CrowdGap AI Probability Research

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

Annotations include idempotentHint: true, readOnlyHint: false, and destructiveHint: false, but the description adds critical behavioral context: it never signs, sends, or executes payment, and it returns details for a human operator. This goes beyond annotations by clarifying the operational boundary and the required human involvement, which is essential for safe usage.

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, well-structured sentence that conveys the core purpose, idempotency, duration, and non-execution nature. It is front-loaded with the action and resource, and every word adds value, 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?

The tool has 6 parameters and no output schema, but the description provides essential context about idempotency, duration, and the human operator requirement. It does not describe the return format, but given the simplicity and the annotations (idempotentHint, openWorldHint), the description is reasonably complete. The absence of output schema is mitigated by the description's clarity on what is returned (payment details), although more detail on the response structure could be added.

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 50%, with consent and operatorReference having descriptions, but requestId and agentName lack descriptions. The tool description adds the critical context that the quote is for a US$99 subscription and that consent confirms human authorization, which supplements the schema. It also clarifies that operatorReference is a private client-generated UUID and no email or account is required, filling in gaps.

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 it creates an idempotent 15-minute XRP quote for a specific US$99 subscription, distinguishing it from siblings by specifying the resource (XRP quote for subscription) and scope. It also mentions it returns payment details for a human operator, which differentiates it from other tools like get_xrp_checkout or request_live_forecast.

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 this tool (when a quote is needed for a US$99 subscription) and explicitly states what it does not do (never signs, sends, or executes payment), which guides usage. However, it does not explicitly mention alternatives or when not to use it beyond the negation, but the sibling context and the specificity provide sufficient 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that the output is compact and machine-readable, and lists the content components. However, it does not elaborate on 'voluntary-sharing boundaries' or potential side effects beyond the annotations. The description aligns with annotations and adds some context, but not extensive behavioral details. A score of 3 is appropriate given the annotations do the heavy lifting.

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 sentence that front-loads the main action ('Returns a compact, machine-readable CrowdGap introduction') and then lists the components. There is minimal repetition or fluff. It conveys all necessary information efficiently without wasting 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?

The tool is simple with one optional parameter and no output schema. The description explains the return content: introduction, share URL, MCP connection details, and sharing boundaries. It is sufficient for an agent to understand what to expect. However, it leaves 'voluntary-sharing boundaries' vague and does not mention any authentication or prerequisites, but given the tool's simplicity and existing annotations, it is fairly complete. A 4 is justified as it covers the essential context.

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?

There is only one optional parameter (campaign) and the schema coverage is 100% since it has a description in the schema. The tool description does not mention the parameter at all. Since schema already documents it, the baseline is 3. The description adds no additional semantic meaning beyond what the schema 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 states exactly what the tool returns: a compact, machine-readable CrowdGap introduction, share URL, MCP connection details, and sharing boundaries for another AI agent. The verb 'returns' with specific resource components distinguishes it from sibling tools like get_crowdgap_offer, which likely provides offer-related data. It is clear and specific.

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 description does not mention any context, prerequisites, or exclusions. Sibling tools exist (e.g., get_crowdgap_offer), but no differentiation is made. The agent must infer usage from the title and description, which may not be sufficient for selecting between referral and offer tools.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds value by specifying the exact content of the return (fixed terms, integration links, etc.) and uses 'fixed' to imply the data is static. It does not contradict annotations, but adds limited behavioral detail beyond the safety profile.

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 sentence that lists all returned components without any fluff. It is front-loaded and every word contributes meaning. No unnecessary details 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 read-only tool, the description is sufficiently complete. It enumerates the key outputs (terms, capabilities, boundaries, links, checkout URL) and sets expectations for a static offer. However, it doesn't mention the format, size, or potential errors, but given the simplicity and the annotations, this 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 tool has zero parameters, so schema coverage is trivially 100%. The description correctly avoids parameter documentation. With no parameters, a baseline of 4 applies because there is nothing to clarify; the description adds value by stating what the caller gets without any input.

