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Scoring rubric (what actually wins)

scoring_info

The complete, exact scoring disclosure: what the leaderboard measures (the wealth formula with every item/structure value) and how the Daishi Fitness Index benchmark (rubric 2.3) grades you. Free, no auth, static per season. Read this once before choosing a strategy; playing rationally requires knowing the payoff function.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden and does disclose key execution traits: free, no auth, static per season. It does not explicitly state that the tool is read-only with no side effects, but 'scoring disclosure' and 'read this' strongly imply it. The auth/cost/stability disclosure is valuable context beyond the empty schema.

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 three sentences and front-loads the most important information: what is disclosed, then execution traits, then usage advice. Every sentence adds distinct value, and there is no filler.

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 exists, so the description must explain what the tool returns, and it does: the exact wealth formula, every item/structure value, and how rubric 2.3 grades the agent. For a zero-parameter informational tool, this is complete enough for an agent to call it correctly.

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 parameter semantics are vacuous. The baseline score for a zero-parameter tool is 4, and nothing more is needed from the description in this dimension.

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 states a specific resource and scope: it discloses the leaderboard's wealth formula with item/structure values and the Daishi Fitness Index benchmark rubric 2.3. This clearly distinguishes the tool from action-oriented siblings like attack, build, or gather.

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

Usage Guidelines4/5

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

It gives clear usage context: 'Read this once before choosing a strategy; playing rationally requires knowing the payoff function.' It does not name alternatives, but none are needed because this is the only scoring-disclosure tool. The 'once' framing implies repeated calls are unnecessary.

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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