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resolve_data_need

End-to-end selection: describe a task, get back the single best service to pay (plus ranked alternatives and any services to avoid). Use this before spending money over x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYesThe task, e.g. "get current weather for Singapore"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the output shape (best pick, ranked alternatives, avoid list), which tells the agent this is a recommendation/decision step. It does not say whether the call itself costs anything, whether it is read-only, or how it behaves with ambiguous tasks.

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?

Two compact sentences, front-loaded with the core value ('describe a task, get back the single best service') and finished with the usage cue. Every clause earns its place and nothing is repeated.

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?

There is no output schema, so the description compensates by summarizing the return (best service, ranked alternatives, avoid list). For a single-parameter decision tool that is close to sufficient; only cost/latency or ambiguity-handling details are 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 the single 'task' parameter already carries an example, so the schema does the heavy lifting. The description adds nothing to parameter semantics beyond implying that the task string drives the selection. Baseline 3 is appropriate for a one-param tool with full schema coverage.

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 a specific verb+resource ('selection', 'describe a task') and states the concrete deliverable: the single best service to pay, ranked alternatives, and services to avoid. It is clear about what the tool returns, but it never mentions the sibling tools (find_service, check_trust, get_verified_data), so an agent must infer how it differs from find_service on its own.

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 a concrete trigger: 'Use this before spending money over x402.' That is a real when-to-use signal rather than vague context. However, it offers no exclusions and does not name an alternative tool for cases where the agent just wants to browse or check trust instead.

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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