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career-mcp

career-mcp

by sindhujaIBM
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

get_active_application

Retrieves the stored resume, voice profile, and active job description together as context for match analysis, tailored resumes, cover letters, or LinkedIn About drafts.

Instructions

Returns the stored resume, voice profile, and the active job description together, as context for match analysis or content generation. Use this to: (1) run match analysis — identify genuine overlaps and honest gaps between the resume and JD, not keyword stuffing; (2) draft a tailored resume by reordering/reframing existing resume content for relevance, never fabricating experience; (3) draft a cover letter; (4) draft a LinkedIn About section. Match the voice profile's tone if one is set. Save any generated output with save_output.

Write the tailored resume as markdown in this exact shape so it renders cleanly to PDF:

Full Name

One-line tagline (target title / positioning) Contact line: City · email · phone · linkedin.com/in/... (one paragraph)

Summary (then a short paragraph)

Experience

Job Title — Company

Start – End | Location

  • achievement bullets

Skills (bullets, or a two-column table: | Area | Skills |)

Education

Output only the resume itself — no commentary before or after it.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_active_application"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations supplied, the description must carry the full behavioral burden. It discloses that this is a read that bundles three stored artifacts and adds a useful constraint ('match the voice profile's tone if one is set'), but it says nothing about behavior when no active application exists, whether missing pieces are omitted or null, or the shape of the returned bundle.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose and usage sentences are front-loaded and tight, but roughly half the text is an embedded markdown template dictating how to format a tailored resume. That template governs a downstream generation/write task, not the act of invoking this getter, so it is off-scope bulk for a selection decision.

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 zero-parameter, non-destructive read with no output schema, the description should characterize what comes back, and it names the three bundled artifacts but not their structure or partial-data behavior. Meanwhile it spends its remaining length specifying an output format for content this tool does not return, so completeness is uneven rather than absent.

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?

The tool takes zero parameters, so there is no parameter semantics for the description to compensate for; the baseline for a parameterless tool applies. Nothing is undocumented on the input side.

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 opening sentence states a specific verb and a precise composite resource: it returns the stored resume, voice profile, and active job description together. That composite scope also distinguishes it implicitly from the single-resource siblings get_resume and get_voice_profile, so an agent can select it without opening the schema.

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 gives an explicit numbered list of when to use it (match analysis, tailored resume, cover letter, LinkedIn About) and routes the agent to save_output for generated artifacts. It never states when not to use it, e.g. when only the resume or only the voice profile is needed and the narrower siblings would suffice.

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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