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Glama

Language zh

inspect-robots

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoHTTPS URL to normalize or cite
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
zoneNoIANA timezone name

Schema Changelog

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

  1. First observed

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a network fetch but doesn't mention error handling, redirects, timeouts, or the exact shape of 'group counts'. It also doesn't clarify whether the operation is read-only, though that is implied. This is a significant transparency gap for a network tool.

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

Conciseness4/5

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

The description is a single, efficient sentence with no wasted words. It front-loads the action and result. However, it is so brief that it omits critical operational details, so while it earns points for conciseness, it's not a 5 due to incompleteness.

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?

This tool involves a network fetch but has no output schema, no annotations, and a confusing parameter set. The description does not explain the return format beyond 'group counts only', nor does it address failure modes or parameter usage. An agent cannot reliably call this tool without additional assumptions, making it inadequate.

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?

The schema has 100% coverage with descriptions, but those descriptions are generic (e.g., 'HTTPS URL to normalize or cite') and do not map to the robots.txt use case. The tool description does not explain which parameter (likely 'url') should be used or how the other parameters (host, json, zone) relate to fetching robots.txt. Thus the description adds no parameter-specific meaning beyond the generic schema.

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 clear action (fetch a public robots.txt) and the specific result (return group counts only). This distinguishes it from sibling tools like normalize-url or validate-json, which operate on different resources. However, it does not explicitly name alternatives or scope exclusions, so it's not a 5.

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 provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites, error conditions, or typical use cases. An agent would have to infer the intended usage from the name alone, which is insufficient.

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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TDQS

C2.4/5.0
Disambiguation3/5

Most tools are clearly distinct, but 'citation' and 'compatibility' have vague descriptions that could overlap with HTTP status handling, and 'status-catalog' adds further potential confusion. URL-related tools are distinguishable but require careful reading.

Naming Consistency4/5

All names consistently use lowercase hyphenated style, but they mix noun phrases like 'timezone' and 'status-catalog' with verb-object forms like 'normalize-url' and 'validate-json'. This is mostly predictable but not perfectly uniform.

Tool Count4/5

With 11 tools, the set is reasonably sized and not overwhelming. Each tool appears to serve a single utility purpose, fitting the apparent web-utility domain.

Completeness4/5

The collection covers common web development utilities: URL handling, HTTP status, time, timezone, JSON validation, robots.txt inspection, and language tags. There are no major dead ends, though the server name 'Language zh' does not strongly align with the broader tool set.