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list_executable_opportunities

Rank both YES and NO across every human-reviewed equivalent Polymarket–Kalshi pair. Each row walks current public depth within the all-in budget, includes estimated taker fees, and links to the lower effective-price venue. Contracts whose rules changed or whose requested size cannot be quoted are omitted and reported as unavailable. Optional family uses a family key returned by the tool; optional side is Yes or No. Use this when the user asks where the largest currently executable cross-venue price differences are.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sideNo
familyNo
amount_usdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains what each row contains (current public depth, estimated taker fees, links to lower effective-price venue) and what happens to excluded contracts ('Since no annotations are provided, the description must be self-sufficient; it is, covering output content and omission behavior without requiring external context.'

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 four sentences with no wasted words. The main purpose, row contents, omission behavior, optional parameters, and usage guideline each earn their place. Front-loading the core action makes it immediately scannable.

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?

Given the tool's moderate complexity and an output schema that covers return values, the description covers the essential context: what the tool ranks, what data is included (depth, fees, venue), the handling of unavailable contracts, the optional parameters, and the exact use case. It is a complete package for an agent to select and invoke the tool 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 schema has no property descriptions, so the description must compensate. It explicitly explains `family` ('uses a family key returned by the tool') and `side` ('Yes or No'). While `amount_usd` is not named directly, the phrase 'all-in budget' clearly refers to it, providing indirect semantics. This is strong but not complete.

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: 'Rank both YES and NO across every human-reviewed equivalent Polymarket–Kalshi pair.' It clearly states the tool's output and scope, and the final sentence ('Use this when the user asks where the largest currently executable cross-venue price differences are') reinforces purpose. This distinguishes it from sibling tools like get_executable_quote (singular) and compare_executable_quotes (comparison), as it lists and ranks all opportunities.

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 ends with an explicit when-to-use instruction: 'Use this when the user asks where the largest currently executable cross-venue price differences are.' This gives clear context, but it does not explicitly state when not to use it or mention alternatives, so it falls short of the 5-level criterion.

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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