crypto-casinos

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

With no annotations, the description compensates by revealing that the tool decodes fine print from T&Cs and excludes expired promos. It also lists the exact output fields. However, it does not discuss behaviors like rate limiting, auth, or the meaning of the value score, leaving some gaps.

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 two sentences that lead with the tool's purpose and immediately list the key output attributes. No filler words or redundant information.

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?

The description covers the tool's purpose, the specific output fields, and the inclusion/exclusion policy. The optional parameters are simple and partially documented in the schema; the lack of an output schema is offset by listing the returned fields. Some details about ranking or updates are absent but not critical.

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 describes only the 'casino' parameter, leaving 'limit' undocumented. The description does not elaborate on either parameter, so the meaning of 'limit' (e.g., maximum number of results) is left entirely to inference. With 50% schema coverage, the description should have compensated for the missing parameter explanation.

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 that this tool returns the current best crypto casino bonuses, with specific fine-print fields (wagering requirement, max bonus, free spins, min deposit, value score) and excludes expired promos. It distinguishes itself from sibling tools like top_casinos or list_casinos by focusing specifically on bonuses with decoded T&Cs.

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 explicitly says 'Use this for "best crypto casino bonus" questions,' providing a clear invocation context. It does not explicitly mention when not to use it, but this guidance is sufficient for the intended use case.

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?

No annotations are provided, so the description must carry the burden. It adds the key insight that 'Data comes from hand-run real-money tests,' lending credibility. However, it does not explicitly state read-only behavior, error handling, or what happens if the casino is not found.

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, information-dense sentence plus a short provenance note. It front-loads the core purpose and every clause adds value.

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 simple single-parameter lookup with no output schema or annotations, the description lists the expected return contents. It lacks edge-case instructions or exact-match caveats, but overall is adequate.

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 input schema fully documents the 'name' parameter with an example. The description does not add extra parameter semantics beyond reinforcing that it is a single casino, so it meets the high-coverage baseline.

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 verb 'Get' and the resource 'WagerX forensic audit verdict for one crypto casino', and enumerates the included data points (trust score, audit status, live test, KYC, license, review link). This differentiates it from siblings like compare_casinos or list_casinos.

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 implies singular use ('for one crypto casino') but does not explicitly mention when to use this over the sibling tools such as compare_casinos or best_bonuses. No exclusions or alternative tool references are provided.

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?

No annotations are provided, so the description carries the full burden. It does add context about the data source (WagerX audit data) and the specific comparison criteria, but it does not explicitly state whether the operation is read-only or what the exact return format is. This is inferred from the 'compare' action.

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, front-loaded sentence with no wasted words. It efficiently conveys purpose, scope, and data dimensions.

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 simple array parameter and no output schema, the description covers the core requirements: what to pass, how many, and what data is used. It lacks an explicit read-only note and explicit alternative tool guidance, but remains adequate for basic invocation.

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 coverage is 0%, so the description must compensate for parameter documentation. It conveys the array length constraint (2-5) and implies that the parameter is casino names, but it does not explicitly name the 'names' parameter or describe its input format beyond the count.

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 tool's function: comparing 2-5 crypto casinos on WagerX audit data, with specific attributes listed (trust score, live tests, KYC, withdrawal speed). This distinctly separates it from siblings like list_casinos or check_casino.

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 clear context that this is for side-by-side comparison of multiple casinos, which differentiates it from single-casino or list-oriented tools. However, it does not explicitly name alternative tools or state when not to use it.

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?

With no annotations provided, the description carries the burden of behavioral disclosure. It adds 'newest first' as a behavioral trait, which is useful, but does not mention whether the operation is read-only, what the return payload looks like, or any rate limits. This is minimal but not empty.

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?

A single concise sentence that states the action, resource, and ordering. No wasted words or redundant information.

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 simple list operation with one parameter, the description gives the essential context (what is listed, ordering). It does not describe the shape of an audit entry, but given the schema covers the parameter and there is no output schema, this is adequate. Slightly incomplete because it doesn't hint at what fields are returned.

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% for the single 'limit' parameter. The description does not mention or explain the parameter at all, leaving the schema's constraints (min, max, default) to imply usage. The description adds no semantic value beyond what the schema already provides.

