GroundTruth Field Evidence

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

With no annotations provided, the description carries the behavioral disclosure burden. 'Get info' clearly signals a read-only, non-mutating operation, and listing what the info covers (purpose, pricing, invocation) adds transparency about what the tool will surface.

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, tightly scoped sentence that front-loads the verb and resource and packs the relevant dimensions (purpose, pricing, usage) without wasted words.

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 no-parameter, no-output-schema informational tool, the description is nearly complete. The only minor gap is that 'ASP' is not expanded, and the source or format of the returned info is not stated, but neither is essential for correct 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?

The tool has zero parameters and the schema has 100% coverage by default, so the baseline is 4. The description appropriately conveys what the informational call returns without needing to document parameters that do not exist.

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 clear verb ('Get info') and names a specific resource ('the GroundTruth ASP') with the specific aspects covered: what it does, pricing, and how to call it. This distinguishes it from the sibling tools, which are action/task-oriented rather than informational.

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 usage context is implied: use it when the agent needs information about the GroundTruth ASP. However, it gives no explicit guidance about when not to use it or how it compares to alternatives like human_do, review_task, or task_status.

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 behavioral disclosure burden. It usefully discloses the x402 payment requirement and the asynchronous task_id polling pattern. However, it omits failure modes, side effects, and what happens after proof is submitted, leaving notable gaps for a paid creation 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 with no filler. It front-loads the core purpose, then states the payment requirement and the follow-up mechanism. Every sentence earns its place and is easy for an agent to parse quickly.

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 no output schema, no annotations, a nested target_location object, and six parameters, the description is incomplete. It mentions task_id but not the full response shape, payment mechanics, or how location constraints affect the task. An agent would need additional context to invoke this tool with full confidence.

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 no parameter-level meaning beyond the schema. It does not explain intent, proof_type, instructions, budget_usdt, target_location, or timeout_seconds. Schema coverage is 67%, leaving budget_usdt and timeout_seconds undocumented in both schema and description, and the description does not compensate.

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 a specific verb and resource: 'Create a task for a human oracle to complete in the real world.' It clearly communicates what the tool does and implicitly separates it from task_status by mentioning the returned task_id is polled there. However, it does not explicitly differentiate from ground_truth_info or review_task.

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: when a real-world human task needs to be completed and x402 payment is acceptable. It does not state when to prefer sibling tools or provide exclusions, so usage guidance is present but only implicit.

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. It discloses the two outcomes and their financial consequences (accept releases payout, reject fails with no payout), which are the key behavioral traits. It does not mention irreversibility, but the effect is clear and the tool is simple.

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 with zero waste. The core action and consequences are front-loaded, and the usage condition is stated immediately after.

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 tool with no output schema, the description covers what it does, when to use it, and the consequences. It does not describe the response format, but that is not required without an output schema, and the tool is straightforward.

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 100%, so the schema already documents all parameters. The description adds the timing condition (after proof is shown) but does not elaborate on parameter specifics beyond the schema, meeting the baseline for high coverage.

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 (review), the resource (submitted proof), and the binary decision (accept/reject) with explicit payout consequences. It distinguishes itself from siblings like task_status by focusing on the action rather than status retrieval.

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 states when to call ('Call this after task_status shows the proof'), providing a clear precondition. It does not name alternatives or when-not cases, but the sibling tools are obviously different in purpose, so the guidance is sufficient.

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 must disclose behavioral traits. 'Check' implies a read-only operation, but the description does not explicitly state that it is side-effect free, nor does it mention error handling (e.g., what happens if the task does not exist or is still running). For a tool with zero annotation coverage, this is a notable gap.

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 conveys the action and target clearly and efficiently, making it easy for an agent to parse quickly.

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 is adequate for a simple single-parameter tool: it states the purpose and the input. However, without an output schema, it does not hint at the shape of the return value (e.g., statuses like 'completed', 'failed'), which could affect how the agent interprets results. This is a minor but real gap.

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 describes the task_id parameter, including format and provenance (returned by human_do). The tool description adds no additional semantic meaning beyond the schema, so the baseline 3 applies due to high schema coverage.

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') and the resource ('status and result of a GroundTruth task') identified by task_id. It is specific and avoids tautology, though it does not explicitly differentiate from sibling tools like ground_truth_info, which could be a related but distinct 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?

No guidance is provided on when to use this tool versus alternatives. The schema mentions task_id is returned by human_do, implying a workflow, but the description itself gives no context about polling patterns, timing, or exclusions. The agent is left to infer the appropriate usage.

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