Prediction-market tools: check if a yes/no claim is decidable, desk Brier track record.
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Scored across 2 tools
The two tools are completely distinct: one aggregates Brier scores and resolved counts, the other checks claim decidability. There is no overlap or ambiguity between them.
Both tool names are two-word noun compounds using underscores (brier_summary, claim_decidability). They follow a consistent pattern, though neither uses a verb_noun convention.
With only 2 tools, the server feels thin for a 'Forecast Desk' purpose. It is borderline, not extreme, but the surface is minimal.
The domain implies a forecasting workflow, but there are no tools to create, resolve, or manage claims. Only a reporting summary and a validation check exist, leaving significant gaps.
Aggregate Brier score and resolved count for the desk and each seat (report-only).
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. The explicit 'report-only' marker clearly signals that this tool has no side effects, which is a meaningful behavioral trait beyond what the empty schema implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One compact sentence front-loads the action, scope, and read-only nature. There is no wasted text, and every phrase earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless, report-only aggregation tool with an output schema present, the description is fully adequate. It specifies what is aggregated, at what granularity, and that it is non-mutating.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description adds conceptual meaning by explaining what is aggregated, even though there are no parameters to elaborate on.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Aggregate') and a precise resource ('Brier score and resolved count for the desk and each seat'). The parenthetical 'report-only' clarifies its analytical nature, clearly distinguishing it from the sibling tool claim_decidability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance on when to use this tool versus claim_decidability, nor any exclusions. 'Report-only' implies a read-only reporting context, but the description does not state when an agent should choose this over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check whether a binary claim names a deadline, a public settlement source, and a clear condition.
| Name | Required | Description | Default |
|---|---|---|---|
| claim | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It states the evaluation criteria but does not clarify what the tool actually returns (e.g., a boolean, a structured assessment) or any side effects (it appears inert, but is not stated). Given no annotations, this is a moderate gap; the description is not misleading but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately front-loads the core purpose and criteria. Every word contributes to understanding. It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (checking three conditions), the description covers the 'what' but not the 'how' or 'return value'. Since there is an output schema (though not detailed in the context), the description does not need to explain return values, but it still lacks context on expected input format and examples. However, for a simple check, it is adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning the schema provides no description for the 'claim' parameter. The description adds some meaning—it implies the claim is a binary claim about a deadline, settlement source, and condition—but it does not define what constitutes a 'binary claim' or provide format examples. With only one parameter and minimal description, the compensation is insufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Check') and a specific resource ('a binary claim') and names the three conditions it evaluates ('names a deadline, a public settlement source, and a clear condition'). It conveys the purpose clearly, though it does not explicitly distinguish from the sibling 'brier_summary'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus 'brier_summary'. The description implies it is for checking decidability, but it does not state contexts where brier_summary would be preferred or when not to use this tool. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
brier_summaryclaim_decidabilityReference data for prediction markets: graded resolution clarity, cross-venue links, provenance.
Polymarket, Manifold, Metaculus compared: one fair probability per question. No API key needed.
Bitcoin-anchored sealed-forecast record: search, grades, calibration, luck test. Read-only, no key.
Sealed prediction-market verdicts, graded in public across Polymarket and Kalshi. No auth required.
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