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cpu_get_markets

Scout the marketplace to compare hubs by resource availability, prices, distances, and sale fees. Filter by hub or resource for targeted searches.

Instructions

Scout the marketplace: one compact row per (Hub, resource) with open-vs-incoming lot counts, lowest price, distance, and the hub's live sale-fee percent for that resource (liveSaleFeePercent, enriched from the local world map — advisory, may trail the chain; null when the rate is unknown, i.e. the map has no read on the hub or it isn't serving sale fees yet). The recommended first look at what is for sale and where — compare hubs by fee in one call, then drill into specific lots with cpu_list_lots. Public read; supports hub / resourceId filters and an optional zone (aroundTokenId + radius in grid steps).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hubNoFilter to a Hub by its cell token id.
radiusNoZone radius in grid steps around aroundTokenId (server clamps to 50).
resourceIdNoFilter by resource id.
aroundTokenIdNoZone anchor as a cell token id.
Behavior5/5

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

With no annotations, the description fully discloses behavior: public read, filters, zone, and limits of liveSaleFeePercent (may trail, null when unknown). No contradictions.

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 adds value; it is compact yet comprehensive, with no redundancy, earning its length.

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?

No output schema, but description specifies return structure: one row per (Hub, resource) with counts, price, distance, fee. Covers filters, zone, and data caveats, making it fully adequate for a first-look tool.

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?

Despite 100% schema coverage, the description adds meaning by explaining hub and resourceId as filters, zone as aroundTokenId + radius, and the advisory nature of liveSaleFeePercent, surpassing baseline.

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 clearly states the tool scours the marketplace with specific fields per (Hub, resource) and distinguishes from sibling cpu_list_lots, fulfilling the 'specific verb+resource' criterion.

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?

Explicitly says 'The recommended first look at what is for sale and where' and directs to drill into lots with cpu_list_lots, providing when-to-use and alternative.

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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