema fields changedNov 4, 2026

addedInput schema / properties / company / description

Added value: +"The employer's name, e.g. \"Stripe\""

addedInput schema / properties / kind / description

Added value: +"Which document: resume or cover_letter"

changedInput schema / properties / title / description

Previous value: -"The role's title; leave it empty when the user named only the company"New value: +"The role's title as the pipeline lists it; leave it empty when the user named only the company"

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "additionalProperties": false,
+  "properties": {
+    "text": {
+      "description": "The answer, or what was done, in plain words for the user: the same text as content",
+      "type": "string"
+    },
+    "widget": {
+      "description": "The card the host draws with it, e.g. \"pipeline\"; \"confirm\" means a write waits for the user's Yes and nothing is saved yet",
+      "type": "string"
+    }
+  },
+  "required": [
+    "text"
+  ],
+  "type": "object"
+}

First observedNov 4, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations declare a mutating, non-idempotent, destructive, closed-world write; the description adds substantially beyond that: it asks the user for confirmation first, runs on the user's own AI, consumes a monthly plan allowance, verifies every claim against the profile and reports unbacked ones, and can be reverted via undo within 24 hours. It also notes the reply contains a link to the draft.

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 front-loaded with purpose, then usage, then behavior, and every clause carries real information (quota, verification, undo window, return value). It is a single dense paragraph with several semicolon-joined ideas, so readability suffers slightly, but there is no filler.

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 three-parameter mutating tool with an output schema, the description covers the gaps that matter: confirmation behavior, cost/quota, result verification, the returned link, and reversibility. Nothing an agent needs in order to call it correctly or warn the user is missing.

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 description coverage is 100% and the enum is already documented, so the schema carries the parameter burden and a 3 is the baseline. The description adds only a light framing that company and title are 'as the pipeline lists them', which is largely already reflected in the title parameter's schema text.

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: 'Draft a resume or cover letter tailored to one tracked role... from the user's profile, and save it on the job as its current draft.' It also names the exact sibling tools it is not (edit_resume, edit_material, get_material), so an agent can separate create from edit and read without opening another 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 there's no tailored version yet or the user wants a fresh one') and explicit alternates for the neighboring cases: edit_resume/edit_material for changing a saved one, get_material for reading it. Nothing about routing is left to inference.

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

All Compass OS: Career tools Inspect

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