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Glama

1cent Web Intelligence for AI Agents

Url Performance

web.url.performance
Read-onlyIdempotent

Return safe network timing, payload and cacheability diagnostics. Use only for public HTTP(S) resources; it does not execute JavaScript or bypass access controls. Pass url as an absolute public HTTP(S) URL. Keep fresh=false to allow cache reuse; set fresh=true only when a new upstream fetch is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAbsolute public HTTP or HTTPS URL to inspect. Private, loopback, link-local, metadata-service and otherwise SSRF-sensitive destinations are rejected.
freshNoSet true only when a new upstream fetch is required; false allows the bounded cached result and is cheaper for the origin.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
toolYes
qualityNo
url_finalYes
checked_atYes
from_cacheYes
request_idYes
content_hashYes
url_requestedYes

Schema Changelog

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

  1. Added

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavioral context beyond that: it explicitly states the tool is safe, does not execute JS, does not bypass access controls, and explains cache-reuse behavior and the fresh parameter's impact. No contradiction with annotations.

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?

Three sentences, information-dense and front-loaded with the core purpose, followed by constraints and parameter guidance. No filler or redundant repetition of schema content; every sentence earns its place.

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

Completeness5/5

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

For a two-parameter tool with a comprehensive schema and rich annotations, the description covers the essential operational context: what it returns, safety constraints, and parameter usage. An output schema exists, so return format details are not required here. The description is sufficient for correct selection and invocation.

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

Parameters4/5

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

Schema coverage is 100%, with descriptions for both `url` and `fresh`, so baseline is 3. The description adds extra nuance by reinforcing that `url` must be an absolute public HTTP(S) URL and by explaining the trade-off for `fresh` (cache reuse vs. new upstream fetch), which enhances understanding beyond schema alone.

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 opens with a specific verb ('Return') and resource ('network timing, payload and cacheability diagnostics'), clearly stating what the tool does. It distinguishes itself from siblings like web.url.timing by emphasizing cacheability and payload diagnostics, making its unique scope evident.

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

Usage Guidelines5/5

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

It gives explicit usage constraints: 'Use only for public HTTP(S) resources' and states the tool 'does not execute JavaScript or bypass access controls.' It also provides direct guidance on the `fresh` parameter, specifying when to set it true vs. false, which is actionable and clear.

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

A4.4/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlap exists among text extraction tools (url_extract, url_text, url_markdown, url_rag_chunks). Descriptions help differentiate them, so disambiguation is mostly clear.

Naming Consistency5/5

All tools follow a consistent prefix (catalog_, demo_, site_, url_) and use lowercase snake_case with descriptive names. Conventions are uniform throughout.

Tool Count5/5

35 tools cover a comprehensive range of URL and site analysis functions without feeling bloated. Each tool serves a specific purpose, and the count is appropriate for the server's scope.

Completeness5/5

The tool set covers all major aspects of URL analysis: health, content, metadata, change detection, site discovery, and security. No obvious gaps for the stated domain.

Resources