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 uses the specific verb 'List' and clearly identifies the resource ('WagerX real-money casino audits') with an ordering constraint ('newest first'). This unambiguously distinguishes it from sibling tools like 'list_casinos' or 'top_casinos'.

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 implies usage by specifying the scope ('most recent... audits') and ordering, but does not explicitly state when to use this tool versus alternatives or what it's not for. It provides clear context but no exclusions or alternative tool references.

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?

With no annotations provided, the description carries the full burden of indicating that this is a read-only listing operation. The phrase 'List every casino' makes the non-destructive nature clear and defines the exact scope, while 'with trust score and status' discloses the result content. It does not detail pagination or ordering, but for a zero-parameter list tool this is adequate.

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, information-dense sentence. Every word adds value: it names the action, scope, and output fields, with no filler or repetition.

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 zero-parameter tool with no output schema, the description is sufficiently complete: it states exactly what will be listed and what data points are included. It could mention ordering or data freshness, but those are minor given the tool's simplicity and clear scope.

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 appropriately avoids redundant parameter explanations and instead adds context about the returned fields, which is useful given there is no output schema.

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 uses a specific verb ('List'), a definite resource ('every casino WagerX holds forensic audit data on'), and names the output fields ('trust score and status'). This clearly distinguishes it from sibling tools like top_casinos, new_casinos, or check_casino, which imply filtered or single-casino operations.

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 implies the tool is for getting a comprehensive list of all audited casinos, but it gives no explicit guidance about when to choose this over siblings such as top_casinos, new_casinos, or compare_casinos. 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.

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

Without annotations, the description carries the full transparency burden. It discloses that the list includes casinos still mid-audit and that unscored entries are awaiting hand-run real-money tests, which is valuable behavioral context. It doesn't mention return format or ordering, but for a simple list tool the key caveats are covered.

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 three concise sentences, front-loaded with the core purpose and a clear usage hint. Every sentence adds value: what it returns, when to use it, and a crucial caveat about unvetted entries. No waste or redundancy.

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 zero-parameter, no-output-schema tool, the description provides sufficient context. It explains the scope (newest on WagerX radar), the inclusion of mid-audit entries, and the meaning of unscored entries. This is complete 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.

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

The tool has zero parameters, so the description doesn't need to explain parameter semantics. The baseline of 4 is appropriate because there are no params to clarify, and the description doesn't introduce any misleading param-related information.

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 that the tool returns the newest crypto casinos on WagerX's radar, including those mid-audit. It explicitly frames the use case with 'Use this for "new crypto casinos" questions,' which distinguishes it from siblings like top_casinos or latest_audits.

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 provides a clear usage context ('Use this for "new crypto casinos" questions') and hints at a distinction from fully audited lists by noting entries may be mid-audit. However, it doesn't explicitly name alternative tools or state when not to use this tool, leaving some room for interpretation.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds meaningful context by explaining the ranking methodology (audit trust score derived from real-money tests, payout speed, KYC, support, license). This goes beyond what the tool name alone conveys. It does not mention output format or pagination, but for a ranked list tool, the ranking criteria are the key behavior.

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 two sentences: the first defines the tool's output and ranking basis, the second gives usage context. Every word earns its place, and the most critical information is front-loaded. No redundancy or fluff.

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 provides substantial context: what is returned (ranked casinos), the ranking criteria, and when to use it. The only gap is the lack of explanation for the limit parameter, which is a minor omission given the schema already provides type and range constraints.

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%, and the description does not mention the 'limit' parameter at all. The parameter is simple and has constraints in the schema, but the description should have clarified that it controls the number of casinos returned. Since the description fails to compensate for the lack of parameter documentation, a score of 2 is appropriate.

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 tool returns 'Best crypto casinos ranked by WagerX audit trust score' with specific criteria (real-money tests, payout speed, KYC, support, license). This distinguishes it from sibling tools like list_casinos (general list) and new_casinos (recent additions) by emphasizing the ranking basis.

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?

It provides explicit usage guidance: "Use this for 'best/safest/most trusted crypto casino' questions." This tells the agent exactly when to select this tool. However, it does not mention when NOT to use it or cite alternatives directly, which would make it a 5.

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