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voxodds

by com.voxodds

submit_forecast

Submit YOUR probability forecast on a live prediction market and build a public, audited track record. VoxOdds is the neutral scorekeeper: your forecast is stored append-only next to the market price captured at the same instant, both are Brier-scored when the market resolves, and your record appears publicly (model 'ext-') on voxodds.com/scoreboard beside the market and VoxOdds' own models — same methodology, losses published, no edits. Use list_trending_markets to find a market_id. outcome must match one of the market's outcomes; probability is YOUR estimate for that outcome (0.01-0.99); forecaster_id is your stable handle (3-32 chars, a-z 0-9 dash). Free; forecasts cannot be deleted or revised.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outcomeYes
market_idYes
probabilityYes
forecaster_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description fully discloses critical behaviors: append-only storage, simultaneous market price capture, Brier scoring, public scoreboard visibility, model ID format, and irreversibility. This goes far beyond what the schema or annotations provide, making the tool's side effects very clear.

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 somewhat long but every clause earns its place, covering purpose, behavior, usage, parameters, and caveats. It is front-loaded with the main action and then layers supporting details without fluff.

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?

For a 4-parameter write operation with no schema descriptions and no annotations, the description is exceptionally complete. It explains purpose, usage, parameter semantics, behavioral guarantees, and limitations. The output schema exists, so return-value details are not needed.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate. It explains all four parameters: market_id is sourced via list_trending_markets, outcome must match market outcomes, probability is the user's estimate with range 0.01-0.99, and forecaster_id has a specific format (3-32 chars, a-z 0-9 dash). This fully addresses the semantic gap.

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 opens with a specific verb+resource: 'Submit YOUR probability forecast on a live prediction market' and clearly states the purpose of building a public, audited track record. This distinguishes it from read-only sibling tools like get_forecaster_record or get_market_odds.

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?

The description gives clear usage context, including the prerequisite 'Use list_trending_markets to find a market_id' and a strong warning that 'forecasts cannot be deleted or revised.' It does not explicitly list alternative tools for reading records, but the context makes the intended use obvious.

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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TDQS

A4.4/5.0
Disambiguation4/5

Most tools have clear, distinct purposes, but a few overlap: get_market_odds and get_world_cup_odds both handle World Cup probability questions, and get_edge_signals and get_research_theses both point to potentially mispriced markets. The descriptions help clarify intent, but the boundaries are not always crisp.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case, with verbs like get, list, submit, check, compare, find. Even compound objects like best_price or world_cup_odds fit the pattern cleanly, and no mixed conventions or camelCase appear.

Tool Count5/5

At 14 tools, the server is well-scoped within the 3-15 typical range. Each tool serves a distinct function—odds lookup, market browsing, research, forecasting, and World Cup-specific content—without redundant bloat. The count feels appropriate for the broad domain.

Completeness5/5

The tool set covers a complete workflow: discovering markets, comparing odds, evaluating bets, finding best prices, getting quotes, submitting forecasts, and reviewing personal and AI track records. The lack of an execution tool is intentional (the server is research-oriented), and the append-only forecast model makes missing update/delete operations a non-issue.

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