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save_output

Persist generated match analyses, tailored resumes, cover letters, and LinkedIn About drafts for an application; defaults to the active application when no slug is given.

Instructions

Persist generated content (match analysis, tailored resume, cover letter, or LinkedIn About draft) for an application. Defaults to the active application if application_slug is omitted. After saving a tailored resume, offer to export it with export_pdf.

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": {
      "output_type": "<output_type>",
      "content": "<content>"
    },
    "name": "save_output"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentYes
output_typeYes
application_slugNoOptional — defaults to the active application

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the full load. It discloses the implicit-active-application default and a post-save chaining step, which is real behavioral value, but it says nothing about whether saving the same output_type twice overwrites the prior record, whether it requires an active application to exist, or what is returned.

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?

Three sentences, front-loaded with the purpose, then the fallback behavior, then the workflow hook. The default-behavior sentence duplicates the schema description of application_slug, a small redundancy, but nothing else is wasted.

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

Completeness3/5

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

For a mutation tool with no annotations, no output schema, and low schema coverage, the description is only adequate. It covers purpose, defaulting, and the next workflow step, but leaves the overwrite/idempotency behavior and return value unexplained, which are the gaps an agent most needs closed.

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 only 33%, so the description needs to compensate. It partially does by naming the four output types and by restating the application_slug default, but "content" is entirely undefined in both schema and description — an agent is not told it should pass the full generated text rather than a path or reference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Persist generated content ... for an application" gives a specific verb and resource, and the parenthetical enumerates exactly the four content types in the output_type enum. It does not distinguish the tool from the sibling save_resume, so an agent must infer the boundary itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It states the default condition ("Defaults to the active application if application_slug is omitted") and a concrete follow-up routing rule ("After saving a tailored resume, offer to export it with export_pdf"). It gives no guidance on when to use this versus save_resume, which is the most likely confusion for an agent.

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