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player_burn_event_prizes

Retrieve a player's public burn-event prize summary by username without calculating a claimable balance. Makes one GET request and does not auto-fetch continuation pages.

Instructions

Read the public burn-event prize summary for an explicit username without inferring a claimable balance. Makes one logical GET request Does not auto-fetch continuation pages. Required inputs reflect tool policy as well as measured upstream requirements. Other declared filters are forwarded as supplied; their effectiveness is not implied by the schema. Array responses are locally limited to 100 rows and 256 KiB, with truncation reported in text and metadata. Oversized records are refused without partial fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usernameYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.0.5

TDQS

A3.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers rich behavioral detail: single logical GET request, no auto-fetch of continuation pages, array responses locally limited to 100 rows and 256 KiB with truncation reported, oversized records refused without partial fields, and filters forwarded as supplied without implied effectiveness. This is comprehensive transparency for a read operation.

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 description is front-loaded with purpose and then systematically lists behavioral constraints. Each sentence adds a distinct piece of information, though some phrasing like 'Required inputs reflect tool policy as well as measured upstream requirements' is slightly verbose. Overall efficient and well-structured.

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 simple read tool with one parameter and no output schema, the description covers return limitations (row/size caps, truncation reporting) and pagination behavior. It does not detail the structure or fields of the prize summary, but that is likely inferable from the tool name and output schema absence.

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

Parameters2/5

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

Schema coverage is 0% for the single required parameter 'username'. The description only says 'explicit username' without adding format, constraints, examples, or validation rules beyond what the schema already provides (a non-empty string). With low coverage, the description fails to compensate.

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?

The description states a specific verb ('Read') and resource ('public burn-event prize summary') scoped to an explicit username, and explicitly distinguishes it from balance-related tools by stating 'without inferring a claimable balance.' However, it does not name or differentiate from other burn-event siblings like player_burn_event_leaderboard or player_burn_event_player.

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 by the purpose statement and the caution against inferring a claimable balance, but there is no explicit guidance on when to choose this tool over alternatives or what prerequisites exist. The agent must infer the appropriate context from the tool name and description alone.

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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