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?
There are no annotations, so the description bears the full burden of behavioral disclosure. It does reveal that the tool returns 'group counts only,' which is useful, but it fails to explain failure modes, whether authentication is ever needed, how redirects or missing robots.txt files are handled, or why parameters like 'json' and 'zone' exist. The schema-description mismatch also obscures actual behavior.
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 a single tight sentence with no filler, and the key output constraint ('group counts only') is front and center. It loses a point because the extreme brevity leaves critical invocation and parameter details unstated.
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?
There is no output schema and no annotations, so the description must carry more weight. It does not explain what 'group counts' means, how results are returned, which parameter supplies the robots.txt URL, or how the four schema parameters relate to the tool. The tool is not adequately self-contained for an agent to invoke 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 100%, which normally earns a baseline of 3, but the parameter descriptions do not align with the stated purpose. For example, 'url' is described as 'HTTPS URL to normalize or cite' rather than as a URL to fetch robots.txt from, and 'json' and 'zone' appear entirely unrelated. An agent cannot confidently determine which parameters to populate when invoking this tool.
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 states a specific verb and resource: 'Fetch a public robots.txt and return group counts only.' This clearly identifies the tool's core action and output scope, and distinguishes it from sibling utilities like normalize-url or validate-json. However, the input schema parameters are described in unrelated terms (normalize, cite, validate, timezone), which somewhat muddies the clarity.
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?
There is no guidance about when to use this tool versus alternatives, and no mention of prerequisites or exclusions. The word 'public' implies a constraint, but the description does not explain when this tool is preferred over related siblings or what conditions make it inappropriate.
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.
Several URL-focused tools (citation, normalize-url, domain-shape) overlap in what they inspect, though their descriptions do specify different outputs. compatibility and sha256-ok are vague, but most other tools have clearly separate jobs.
All names use lowercase hyphenation, but they mix verb-object names (normalize-url, inspect-robots, validate-json) with noun-only or noun-noun names (citation, timezone, status-catalog, iana-zones). This is readable but gives agents no reliable pattern for predicting tool names.
Eleven tools is within a reasonable size for a general-purpose privacy-safe utility server, and no tool is an exact duplicate. The set could be tightened around a single domain, but the count itself is not excessive.
The server's domain is too broad and unfocused to define a complete workflow: URL inspection lacks redirect/header coverage, timezone handling lacks conversions, and JSON/hash tools are single-purpose checks. As a result, agents will likely need tools outside this server for related operations.