Find Indian-American education & tutoring (heritage/language schools, Bal Vihar, coaching).
Provide a point (`lat`+`lng`, optional `radius_miles`) or `city`/`state`. Filter by `tag`
(e.g. "language_school", "heritage", "tutoring").
| Name | Required | Description | Default |
|---|---|---|---|
| lat | No | ||
| lng | No | ||
| tag | No | ||
| city | No | ||
| limit | No | ||
| state | No | ||
| offset | No | ||
| open_now | No | ||
| radius_miles | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / offsetAdded value: +{
+ "default": 0,
+ "title": "Offset",
+ "type": "integer"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It explains that the tool returns results based on location and tag, but does not disclose pagination (limit, offset), the open_now filter, or the default radius of 25 miles. More detail on the response format would improve transparency.
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?
The description is two sentences long, with the first sentence immediately stating the purpose. Every word adds value, and the structure is efficient with no redundancy.
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?
Given the 9 parameters, no annotations, and the presence of an output schema, the description covers the core usage (location and tag) but omits description of limit, offset, and open_now. The output schema may compensate for return values, but the input guidance could be more thorough.
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 0%, so the description must add meaning. It explains that lat+lng and radius_miles form a point, and city/state are alternatives, and tag filters by category. However, it omits limit, offset, and open_now, which are part of the schema. The guidance is helpful but incomplete.
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?
The description clearly states the tool finds Indian-American education & tutoring resources, listing specific types like heritage/language schools, Bal Vihar, and coaching. This distinguishes it from sibling tools like get_education_details (which likely retrieves a single entity) and other category search tools.
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?
The description tells when to use the tool (e.g., by location or city/state) and how to filter by tag. It does not explicitly state when not to use it or mention alternatives, but the context is clear enough for selecting this over get_education_details.
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.