text_classifySort text into one of the labels you give, with a confidence. For routing, triage and moderation. Capped at 30,000 characters
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to sort | |
| labels | Yes | Comma-separated labels to choose between |
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 description discloses some behavioral aspects: it returns a confidence and has a 30,000-character cap. Since there are no other annotations besides the title, the description carries the burden of transparency. It does not describe the return format in detail (e.g., how labels are returned, whether the label is a string or object) or error handling for over-length input, leaving some gaps.
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 exceptionally concise: two sentences that front-load the action, specify inputs, list use cases, and set a size limit. Every word adds value 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?
For a simple classification tool with no output schema, the description covers the key aspects: action, inputs, output (label with confidence), use cases, and a size limitation. It misses some details like output format and over-limit behavior, but these are relatively minor given the tool's simplicity.
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?
The schema fully describes both parameters (text and labels) with 100% coverage. The description adds minimal extra meaning, mainly reinforcing that labels are provided by the user. It does not enrich parameter understanding beyond the schema, so the baseline score of 3 is appropriate.
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 action (sort/classify), the resource (text), and the expected output (a label with confidence). It also names concrete use cases (routing, triage, moderation), which distinguishes it from sibling text tools like text_extract, text_summarise, and text_translate.
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 provides explicit use cases (routing, triage, moderation), indicating when the tool is appropriate. It also mentions a character limit (30,000), which suggests a constraint. However, it does not explicitly mention when not to use it or name alternative tools.
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.
Every tool is prefixed with a clear domain (e.g., apps_, blog_, transit_), and the suffix identifies a distinct action or resource. Overlapping tools like archive_search and news_search are explicitly differentiated in their descriptions.
All tools consistently use a domain_prefix_suffix pattern, but the suffix is sometimes a verb (create, list, search) and sometimes a noun (inbox, status, address). This minor mixing prevents a perfect score but remains predictable and readable.
With 113 tools, the count is far beyond the typical well-scoped range, even for a broad personal assistant. While each tool is distinct and serves a purpose, the sheer number is overwhelming and could be better organized into separate domain-specific servers.
Each domain has near-complete lifecycle coverage, including CRUD and search where relevant, with only minor gaps such as missing apps_delete or events_update. The wide range of covered domains itself demonstrates strong completeness for a general assistant.