Skip to main content
Glama

career_test

Match EVE players to suitable career paths by analyzing their preferences, then provide concrete first steps for the best fits.

Instructions

Data for the EVE career 'sorting hat'. Returns all recognized career paths with traits (social/risk/income/activity, who it appeals to, first ship, first steps). To use: interview the player about what they enjoy (solo vs group, risk appetite, building vs fighting vs exploring, active vs idle, how much structure they want), THEN call this and match their answers to 2-3 paths. Recommend concrete first steps, not just labels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the full burden. It transparently frames the tool as returning static data ('Data for...'), lists the returned trait categories, and clarifies that matching/recommendation is the caller's follow-up. It does not explicitly state 'read-only' or mention lack of side effects, but the intent is clear and no contradictions exist.

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 extremely concise—two succinct sentences plus a usage clause. It front-loads the purpose, then packs trait details and workflow into a compact, scannable form. Every sentence earns its place with no repetition or 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 tool with zero parameters and no output schema, the description is remarkably complete. It explains what is returned (all career paths with specific trait categories), how to use it (interview first, then call, then match), and even how to follow up (recommend concrete steps). No other details are necessary for an agent to invoke it correctly.

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 has 0 parameters, so per the rubric the baseline is 4. The description adds no parameter-specific meaning (and none is needed). It focuses on the return value and usage, which is appropriate for a no-input tool.

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 identifies a specific resource (EVE career paths) and verb ('Returns'), listing what is included (traits like social/risk/income/activity). This distinguishes it from sibling tools like 'what_should_i_do_tonight' by focusing on comprehensive career path data rather than suggesting immediate activities.

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?

Explicit usage guidance is provided: interview the player about preferences, then call this tool, then match answers to 2-3 paths, and recommend first steps. It does not name alternatives or state when not to use it, so it falls short of a full 5.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/henryjrobinson/eve-mentor-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server