Fetch a public robots.txt and return group counts only.
| 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?
With no annotations, the description carries the full burden of disclosing behavior. It only says 'fetch' and 'return group counts,' with no mention of error handling, missing robots.txt, network failures, rate limits, or whether any side effects occur.
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 main description is a single, tight sentence that wastes no words. However, the parameter block is cluttered with irrelevant descriptions, which slightly harms overall structural clarity.
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?
The tool is not complete enough to use correctly. There is no output schema, yet 'group counts' format is not described. More importantly, the four parameters (url, host, json, zone) have no obvious relationship to the stated purpose, leaving the agent unable to determine how to invoke the tool meaningfully.
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 parameter descriptions are actively misleading. 'url' is described as 'HTTPS URL to normalize or cite,' 'json' as 'JSON text to validate; discarded after the check,' and 'zone' as 'IANA timezone name'—none of these align with fetching a robots.txt file. Only 'host' vaguely relates, but its purpose is not explained.
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 a specific action ('Fetch a public robots.txt') and a precise result ('return group counts only'), making the tool's purpose unambiguous even among unrelated siblings.
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 given about when to use this tool versus alternatives like normalize-url, status-catalog, or validate-json. The description implies use when robots.txt group counts are needed, but it never states conditions, exclusions, or comparisons.
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.
Most tools have distinct purposes, such as byte-count, validate-json, and utc-time. However, citation and normalize-url both handle URLs, and timezone and utc-time both provide time information, which could lead to occasional misselection.
Names are mostly lowercase with hyphens, but the pattern is inconsistent: some are nouns (byte-count, timezone, status-catalog) while others are verbs (inspect-robots, normalize-url, validate-json). There is no clear verb_noun or noun_verb convention across the set.
11 tools is a reasonable count for a utility server covering URLs, time, robots, and data validation. Each tool does something different, though a few are quite trivial, making the set slightly broad but not excessive.
The tools cover several common utility categories like URL normalization, current time, timezone lookup, and JSON validation. However, the scope is broad and shallow, leaving obvious gaps such as domain lookups, HTTP request mechanics, or date formatting, and there is no unifying workflow to judge full coverage.