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web_task_start

Starts a research task: a question answered by reading public pages, with sources, progress and cost. Requires an API key and credits. The maximum budget is reserved, actual execution cost is charged, and unused credits are released. Returns a task id: check it with web_task_status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoOnly research is available: read public pages and answer.research
taskYesWhat to find out, in plain words. Be specific about what to compare.
urlsNoPages to read first, up to 5. Public http or https urls only.
limitsNoBounds on cost, time and steps.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / limits / properties / max_cost_usd / description
      Previous value: -"Most the task may cost, in USD. Execution budget. Free over MCP; charged as a fixed package over HTTP/x402. No automatic on-chain refund."New value: +"Most the task may cost, in USD. Execution budget. Reserved against account credits over MCP/HTTP with an API key; charged as a fixed package over HTTP/x402. No automatic on-chain refund."
  2. Changed1 schema field changed
    • changedInput schema / properties / limits / properties / max_cost_usd / description
      Previous value: -"Most the task may cost, in USD. Reserved up front; the rest is returned."New value: +"Most the task may cost, in USD. Execution budget. Free over MCP; charged as a fixed package over HTTP/x402. No automatic on-chain refund."
  3. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare non-read-only, open-world, non-idempotent behaviour, so the bar is lower; the description still adds real value by disclosing the credit model: max budget reserved up front, actual cost charged, unused credits released. It doesn't flag that this is asynchronous with no on-chain refund, though the schema's max_cost_usd note covers the transport nuance.

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, front-loaded with the purpose, then prerequisites, then billing and the return handle. No filler and nothing repeated from the 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, and the description compensates by stating the return value (a task id) and where to check it (web_task_status), along with cost and auth expectations. For an async, credit-consuming tool this covers everything an agent needs before invoking.

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% and each parameter (task, urls, mode, limits) is already documented with constraints and defaults. The description's budget-reservation sentence touches max_cost_usd but adds no syntax or constraint detail beyond what the schema states, 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?

States a specific verb and resource ('Starts a research task') and immediately defines the scope: a question answered by reading public pages, returning sources, progress and cost. This separates it from web_scrape, web_crawl and web_search_exa, which an agent can rule out without opening a 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?

Gives the operative context (a question to be answered from public pages) and an explicit prerequisite (API key and credits), plus routes follow-up to web_task_status. It stops short of saying when to prefer this over web_act or a plain scrape, so the exclusion side is inferred rather than stated.

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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