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Agent Data Marketplace

by io.github.wabarakat
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request_data

Request data from the marketplace. Nothing is charged; the request is queued.

Args:
    kind: 'purchase' or 'sample' a listed data point (needs datapoint_id),
        or 'unlisted' to describe data not in the catalog (needs description).
    datapoint_id: Id from search_datapoints.
    description: What you need and what it is for.
    format: Preferred format, e.g. json, csv, parquet.
    frequency: e.g. once, hourly, daily.
    max_price_credits: Most you would pay, in credits (1 credit = $0.01).
    agent_name: A stable name for your agent, so repeat requests are grouped.
    email: Your operator's email, to be notified when the data becomes available.

Input Schema

NameRequiredDescriptionDefault
kindYes
emailNo
formatNo
frequencyNo
agent_nameNo
descriptionNo
datapoint_idNo
max_price_creditsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose the two behaviors that matter most: no charge is incurred and the request is asynchronous ('queued'). It also hints at deduplication via agent_name grouping repeat requests. It stops short of stating what is returned on submission or how long queueing takes.

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?

The lead sentence front-loads the two facts an agent most needs, followed by a compact one-line-per-parameter list with no filler. The Args enumeration is slightly mechanical but every line adds information not present in the schema.

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 an 8-parameter, no-output-schema, no-annotation mutation tool, the description covers the parameters and the key async/no-charge behavior. The main omission is what an agent should do after submitting (retrieve via get_request_status) and whether a request id comes back.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, and it does: every one of the 8 parameters gets meaning, including the conditional requirements of kind, the units for max_price_credits (1 credit = $0.01), and the purpose of agent_name and email.

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?

States a specific verb and resource ('Request data from the marketplace') and immediately clarifies the operation's nature ('Nothing is charged; the request is queued'). It does not explicitly contrast itself with sibling request_service, but the framing around listed datapoints makes the domain clear enough.

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

Usage Guidelines3/5

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

Usage is implied through the kind enum semantics (purchase/sample need datapoint_id, unlisted needs description) and it points to search_datapoints as the source of ids. However, it never says when to prefer this over request_service, or that get_request_status is how you follow up on a queued request.

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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