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List a page's XHR/fetch calls, then return a matching response body to extract real API data, field names, and paging without guessing endpoints.

Instructions

START HERE when you need DATA rather than an action. Lists the XHR/fetch calls the page made, then returns one response body via body:"<url fragment>". Real field names, real numbers, paging as a parameter. Add reload:true if nothing was captured yet. Never guess an endpoint name from memory — list first, pick by response size. One page's API messy? Another page on the same site often exposes the same data cleanly.

Input Schema

NameRequiredDescriptionDefault
bodyNoReturn the full response body of the latest request matching this URL fragment.
indexNoWith `body`: which match, counting back from the newest. 0 = latest (default), 1 = one before it. Paged endpoints differ only by a cursor, so walk this to collect every batch.
matchNoOnly list requests whose URL contains this.
tabIdNoTarget tab id. Omit to use the active controlled tab.
reloadNoReload the page first to capture requests made during load.
maxBodyNoTruncate the body at this many chars. Default 120000.
spaceIdNoPin this command to an owned BeatBrowser TaskSpace. Also pass its tabId.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.1

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does reasonably well: it discloses that only requests the page already made are listed, that a reload is needed to capture load-time requests, that results are matched by URL fragment, and that paging is done via a parameter. It omits permission/auth requirements and whether captured bodies persist across navigations, which a mutation-free data tool arguably should note.

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?

It is front-loaded with the decisive instruction ("START HERE...") and every sentence except the final heuristic ("One page's API messy? Another page on the same site...") carries actionable guidance. It runs slightly long and is written in a conversational register, but there is little dead weight.

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

Completeness4/5

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

For a 7-parameter, annotation-free tool with no output schema, the description covers purpose, workflow ordering, capture timing, and paging well enough to invoke correctly. The remaining gap is the absence of any detail on permissions, failure modes, or the shape of the returned list beyond 'the XHR/fetch calls the page made'.

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 schema already documents every parameter including body, index, match, reload and maxBody. The description's mentions of body/"<url fragment>" and "paging as a parameter" largely restate what the schema says, adding only mild emphasis rather than new semantics, so the baseline 3 applies.

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 verb and resource: it 'Lists the XHR/fetch calls the page made' and can return 'one response body' via a URL fragment. The opening "START HERE when you need DATA rather than an action" cleanly separates it from the action-oriented siblings (click, type, navigate), so an agent can classify it without opening the schema.

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

Usage Guidelines4/5

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

It gives real when-to-use guidance ("when you need DATA rather than an action", "Add reload:true if nothing was captured yet") and a workflow rule ("Never guess an endpoint name from memory — list first"). It stops short of naming a concrete alternative tool for the case where this tool isn't right, so it is clear context rather than full when-not routing.

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