Show how this request is classified. No identifiers are retained.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
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?
The privacy note 'No identifiers are retained' adds some transparency, but the description does not disclose whether the tool has side effects, what it returns, or how it behaves beyond classification. No annotations compensate for this lack of detail.
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 very short and free of unnecessary detail, which is concise. However, the brevity contributes to vagueness, so it does not fully earn a top score.
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 vague description and lack of output schema, the tool's purpose, behavior, and expected result are not sufficiently explained. More context is needed for an agent to know when and how 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?
Each parameter has a schema-level description, but the overall description does not explain how the parameters relate to the classification logic. The parameter descriptions are present but add little semantic context beyond their names.
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 'Show how this request is classified' is vague and does not specify what kind of classification is performed or what the tool actually does. It also does not distinguish this tool from siblings like validate-json or normalize-url.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or conditions under which this tool should be selected.
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 unique, well-defined purpose with no overlapping functionality. For example, 'normalize-url' and 'validate-json' address distinct concerns, and time-related tools are clearly separated.
Tool names follow a mix of conventions: some are verb-object (normalize-url, validate-json, inspect-robots), while others are noun phrases (citation, compatibility, timezone). This inconsistency makes the naming pattern less predictable.
With 11 tools, the count is reasonable and not excessive. Each tool covers a separate utility, though a few could arguably be merged (e.g., timezone and utc-time), but the number is still within a sensible range.
The server name 'Language ja' suggests a language-related domain, yet the tools cover miscellaneous web utilities (URL handling, HTTP status, time, JSON). This mismatch and lack of a cohesive domain make the surface feel incomplete for any specific purpose.