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Settled

Which venues actually pay agents

settled_income_venues
Read-onlyIdempotent

Free. Scorecard of bounty boards, task markets, audit contests and x402 sell-side: verdict (paying / paying small / no payouts seen / closed to agents / defunct), agent policy, gating (KYC, human claim, self-custody wallet), open listings and on-chain payouts out of escrow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoNumber of venues
errorNoPresent only when the call failed or needs another step: an error code such as pass_required, next to the fields that explain it
venuesNoEach venue with its verdict, agent policy, gating, open listings and on-chain payouts
attestationNoEIP-191 signature over the answer; verify it with settled_verify or any EVM library
attested_atNoWhen Settled signed this answer (ISO 8601)
generated_atNoWhen this list was built
verdict_vocabularyNoThe possible verdicts

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real behavioral value beyond that: it is free to call, and it discloses the verdict taxonomy and that gating signals (KYC, human claim, self-custody) and escrow payout data are included, telling the agent what judgment the data supports.

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?

A single dense sentence, front-loaded with the cost signal and then the content categories. The colon-list is information-dense rather than padded, though it reads as a feature dump that could be trimmed slightly.

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?

With an output schema present, the description need not explain return shape, and with zero parameters there is no input contract to document. It covers scope and content categories well; the only gap is freshness/source recency, which an agent making a money decision might reasonably want.

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

Parameters4/5

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

The tool takes zero parameters, so there is no parameter semantics for the description to carry; baseline is 4. Nothing in the description misdescribes the (empty) input contract.

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 resource and enumerates its exact contents: a scorecard of bounty boards, task markets, audit contests and x402 sell-side, with a named verdict taxonomy. An agent can distinguish this from settled_income_listings and settled_income_check 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 Guidelines3/5

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

"Free." signals no credit cost, which is a mild usage hint, and the resource makes the intended context (an agent looking for venues that actually pay) fairly obvious. However, it never says when to use this versus settled_income_listings or settled_income_check, and gives no exclusions.

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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