Send Your Agent Website Readiness

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

Annotations already indicate readOnlyHint=true and idempotentHint=true, so the agent knows this is a safe, non-destructive operation. The description adds that the tool explains and provides a next step, but no additional behavioral details (e.g., rate limits, auth) are disclosed. The description adds some value beyond 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 two sentences: the first defines the purpose, the second clarifies scope. Every word adds value with no redundancy. It is front-loaded with the core action.

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 explanatory tool with one parameter and no output schema, the description is largely complete. It indicates the tool explains meaning and next step. However, it could be slightly more specific about the output format (e.g., returns a text explanation).

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%, with the parameter already well-documented as a number from 0 to 100. The description does not add extra meaning about the parameter beyond what the schema provides, so baseline score 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 clearly states the tool explains an SYA structural readiness score and its next step, with a specific verb ('Explain') and resource ('readiness score'). It explicitly distinguishes itself by stating what it does not measure (AI answer rankings, mentions, etc.), setting it apart from potential sibling 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 provides clear negative guidance on what the tool does not do (measure AI answer rankings, mentions, citations, traffic), helping the agent avoid misuse. While it lacks explicit 'when to use' or alternatives, the sibling tools are distinctly different actions, making the usage context clear.

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 indicate readOnlyHint=true and destructiveHint=false, so the description reinforces safety by stating it does not create a checkout or purchase. This adds context beyond the annotations, making the behavioral profile clearer for the agent.

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 every word adds value. There is 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 simple retrieval tool with fully documented parameters and safety annotations, the description provides sufficient context: it returns links and does not mutate state. It could mention that the links are publicly accessible, but this is a minor gap given the overall clarity.

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 100% schema description coverage, the input schema already documents both parameters (package_id and currency). The tool description does not add additional meaning or context to the parameters beyond what the schema provides, so it receives the baseline score.

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 public detail and pricing links for a specific package, explicitly distinguishing from creating a checkout or purchase. The verb 'Return' and resource 'public detail and pricing links' are specific, and it is differentiated from sibling tools like 'list_packages' and 'scan_website.'

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 only mentions what the tool does not do (no purchase), but lacks explicit guidance on when to use it vs. sibling tools. For example, it does not suggest using this tool when you need to display or share package links, versus using 'list_packages' to enumerate options.

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 provide readOnlyHint, idempotentHint, and destructiveHint. The description adds context that the reports are 'limited public' and 'previews', which clarifies scope. It doesn't contradict annotations and adds 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 a single concise sentence (16 words) that immediately communicates the tool's purpose. No unnecessary words, front-loaded with 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 tool has only one optional parameter, good annotations, and no output schema, the description provides sufficient context. It covers the inputs and what the tool returns, making it complete for an AI agent to use 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?

Schema coverage is 100% and the description mentions the enum values (saas, api, ecommerce, web3) consistent with the schema. The description does not add significant new meaning beyond the schema's parameter description, so 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 states the action (Return), the resource (public SYA sample report previews), and the scope (SaaS, API, ecommerce or Web3). It distinguishes from sibling tools like scan_website or list_packages by specifying it returns a sample report preview.

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 fetching sample reports but does not provide explicit guidance on when to use vs. alternatives or any prerequisites. There are no exclusions or when-not-to-use details.

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 tool is safe. The description adds value by specifying the output includes localization and detail links, which is beyond the schema's minimal currency parameter.

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 front-loads the action and key outputs. Every word is necessary; no extraneous 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 list tool with no output schema, the description adequately describes what is returned (packages, prices, intended use, links). It does not mention pagination or limits, but given the likely small dataset, this is sufficient.

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 100% for the single 'currency' parameter, which has a clear description and enum. The description mentions 'localised USD/GBP/EUR prices', reinforcing the parameter's purpose, but adds no new information 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 clearly states the action ('List current SYA packages') and specifies the output includes localized prices, intended use, and detail links. It distinguishes itself from sibling tools which have different functions (e.g., 'explain_readiness_score', 'scan_website').

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 does not explicitly state when to use this tool versus alternatives, nor does it mention when not to use it. However, the sibling tool names are distinct enough that the purpose is implicitly clear.

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 description does not need to repeat these. It adds the fact that the tool is free and returns specific outputs. It does not disclose additional behavioral traits like rate limits, caching, or side effects beyond what annotations imply. With annotations present, this is adequate but not rich.

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 consists of two clear, front-loaded sentences. Every word serves a purpose: it specifies the action, authorization requirement, and output components. No unnecessary 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?

For a simple tool with one parameter, no output schema, and robust annotations, the description covers the essential context: authorization requirement, output details, and that it's a free preview. It is nearly complete, though slightly more detail on what 'readiness pillars' are could help.

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 100% coverage (one parameter 'url' with description). The description simply restates it as 'Public website URL or domain', adding no new semantic information. Baseline score of 3 is appropriate since schema already does the work.

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 ('Run') and identifies the resource ('public website') and the action ('structural AI-readiness preview'). It explicitly lists the returned data (score, grade, readiness pillars, package). This clearly distinguishes it from siblings like 'explain_readiness_score' or 'get_sample_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 states the tool is for websites the user owns or is authorized to assess, providing some context. However, it does not explicitly state when to use this tool versus alternatives (e.g., after scanning, use 'explain_readiness_score' for details). No exclusions or when-not-to-use guidance is given.

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