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Tollbridge calls (your calls graded against the house)

tollbridge_calls
Read-onlyIdempotent

FREE — YOUR SCOREBOARD AGAINST THE HOUSE on identical events: n, graded, open, player/house accuracy, both Brier scores (lower is better; a bare call is a certainty claim and grades 0 or 1), per question. Every number is a count of real graded calls — n=0 reports nulls, never fabricated zeros. Strictly personal: name your payer address and this reads only your own calls; no public leaderboard exists. No payment required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
payerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
metaNo
errorNo
statusYes
paymentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent, open-world behavior, so the bar is lower. The description adds genuinely useful traits beyond them: null handling ('n=0 reports nulls, never fabricated zeros'), scoring direction ('lower is better'), the 0/1 grading of a bare certainty call, and that no payment is required. It does not spell out auth/permission requirements for the payer, which keeps it below a 5.

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?

Front-loads the headline ('FREE — YOUR SCOREBOARD AGAINST THE HOUSE') and packs metrics, semantics, and scope tightly into one paragraph. Slight redundancy between 'FREE' and 'No payment required' is the only waste, and every other clause adds call-relevant information.

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?

With an output schema present, the description needn't re-explain return values, yet it usefully disambiguates them (null handling, lower-is-better Brier). Combined with annotations and the single required parameter, it is nearly complete; only the absence of sibling routing guidance leaves a small gap.

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%, so the description must carry the parameter's meaning, and it does: payer is your address and it scopes the read to your own calls only. The format (0x pattern) is left to the schema, but the semantic role of the parameter is clarified beyond the bare name.

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?

States a specific deliverable: a personal scoreboard of your own calls graded against the house on identical events, enumerating the returned metrics (n, graded, open, accuracy, both Brier scores). It also distinguishes itself from the leaderboard sibling by declaring 'no public leaderboard exists', so an agent can route correctly without opening schemas.

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?

Provides the key precondition ('name your payer address and this reads only your own calls') and the scope boundary (personal, not public), which implies when it applies. However, it never contrasts with near siblings like tollbridge_arena_profile or tollbridge_calibration, so the when-to-use-this-vs-that decision is left to inference.

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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