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AI Web Research & Research Brief Agent

industrial_platform/research-brief-agent

industrial_platform--research-brief-agent
Destructive

This tool calls the Actor "industrial_platform/research-brief-agent" and retrieves its output results. Actor description: Cited multi-source web research and synthesis. Price: $1.99 per completed brief.

This tool requires an x402 payment. Include a valid x402 payment signature in the request metadata (_meta["x402/payment"]). Your MCP client must support the x402 payment protocol.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contextNoOptional decision context, constraints, audience, or background that should shape the research.
waitSecsNoMax seconds (0–45, default 30) to cap the wait for the Actor run to reach terminal state. For long-running Actors the response returns at the cap with the current run status; follow `nextStep` to poll via get-actor-run. Set to 0 to fire-and-forget.
requirementsNoOptional output and evidence requirements such as comparison criteria, source preferences, tables, calculations, citations, or unresolved-fact handling.
research_questionYes**REQUIRED** REQUIRED. The current multi-source research question to investigate. Use a specific question that needs web research, comparison, verification, citations, or synthesis. Example values: "What are the current official Model Context Protocol transport options in the latest specification?"

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

With annotations already declaring openWorldHint and destructiveHint, the description still adds material behavior: it requires an x402 payment, costs $1.99 per completed brief, and specifies the exact metadata key (_meta["x402/payment"]) plus the client-support prerequisite. That is real operational disclosure beyond the structured annotations. It stops short of describing failure modes or the wait/poll tradeoff (which the schema covers).

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 short sentences, each carrying load: purpose, price, and the payment prerequisite with its exact key. Slight boilerplate in the opening 'This tool calls the Actor...' sentence, but no padding or repetition.

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?

An output schema exists, so return values need no explanation, and the schema also handles wait behavior and polling guidance. The description covers the one thing structured fields cannot: the mandatory payment flow and its cost. Only the absence of any usage/routing guidance keeps it from being fully complete.

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 fully documents research_question, context, requirements, and waitSecs, including defaults and the fire-and-forget option. The description adds no parameter-level syntax or semantics beyond that, so baseline 3 applies.

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 names the concrete action (calls the Actor and retrieves its output) and the embedded Actor description pins down the actual purpose: 'Cited multi-source web research and synthesis,' i.e. producing a source-backed research brief. The first sentence is somewhat tautological since the Actor name equals the tool name, but the appended Actor description rescues the purpose. Siblings are unrelated run/dataset utilities, so differentiation is implicit.

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 gives no when-to-use vs when-not guidance and names no alternative tool. The only usage steer ('use a specific question that needs web research...') lives in the input schema, not the description. An agent gets pricing context but no routing logic.

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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