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Europe/Istanbul clock

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. Changed5 schema fields changed
    • addedInput schema / properties / city
      Added value: +{
      +  "description": "City name for a public weather hint; discarded after the call",
      +  "type": "string"
      +}
    • addedInput schema / properties / feed
      Added value: +{
      +  "description": "Public RSS or Atom URL; titles discarded",
      +  "type": "string"
      +}
    • addedInput schema / properties / path
      Added value: +{
      +  "description": "File path to check; no disk access",
      +  "type": "string"
      +}
    • addedInput schema / properties / query
      Added value: +{
      +  "description": "Search text; discarded after the length check",
      +  "type": "string"
      +}
    • addedInput schema / properties / ref
      Added value: +{
      +  "description": "Git ref name; discarded after the shape check",
      +  "type": "string"
      +}
  2. First observed

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description bears the full transparency burden. It does disclose that the tool performs a network fetch and returns only group counts, but it does not explain timeout behavior, error handling, redirects, or whether 'host' is used to construct the robots.txt URL. Basic transparency, but not comprehensive.

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 one sentence with no wasted words. The core action and output limitation are front-loaded, making it immediately scannable.

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?

With no output schema and no annotations, the description should fully specify how to call the tool. It does not explain how the four seemingly unrelated parameters relate to fetching robots.txt, what 'group counts' means, or what happens when robots.txt is missing or invalid. The description is too sparse for reliable invocation.

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

Parameters2/5

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

Schema coverage is 100%, giving a baseline of 3, but the description adds no parameter mapping. The schema descriptions for 'url', 'json', and 'zone' align with sibling tools (normalize/cite, validate JSON, timezone) rather than with fetching robots.txt, leaving the agent unable to determine which parameter supplies the target. This mismatch warrants a below-baseline score.

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

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Fetch'), a clear resource ('public robots.txt'), and an explicit output restriction ('return group counts only'). This distinguishes it from unrelated siblings like normalize-url or validate-json despite the tool's generic input schema.

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?

No guidance is provided on when to use this tool versus alternatives, no prerequisites are mentioned, and there are no exclusions or mentions of when not to use it. The 'group counts only' caveat hints at a limited use case but is not enough to route an agent.

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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