degree_roi5-year-after-graduation net ROI + break-even year for a degree. Pass a preset country slug (e.g. germany, uk-oxbridge, us-private) or 'all' for the ranked list.
| Name | Required | Description | Default |
|---|---|---|---|
| lang | No | Response language; defaults to en. | |
| country | Yes | ROI destination slug, or 'all' |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, so no contradiction. The description adds value by specifying the output content (net ROI and break-even year), which is beyond the annotation's safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. First sentence gives purpose, second sentence provides parameter guidance. Ideal conciseness and front-loading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters and no output schema, the description is complete. It explains what the tool returns, how to call it, and provides necessary examples. No missing context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% but parameter descriptions are generic. The description enriches them by explaining 'preset country slug' with examples and clarifying 'all' returns a ranked list. This significantly adds meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it provides '5-year-after-graduation net ROI + break-even year for a degree.' This specific verb+resource combination distinguishes it from sibling tools like compare_universities or get_university_profile.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells the user to pass a preset country slug or 'all', providing concrete examples. It implies when to use (when ROI data is needed) but doesn't explicitly state when not to use or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, distinct purpose: answering questions, comparing universities, calculating ROI, fetching details, getting profiles, listing universities, matching schools, and searching. No overlap in functionality.
All tool names use snake_case and follow a verb_noun or noun_noun pattern, making them predictable. The only minor deviation is 'fetch', which is a single verb, but it's still clear and common for such operations.
8 tools is ideal for an education data server, covering core operations (search, list, profile, compare, ROI, etc.) without being overwhelming or insufficient.
The tool set covers main user needs: answering questions, searching and listing universities/schools, getting profiles and comparisons, and ROI calculations. Missing features like school comparison or data updates, but overall solid for a read-only knowledge base.