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YAML validity, body discarded

inspect-robots

Fetch a public robots.txt and return group counts only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the burden of disclosing behavior. It states that the tool fetches a public robots.txt and returns only group counts, which covers the core read-only network behavior. It does not disclose failure modes, whether full content is discarded, or any rate-limit/auth considerations, but it is minimally transparent for a simple public fetch operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that is compact and free of filler. It communicates the core action and the output limitation in minimal words, earning high marks for conciseness without losing meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 9 optional parameters, no output schema, and no annotations, yet the description does not explain which parameter to use, what shape the input should take, or what the group-count return means. An agent is left to guess between url, host, and others. The description is too lean for this level of ambiguity and provides insufficient context for a reliable call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description does not add meaning beyond the schema, and notably it does not clarify which of the nine optional parameters supplies the robots.txt URL or hostname. Still, the schema already describes each parameter individually; no contradiction or lost meaning attributable to the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 restricts the result to 'group counts only.' This makes the purpose clear and differentiates it from sibling fetch tools like web-fetch, which would return full content. However, it does not explicitly name a sibling or contrast itself in the description, so it stops short of the strongest clarity level.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no explicit guidance on when to use this tool versus alternatives such as web-fetch, fetch-status, or normalize-url. It only implies the use case through 'group counts only,' but provides no exclusions or routing hints. An agent gets no context on when this tool is preferred.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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