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Task Agent with Tools (AI)

agent_run
Read-only

Hand off a whole research or lookup task in one call: a Claude Haiku 5.5 agent plans the steps, calls up to 38 agentsvc.io tools in parallel (web and news search, page reading, papers, GitHub and npm, company registers and sanctions, crypto prices, token checks, DeFi TVL and yields, wallets, FX and macro data, weather, DNS, WHOIS, SSL, CVEs) and returns a Markdown answer with sources and the list of tool calls it made. Up to 12 steps and about 90 seconds. Read only: it cannot spend money or send anything. Example: compare two DeFi protocols, check a company and its domain, or summarize what changed this week on a topic. AI-written, check the sources. Price: $0.5 USDC per call, paid inside this MCP call via x402 (USDC on Base, Solana, Polygon or Arbitrum). x402 MCP clients such as @x402/mcp pay automatically. Free sample: call with the example input {"task":"What is the TVL of Aave and Morpho right now? Answer in two sentences.","max_steps":4}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesWhat to find out or do, in plain words, max 4000 characters
max_stepsNoUpper limit of model rounds

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnly/openWorld/non-destructive, and the description substantially extends them: 38 tools, 12-step and ~90s limits, explicit 'cannot spend money or send anything', 'AI-written, check the sources', and the x402 USDC pricing/payment mechanics with supported chains. This is rich behavioral context an agent cannot get from annotations alone.

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?

Core purpose and capability list are front-loaded in the first sentence, so it is well-structured despite being long. Pricing, example, and free-sample details are useful but the passage is dense enough that the payment paragraph could be tighter.

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 complex, open-world orchestrator with no output schema, the description covers what it returns (Markdown answer with sources and the tool-call list), its limits, safety profile, cost, and payment path. Nothing an agent needs to invoke it correctly appears to be missing.

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 coverage is 100% and both parameters are fully described in the schema, so the baseline is 3. The description adds light framing (the 'Up to 12 steps' cap and the sample max_steps:4), but no syntax or semantic detail beyond the schema.

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+resource (hand off a whole research/lookup task) and enumerates the concrete capability envelope (planning, parallel tool calls, Markdown answer with sources). It is clearly distinguishable from the single-purpose siblings like web_search or research_report because it describes orchestrating up to 38 tools across many domains.

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 concrete use examples (compare two DeFi protocols, check a company and its domain, summarize a week's changes) and a free sample input, which tells the agent when a multi-step task is worth one call. It does not, however, explicitly name the alternatives (e.g. web_search, answer_with_sources, research_report) or state when to prefer those instead, so routing against siblings 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.

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