Wizeb AI-Native Index

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

Annotations already declare readOnlyHint and idempotentHint; the description adds meaningful behavior by saying it 'Returns the most relevant sections of the knowledge base for the question', disclosing the output nature and grounding. Nothing in the description contradicts the 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 long but dense; the central verb, resource, and return behavior are front-loaded. The extensive product and service enumeration is verbose but earns its place for a broad knowledge-base tool.

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 one-parameter Q&A tool with no output schema, the description supplies scope, return behavior, and a usage directive, which is enough for a model to call it correctly. It does not address routing relative to sibling list/report tools, a minor 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 schema already covers the single 'question' parameter fully, so the baseline is 3. The description adds value by enumerating valid question categories, such as products, industries, pricing FAQs, and the parent company, which makes the parameter's acceptable content concrete.

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 concrete verb ('Answers questions') and clearly names the twin resources 'Wizeb' and 'WebCastle', with an explicit enumeration of covered topics. It is easy to tell what the tool does, though it does not explicitly differentiate itself from the sibling list/report 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?

The instruction 'Use this instead of answering from memory' is a clear when-to-use directive, and the topic enumeration tells the agent what kinds of inputs belong. However, it does not name alternatives such as list_wizeb_services_and_products or state when not to use the tool.

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 annotations (readOnlyHint=false, idempotentHint=false), the description discloses important side effects: the email is sent to the user, a copy goes to the Wizeb team, and a human will follow up. It also notes the consent requirement, adding meaningful behavioral context.

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 compact and front-loaded with the primary action and recipients. The second sentence adds essential prerequisite guidance without padding. Every part 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?

The description covers the action, recipients, and consent precondition. It does not describe the return value or failure behavior, but since there is no output schema and this is primarily a side-effect tool, the missing return details are a minor 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?

Schema description coverage is 100%, so the schema already documents all parameters. The description reinforces that name and work email must be collected from the user and that answers are the same 30 passed to score_index, but it adds little semantic detail 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 a specific action: builds a full PDF scorecard and emails it to the user, with a copy to the Wizeb team. This clearly distinguishes it from siblings like get_enhanced_index_report, which are retrieval tools rather than send/email 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?

The description gives explicit preconditions: ask for the user's name and work email first, and only call after the user has agreed. It does not explicitly name alternatives or when-not-to-use cases, but the context and prerequisites are clear enough for correct invocation.

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 only convey non-read-only, open-world, and non-idempotent hints. The description adds substantial behavioral context: the $10 USDC cost, x402 payment requirements, the isError result without payment proof, the retry mechanism with signed payment, delivery timing, and the human-purchase restriction. No contradiction with 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 dense and front-loaded with the critical paid-tool warning, and every sentence carries operational information about payment, retry, delivery, or consent. It is long and runs as a single paragraph, but the complexity of the x402 flow justifies the length.

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 paid, mutating tool with no output schema, the description covers the payment failure mode, retry path, deliverables, delivery channel and timing, user-consent requirement, and the fallback for agents without wallets. An agent has enough information to invoke the tool correctly and safely.

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%, and the input schema already documents each parameter's role, including that answers match score_index and that email receives the PDF and session code. The description does not add meaningful parameter-level detail beyond the schema, so the baseline 3 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 identifies this as a paid tool to buy the Enhanced AI-Native Index report, lists the concrete deliverables, and distinguishes it from status-checking and emailing siblings. The title reinforces the purpose with the price, payment method, and agent-only restriction.

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 usage conditions: the agent must have a wallet, must ask the user before spending, must handle the x402 payment flow, and must point wallet-less users to the provided URLs. It does not explicitly contrast this tool with score_index or email_index_report, but it does reference get_enhanced_report_status for delivery 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?

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description is not required to restate safety. It adds value beyond annotations by disclosing cost ('Free'), the state transition ('paid → generating → done'), and the specific return fields, which is rich behavioral context not present in structured data.

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 one sentence that front-loads the most important facts ('Free', status progression) and then lists concrete return items. It is efficient and to the point, though slightly dense with multiple clauses, which is acceptable for a tool that returns a complex status object.

