Add
addAdds two numbers and returns the sum.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes |
addAdds two numbers and returns the sum.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | ||
| b | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the operation and return value, making the pure-function behavior clear. There are no side effects or edge cases mentioned, but for a simple arithmetic tool this is sufficient.
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?
A single, front-loaded sentence with no wasted words. Every part of the description earns its place.
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 two-parameter numeric addition tool with no output schema, the description fully covers what the tool does and what it returns. No critical information is missing 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.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description's 'two numbers' directly maps to the a and b parameters. Since addition is commutative, parameter order is irrelevant, so the description adequately compensates for missing schema documentation.
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 'Adds two numbers and returns the sum' uses a specific verb and resource, and clearly differentiates from sibling tools like echo and server_time. There is no ambiguity about what the tool does.
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 implies usage (when you need to add two numbers) but provides no explicit guidance about when to prefer this tool over siblings. No exclusionary or comparative context is given.
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 performs a completely distinct action: arithmetic, text echoing, and time retrieval. There is no realistic overlap or ambiguity between them.
add and echo use bare imperative verbs, while server_time is a noun phrase with an underscore. The names are readable, but they do not follow a consistent verb_noun or get_x pattern.
Three tools is not bloated, but the set feels arbitrarily scoped for a server named InferMap. The count is reasonable in isolation but not clearly aligned with any apparent domain or purpose.
The tools share no common domain or workflow, so there is no complete lifecycle or task progression. Despite the server name suggesting mapping or inference, no such operations are present, leaving obvious gaps for any real use.