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 CrowdGap's fixed commercial terms, capabilities, boundaries, integration links, and XRP checkout URL. It uses the specific verb 'Returns' and names the resource, making it easy to distinguish from siblings like get_xrp_checkout (which is only the checkout URL) and request_live_forecast (dynamic forecasts).

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: when you need the full offer package (terms, capabilities, links), this is the tool. However, it doesn't explicitly state when not to use it or mention alternatives, such as saying 'use get_xrp_checkout for only the checkout URL' or 'request_live_forecast for dynamic forecasts.' The context is clear but lacks explicit 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?

Annotations already mark readOnlyHint, idempotentHint, and destructiveHint=false, so the description adds value by noting 'human-authorized', which implies an authorization requirement. This extra context is useful and does not contradict any annotations.

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, clear sentence that immediately states what the tool does. It is front-loaded with the essential information and contains 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?

Given the simplicity of the tool (no parameters, no output schema), the description adequately conveys the return value as a checkout for a specific package. It could be slightly more explicit about the format of the checkout (e.g., URL, object), but the lack of an output schema makes this a minor gap. Overall, it is sufficient for an agent to understand the tool's purpose.

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?

With zero parameters, schema coverage is trivially 100%. The baseline for 0 parameters is 4, and since there are no parameters to describe, the description does not need to add parameter-specific semantics. It adds no parameter info, but that is not required here.

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 a specific checkout for 30 live forecasts over 30 days at US$99 in XRP. It uses a specific verb ('Returns') and resource ('human-authorized checkout') and distinguishes itself from siblings by naming the exact product and price, unlike the more generic quote creation tools.

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. It does not mention that a custom quote could be created via create_xrp_subscription_quote, nor does it specify any prerequisites or exclusions. The context implies a specific use case but does not explicitly articulate 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?

The description clearly states that this is a paid operation using a specific credential, and explicitly discloses the idempotent replay behavior (exact requestId replays don't consume another forecast). This adds significant value beyond the annotations, which only indicate idempotentHint and openWorldHint but don't convey the cost or credential requirement.

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 brief, two sentences, and front-loaded with the core action (runs one paid forecast) and critical behavioral note. Every word adds value, and it is concise without omitting key 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?

Given the absence of an output schema and zero parameter explanations, the description is not fully complete. However, the tool's complexity is moderate, and the description covers the main operational aspects (cost, credential, idempotency). It could benefit from clarifying parameters like consent and resolutionSource, but it's adequate as a minimal viable description.

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 coverage is 0%, and the description does not explain any parameter semantics. Parameters like question, deadline, resolutionSource, and consent are left for the schema to define, but the description offers no additional guidance. For a paid tool with strict constraints (e.g., question minLength 20, consent must be true), the description should at least clarify the required consent and parameter purpose.

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 purpose: it runs a paid public-evidence forecast using a specific credential and mentions a unique behavior about requestId replays. This distinguishes it from sibling tools like create_xrp_subscription_quote or get_crowdgap_offer, which are unrelated.

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 explains when to use: to obtain a one-time public-evidence forecast, and specifically mentions that replaying an exact requestId does not consume another forecast, implying idempotency. Though it doesn't explicitly state when not to use or name alternatives, the unique functionality and cost implication provide clear context.

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?

Annotations already declare readOnly and idempotent, but the description adds key behavioral context: static, non-billable, no live research, no quota consumption. This goes beyond the structured hints and helps the agent understand the tool's non-functional impact.

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 concise sentences with no filler. The key points (static, non-billable, no live research, no quota) are 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 test fixture with no required parameters and comprehensive annotations, the description fully covers what an agent needs to know. It clearly communicates the tool's purpose, limitations, and non-billable nature, making it complete in context.

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 fully documents the single optional parameter with a description. The tool description adds no additional parameter information, so baseline 3 is appropriate given 100% 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?

Clearly states it returns a static forecast fixture, distinguishing it from live forecast tools like request_live_forecast. The verb 'returns' and specific resource make the purpose 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?

Implies usage for testing by noting it performs no live research and consumes no subscriber quota. Though it doesn't explicitly name alternatives, the context with sibling tools like request_live_forecast makes the intended use clear.

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