NegativeEV bet checker

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

The description adds substantial behavior beyond the annotations: invalid inputs return a plain status without spending a check, every result leads with status and check_spent, re-wording information is provided, and games that already started still check against pre-start simulations. This is transparent about cost, output shape, and edge cases.

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 dense and information-rich with almost no wasted words. It is slightly long, but each sentence adds meaningful operational detail, so the length is justified.

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 has only one parameter, no output schema, and rich runtime behavior, the description is complete: it covers input format, output fields, error behavior, cost semantics, sports coverage, and time-edge handling. An agent has enough context to call it correctly.

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 single 'bet' parameter is 100% covered by the schema, and the description enriches it significantly with plain-text format guidance, a concrete example, and parlay handling semantics. This goes well beyond the schema's minimal example.

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 clearly states the action ('Check a specific sports bet'), the resource (sports bets), and the evaluation method (thousands of play-by-play simulations). It explicitly distinguishes this tool from suggestion-oriented tools by stating it prices a bet the caller names and never suggests one.

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?

The description gives strong usage guidance: 'Call this first', explains there is no setup, and explicitly says not to use it for 'what should I bet tonight'. It provides failure behavior for missing/unrecognized bets, but it does not explicitly contrast with the sibling tools get_slate or get_usage by name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

The readOnlyHint annotation already covers safety, and the description adds valuable behavioral context: it is free, spends no check, and clarifies that no_slate/ungraded mean the game is not on the simulated slate rather than the bet was worded wrong. This goes well beyond the annotation.

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?

Four dense sentences, each carrying distinct, non-redundant information: purpose, parameter usage, cost/necessity, and call contexts. The core definition is front-loaded and there is no filler.

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 tool with one optional parameter and no output schema, the description covers purpose, parameter usage, cost, relation to check_bet, and interpretation of related result codes. Nothing an agent needs to call it correctly is missing.

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 schema covers 100% of the parameter and already documents the sport enum and the omit behavior. The description's 'Pass sport for one; omit it for all' restates the schema without adding new meaning, so the baseline 3 applies.

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?

States a specific, measurable purpose: identify which of four named leagues have a checkable slate, defined as at least one simulated game not started. The explicit league list and the definition of 'checkable' distinguish it clearly from siblings like check_bet.

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?

Explicitly tells the agent when to call it ('Call it to answer "what can be checked today"') and when not to, noting that check_bet reports a missing slate itself at no cost. It also names concrete triggers: after a no_slate or ungraded result.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Beyond the readOnlyHint annotation, the description discloses meaningful behavioral details: the operation is free and 'spends no check,' and it spells out rate limits (100/day anonymously, 1000/hour with a signed-in token). These details are not available from annotations and materially inform how an agent should plan calls.

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?

Three dense sentences front-load the core answer ('How many bet checks...'), then add quota mechanics, cost behavior, and usage guidance without redundancy. Every clause 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 read-only quota query with a readOnlyHint annotation and no output schema, the description fully covers what an agent needs: the meaning, the quota limits, the free/no-check behavior, and when to invoke it. Nothing important is missing.

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 schema coverage is 100% by definition. The baseline for zero parameters is 4; the description correctly focuses on behavior and usage rather than inventing parameter details.

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 exactly what the tool does: reports how many bet checks the caller has left and when the next one frees up, with specific quota numbers. It also explicitly differentiates from the sibling check_bet by stating 'It grades nothing', making its role unambiguous.

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?

The description gives explicit when-to-use guidance: 'call it when a check comes back refused for quota, or before working through a long list of bets.' It also states a clear when-not-to-use: 'not a step before a check,' which helps an agent route to check_bet instead when grading is needed.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.