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What Agents Buy

by com.whatagentsbuy

The leaderboard: biggest, or most real

rank_sellers

USE WHEN you want a ranked list of sellers across the market. by='revenue' ranks by raw USDC received (who is busy); by='real_demand' ranks by Organic Demand Score (whose money comes from many independent wallets rather than one wallet supplying almost all of it). The two disagree often, and the disagreement is the point. For accuracy ranking within an objective category, use rank_by_accuracy. (Formerly named top_services.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
byNorevenue
limitNo

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are present, so the description carries the full burden of explaining behavior. It does meaningfully explain how each ranking mode is computed and highlights that revenue and real_demand intentionally disagree. It stops short of stating output ordering, pagination, or read-only guarantees, but for a ranking tool the behavioral core is well covered.

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?

Every sentence earns its place: the trigger phrase, metric definitions, the caveat about disagreement, and the sibling routing. The content is front-loaded and there is no filler.

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 a two-parameter ranking tool with no output schema, the description is nearly complete. It explains the metrics, differentiates the tool from its closest sibling, and notes the legacy name. It does not describe the return format or explicitly state ordering, though 'leaderboard' and 'ranks' imply descending order.

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?

Schema description coverage is 0%, but the description adds rich semantics for the 'by' enum, explaining exactly what revenue and real_demand measure and why they differ. The 'limit' parameter receives no extra explanation, but its meaning is already clear from the schema's name, default, minimum, and maximum.

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?

The description opens with a clear verb and resource: 'ranked list of sellers across the market.' It also distinguishes this tool from rank_by_accuracy by explicitly stating the accuracy-ranking alternative, so an agent can tell them apart without reading the schema.

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

Usage Guidelines5/5

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

The description begins with 'USE WHEN' and explains the two ranking modes with concrete definitions: revenue means raw USDC received, real_demand means organic demand from independent wallets. It also gives an explicit exclusion: for accuracy ranking within a category, use rank_by_accuracy.

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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TDQS

A3.9/5.0
Disambiguation4/5

Each tool has a reasonably distinct role: finding an API, inspecting one seller, preflighting it, searching the ledger, ranking sellers, and reading aggregate market data. The closest pairs are find_api/search_services and market_pulse/market_summary, but the descriptions call out these differences explicitly, so an agent should rarely choose the wrong one.

Naming Consistency3/5

All names use snake_case and are readable, but they do not follow one clear convention. find_api, get_service, list_traps, and search_services are verb_noun, while market_pulse, market_summary, most_accurate, preflight, and top_services are noun phrases or standalone descriptors. The naming style is coherent enough, but inconsistent verb/noun usage lowers the score.

Tool Count5/5

Nine tools is well-scoped for this server's purpose: it needs to cover discovery, seller inspection, ranking, preflight checks, search, and market intelligence. The count feels deliberate rather than bloated, and each tool has a distinct niche.

Completeness4/5

The server covers the full research side well: find candidates, inspect sellers, check safety with preflight, search recorded grades, compare top sellers, and understand market activity. The main gap is that no tool actually completes or confirms a payment, but the descriptions suggest payment is intentionally left to the agent's own x402 signing flow.

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