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alpha_get_orderbook

Fetch and merge all four sides of an Algorand blockchain orderbook into a unified YES-perspective view, including spread calculation for market analysis.

Instructions

Fetch the on-chain orderbook as a unified YES-perspective view. Merges all 4 sides (YES bids/asks + NO bids/asks). Includes spread calculation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marketAppIdYesThe market app ID
networkNoAlgorand network to use (default: mainnet)
itemsPerPageNoNumber of items per page for paginated responses (default: 10)
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches and merges data, implying a read-only operation, but doesn't address critical aspects like rate limits, authentication requirements, error handling, or the format of the returned data. The mention of 'paginated responses' in the schema hints at behavior, but the description doesn't elaborate on this.

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?

The description is extremely concise and front-loaded, consisting of just two sentences that directly convey the tool's purpose and key features. Every word earns its place, with no redundant or vague language.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of fetching and merging orderbook data, the lack of annotations, and no output schema, the description is incomplete. It doesn't explain the structure of the returned data, how the merging works, what 'YES-perspective view' means, or how the spread calculation is performed. This leaves significant gaps for an agent to understand the tool's behavior fully.

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?

The schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional meaning about the parameters beyond what the schema provides, such as explaining the significance of 'marketAppId' or the implications of network choice. However, it doesn't contradict the schema, so the baseline score of 3 is appropriate.

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 specific action ('Fetch'), the resource ('on-chain orderbook'), and the distinctive transformation ('unified YES-perspective view'). It explicitly distinguishes this tool from siblings by mentioning the merging of all 4 sides and spread calculation, which no other tool in the list addresses.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. While it mentions the unified view, it doesn't specify scenarios where this is preferred over other order-related tools like alpha_get_open_orders or alpha_get_market, nor does it mention prerequisites or 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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