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Glama

web_site_search

Read-only

Search a single site via its own search box to learn the URL pattern for direct queries, enabling later plain web fetches without a browser or crawl.

Instructions

Search one site through its own search box and learn the URL pattern the form produces. Use for shops, job boards and docs whose content only appears when asked for: a crawl reaches only what is linked, and web_search covers the whole web, not one site. Returns results_url, the pattern (/search?q=...) that makes every later query a plain web_fetch with no browser, plus the first results while fetch is true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAny page of the site — usually the home page. Its search box is what gets used.
fetchNoFetch the results too, rather than only reporting the pattern. Default true.
queryYesWhat to search for.
timeoutNoTimeout in ms. Default 60000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.3

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover safety (readOnlyHint, openWorldHint), and the description adds real behavioral value: it discloses the return shape (results_url plus the /search?q=... pattern) and the downstream consequence that later queries become plain web_fetch calls with no browser. It stops short of failure modes, timeouts, or what happens when a site has no usable search box.

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?

Three dense sentences, front-loaded with purpose then alternatives then return value; the middle sentence carries the most weight but is somewhat listy ('shops, job boards and docs'). No filler sentences, though it is close to overpacked for a tool with a four-field schema.

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?

There is no output schema, so the description must carry the return contract — and it does, naming results_url, the pattern, and the conditionally returned first results. Combined with annotations and a fully documented schema, an agent has everything needed to call this correctly.

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%, so baseline is 3, but the description adds meaning: it explains that `url` is 'any page of the site' and ties `fetch` to a concrete outcome ('the first results while fetch is true'), clarifying what the flag buys rather than just restating its default.

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?

States a specific verb (search) and resource (one site, via its own search box) and explicitly separates itself from two siblings: web_crawl ('a crawl reaches only what is linked') and web_search ('covers the whole web, not one site'). An agent can route correctly without opening any schema.

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?

Gives an explicit when-to-use profile ('shops, job boards and docs whose content only appears when asked for') and names the two competing alternatives with the condition that disqualifies each. Nothing is left to inference.

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