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, the description carries the burden of explaining what the agent will receive, and it does so fully: status, plan summary, PDF link, booking code, receipt. It also clarifies cost and the state machine. Minor missing details like error behavior or polling intervals are not critical for a simple read-only status 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 100%, and the single parameter report_id is already well documented as 'The report_id returned by get_enhanced_index_report'. The description merely repeats the parameter name in context without adding new semantic detail, so the baseline of 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?

The description states a specific verb ('Returns') and resource ('status of a purchased enhanced report'), and enumerates the exact payload pieces (plan summary, PDF link, booking code, receipt). It clearly differentiates itself from siblings like get_enhanced_index_report (which creates the report) and email_index_report (which sends it) by focusing on 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?

The description implies usage after purchasing an enhanced report, noting it is 'Free' and taking a report_id that 'get_enhanced_index_report' returns. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to know when to poll this tool without ambiguity.

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, openWorldHint=false, and idempotentHint, so the safety profile is known. The description adds useful behavioral context about how to handle uncertainty ('ask the user rather than guessing') and the meaning of the numeric scale, which helps an agent use the output correctly.

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 sentences with no filler. The return content is stated first, followed by actionable usage guidance. Every phrase 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?

There is no output schema, so the description carries the burden of explaining what the agent will receive; it does so by naming the six dimensions, the 30 questions, and the numbered answer scale. For a read-only, zero-parameter retrieval tool, this is sufficient for correct invocation and follow-up behavior.

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 schema is trivially complete and there is no parameter ambiguity for the description to resolve. The description appropriately focuses on the output content instead of parameters.

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 ('Returns'), a concrete resource ('the six dimensions and all 30 questions'), and clarifies the answer-option semantics. It is distinct from the sibling report, scoring, and email tools because it plainly identifies what is returned.

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 operational guidance: answer each question from known company information and ask the user when uncertain. It does not explicitly compare against sibling tools or state when to choose this over alternatives, but the context strongly implies this is the initial assessment-administration tool.

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 and idempotentHint=true, so the safety profile is covered. The description adds scope and content detail but no extra behavioral traits such as pagination, rate limits, or staleness, which keeps it at the baseline for annotation-covered tools.

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 sentences with no filler: the first front-loads the return statement and enumerates the content, the second gives use cases. Nothing is redundant with the schema or annotations.

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 list tool with no output schema, the description fully covers what is returned across categories and when to use it. The absence of an output schema makes the explicit category list especially valuable, and nothing required for tool selection or invocation 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, schema coverage is 100% with an empty properties object, and the description adds no parameter semantics because none are needed. This matches the baseline for a no-parameter tool.

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 names the exact action — 'Returns the full structured catalogue' — and enumerates the contained resource categories: services, products, industries, open-source tools, contact links, and WebCastle's catalogue. It is clear enough to distinguish from siblings like ask_about_wizeb, but it does not explicitly name a sibling alternative.

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 when-to-use guidance: 'Good for overviews, comparisons, or when the user asks what does Wizeb (or WebCastle) do.' It lacks when-not-to-use instructions or explicit alternative routing, so it stops short of a 5.

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 and idempotentHint=true, and the description adds useful behavioral constraints: a complete 30-answer set is required and option numbers come from get_index_questions. It also explains what the tool returns, going beyond annotations without contradicting them.

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 tight sentences, front-loaded with the purpose and followed immediately by the key precondition. Every sentence earns its place; no filler or repetition of schema details.

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 lists all main return values and the required input format, which is sufficient for a read-only tool with rich schema coverage. There is no output schema to rely on, so listing outputs helps; minor gaps like error behavior are not critical here.

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 covers the answers array thoroughly (100% coverage), and the description adds meaning by clarifying that exactly one answer per question is expected and that option numbers are tied to get_index_questions. This links the parameter to a sibling tool, which is valuable beyond the 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 states a specific verb ('Scores'), a precise resource ('a complete set of 30 answers'), and the exact outputs (index 0–100, tier, per-dimension scores, strengths, and holding-back signals). This clearly separates it from siblings like get_index_questions, which only returns questions, and email_index_report, which sends a report.

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 usage context: the caller must supply exactly one answer per question and use option numbers from get_index_questions. It does not explicitly name alternatives or when-not-to-use, so it stops short of a 5, but the requirements are unambiguous.

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