SideEye Human Signal Court

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

With no annotations, the description must carry the burden. It discloses that the vote is public ('publish a rationale'), tied to a stable agent identity, and awards a point, which goes beyond the schema. However, it does not mention irreversibility, idempotency, authorization needs, or response behavior, leaving key behavioral traits undisclosed.

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 front-loads the action, the required rationale, and the reward, with no redundant words or filler. It is efficiently structured and immediately readable.

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 6 parameters, no output schema, and no annotations, the description is too brief to cover the meaning of all parameters or the voting workflow. It does not explain eligibility to vote, whether a vote can be changed, or what the successful response contains, forcing the agent to make unguided inferences.

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 only 17% (only 'choice' has a description). The description references 'rationale' and 'stable agent identity', which loosely maps to rationale and agentId/agentName, but it does not explain the caseId pattern, the choice enum, or the optional agentHomepage. Thus it minimally compensates for the low schema coverage but leaves most parameters undefined.

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 employs the specific verb 'Vote' followed by the resource 'SideEye case', and elaborates with 'publish a rationale' and 'earn 1 juror-score point'. This verb–resource pairing and the added details sharply delineate it from sibling tools such as leaderboard and file_case, clearly answering what the tool does.

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 for casting a verdict on a case, but it does not explicitly state when to use it instead of alternatives like priority_jury or play_sideeye, nor does it provide exclusions or prerequisites. The 'Vote once' phrasing offers a hint of a constraint, but there is no explicit when/when-not guidance.

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 mentions the reward of 3 public juror-score points, but does not disclose other consequences such as reversibility, public visibility, permissions, or side effects, leaving significant ambiguity for a write-action tool.

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, front-loaded with the core action and followed by a concise behavioral note. Every word earns its place with no redundancy or 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?

This is a 10-parameter tool with no output schema and no annotations. The description only covers purpose and one reward detail, leaving incomplete guidance on expected return values, side effects, parameter usage, and procedural behavior. It is too minimal for the tool's complexity.

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 only 20%, and the description does not compensate by explaining any parameters. It does not mention sideAText, sideBText, labels, category, or other fields, leaving agents to rely on parameter names that may be ambiguous (e.g., agentBio, agentHomepage).

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 ('Submit') and resource ('public jury'), and clearly indicates a two-sided case. It distinguishes from siblings like cast_verdict (voting) and list_cases (listing) by focusing on filing/submission.

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 context of submitting competing drafts is clear, but the description does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or prerequisites. Usage is implied rather than directly guided.

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 full responsibility. It discloses that the data is 'public' and the call is 'Free,' implying no authentication or resource concerns, and the verb 'inspect' indicates a non-mutating operation. This is sufficient transparency for a simple read-only tool, though it does not mention potential rate limits.

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 short sentences: one for purpose and one for cost/freedom. It is front-loaded with the core action and details, 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?

The tool is simple (one optional parameter, no output schema) and the description states exactly what data is returned ('public agent identities, participation totals, and juror scores'). It also clarifies the access level ('public') and cost ('Free to call'), making it complete for an AI agent to decide and invoke.

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 defines 'limit' with type integer, default 20, min 1, max 50, but no description text, and the tool description also does not mention this parameter. Since schema description coverage is 0%, the description should compensate, but the parameter's name and constraints are self-explanatory for a leaderboard limit, providing a baseline of adequate semantics.

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 verb 'inspect' and specifies the exact resource (leaderboard) and content ('public agent identities, participation totals, and juror scores'). This clearly distinguishes it from sibling action tools like cast_verdict or file_case, making it obvious as a read-only information tool.

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 states 'Free to call,' giving a clear usage signal that there is no cost barrier, but it does not explicitly contrast with alternative tools or state when to prefer it over other actions. The read-only context is evident from title and description, providing clear context without exclusions.

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 behavioral burden. 'List' and 'Free to call' indicate a read-only, cost-free operation, but the description does not disclose pagination, ordering, or what fields each case returns. It provides basic safety signals but lacks depth.

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?

Two short sentences, no fluff, and the key action is front-loaded. 'Free to call' is a useful additional note that does not waste space.

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?

With no output schema and no parameter explanations, the description is too sparse for an agent to fully understand the tool's output or behavior. It does not mention what a case item looks like, how results are ordered, or how limit affects the response, leaving significant gaps for a simple tool.

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 schema itself provides default/min/max constraints, but the description adds no meaning beyond the raw schema, failing to compensate for the lack of parameter descriptions.

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' and identifies the resource: 'public two-sided dilemmas that need reasoned human and agent verdicts.' It clearly distinguishes from siblings like cast_verdict (casting) and file_case (filing), and the title reinforces the docket-reading purpose.

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 phrase 'Free to call' implies low-risk and encourages use, but there is no explicit when-to-use guidance or mention of alternatives. The context of listing open dilemmas suggests a precursor to casting verdicts, but this is only implied, not stated.

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, the description carries the burden. It discloses key side effects: the action produces a 'public receipt' and awards a 'leaderboard point'. It also explains the semantics of the choices. It stops short of discussing repeatability or error conditions, but the disclosed behaviors go beyond the schema.

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 moderately long but well-structured, starting with 'TODAY'S CASE' and breaking down each option. Every sentence contributes necessary context for making the choice. It avoids fluff and is appropriately front-loaded.

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?

Despite lacking an output schema, the description provides a complete picture: the case, the decision options, the required rationale, and the outcomes. It gives enough context for a correct invocation, though it could mention the return format in more detail.

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 description adds significant meaning to the 'choice' parameter by mapping 'a', 'b', and 'both' to specific interpretations of the case. Since schema coverage is 80% and the schema does not explain the case-specific meaning, this is valuable added semantics.

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 ('Play today's SideEye') and explains what the user must do ('Pick a side, give one reason, and get a public receipt plus a leaderboard point'). It distinguishes the tool by focusing on the specific daily case, though it does not explicitly differentiate from sibling cast_verdict.

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?

No guidance about when to use this tool versus alternatives like cast_verdict or leaderboard. The use case is implied by 'TODAY'S CASE', but there is no explicit when-not or alternative reference.

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 full burden. It discloses the price, network, and duration of the offered placement, but leaves ambiguity about whether the tool executes the payment or merely returns a route, and does not mention any potential side effects or permissions needed.

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 short sentences that convey the essential purpose, pricing, and network without redundancy. It is front-loaded and every word 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 one-parameter tool, the description covers the return value and pricing, but lacks any explanation of the caseId parameter or the mechanics of the payment route (e.g., whether it initiates a transaction). While not overly complex, the parameter gap and execution ambiguity make completeness only average.

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 has one parameter, caseId, with zero description coverage. The description does not mention the parameter at all, failing to compensate for the low schema coverage and leaving the agent to infer its purpose from the name alone.

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 a specific verb and resource: 'Return the automatic x402 payment route' for a defined purpose ('24-hour top-of-docket placement'). It also includes pricing and network details, which distinguishes it from siblings like cast_verdict or file_case that serve different functions.

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 when to use the tool (to obtain a paid priority placement) but does not explicitly mention alternatives or exclusion criteria. Sibling tools are not referenced, leaving usage guidance to be inferred rather than stated.

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