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

With no annotations, the description carries the full burden of behavioral disclosure. It does mention the $0.01 USDC/call cost, which is useful, but it does not state whether the operation is read-only, whether authentication is needed, or what the response contains. For a paid external API call, more transparency is expected.

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 that communicates the core purpose and the cost without filler. Every word 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 tool is simple, with one required and one optional parameter, so the description is minimally viable. However, there is no output schema and no description of the return format, pagination behavior, or query syntax, leaving some ambiguity for an agent invoking the 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 both parameters are documented: 'q' as Query and 'n' as Max results with a default of 5. The description adds no additional meaning beyond the schema, so the baseline score of 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 states 'Research paper search on arXiv,' which gives a specific verb (search), a specific resource (arXiv), and a domain qualifier (research papers). This clearly distinguishes it from generic siblings like x402_search and other x402 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?

There is no guidance on when to use this tool versus alternatives such as x402_search or x402_read. The description only implies that it is for research paper searches, without stating exclusions, prerequisites, or query construction tips.

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 of behavioral disclosure. It states the core function (discovering subdomains) and the cost, but it does not mention whether the operation is read-only, any authorization requirements, rate limits, or potential error conditions. The cost detail is useful, but other behavioral context is missing.

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 is front-loaded with the purpose and includes the cost. There is no filler or redundant information, making it efficiently structured for quick agent comprehension.

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 and no output schema, the description adequately conveys its purpose and what it returns (subdomains). However, it lacks details about the response format, pagination, or any limits, which would be helpful but are not critical for a straightforward lookup 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 coverage is 100% since the only parameter (domain) has a description 'Domain'. The tool description adds no additional meaning beyond the schema, so the baseline score of 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 uses a specific verb ('Discover') and names the resource ('subdomains from certificate-transparency logs'), which is distinctly different from sibling tools like x402_dns or x402_whois. It clearly communicates the tool's function without being a tautology of the name.

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 mentions the cost per call ($0.01 USDC/call), which implies a usage consideration, but it does not explicitly state when to use this tool versus alternatives (e.g., 'use x402_dns for live DNS lookups'). No exclusions or alternative routes are provided.

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 full burden of behavioral disclosure. It does reveal an important side effect: each call costs $0.02 USDC, and 'AI chat completion' makes the action clear. However, it does not mention response format, statelessness, or any error/rate-limit behavior, so some transparency gaps remain.

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 compact sentence that front-loads the purpose and includes the key cost detail. There is no filler, redundant wording, or unnecessary explanation; every element 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?

For a tool with a single string parameter and no output schema, the description is mostly complete: it states what the tool does and the cost of calling it. It could be more explicit about the return value and when to choose this over summarize or translate, but the simplicity and transparency of 'chat completion' make it sufficient for basic 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 schema covers the single 'message' parameter with 100% description coverage, so the baseline is 3. The description adds no parameter-specific meaning beyond the schema, but the parameter is simple and self-explanatory, so the baseline 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 the tool as an AI chat completion endpoint and adds the cost per call. It distinguishes itself from siblings like search or read by naming the specific resource and action, though it does not explicitly contrast with related tools like summarize or translate.

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?

There is no guidance on when to use this tool versus alternatives such as x402_summarize or x402_translate. The intended use is only implied by the phrase 'chat completion,' and no prerequisites, exclusions, or recommended alternatives are provided.

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 the full burden of behavioral disclosure. It does disclose the per-call cost ($0.01 USDC) and the live nature of the data, which is useful context. However, it omits authentication requirements, rate limits, error behavior, and data source details, leaving meaningful gaps.

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 core purpose and cost with no filler. Every word contributes useful information, making it highly efficient and easy for an agent to parse.

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 tool with one optional parameter and no output schema, the description plus schema cover the essential facts: the data returned, the unit, the cost, and the parameter. The description names the output fields, but minor omissions like response format and data source prevent a perfect score.

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 documents the single optional 'coin' parameter with an example and a default value, so schema description coverage is 100%. The description adds no additional parameter semantics beyond what the schema provides, so the baseline score of 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 names the resource (crypto) and the data returned (live price, 24h change in USD), which distinguishes it from sibling tools like x402_stock and x402_fx. It does not explicitly contrast itself with those alternatives, but the resource and metric are specific enough for an agent to infer the tool's 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 description implies the tool should be used when live crypto price and 24h change data are needed, but it provides no explicit when-to-use guidance, no exclusions, and no mention of alternative tools. This is implied usage rather than clear, actionable 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 full burden for behavioral disclosure. It only implies a read-only operation via 'lookup' and adds a cost note, but does not mention side effects, return format, network dependency, or any constraints. The minimal wording does not contradict anything but leaves significant behavioral context unstated.

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 extremely concise, a single sentence with no filler. The core action is front-loaded, and the cost is appended as a clear note. For a simple tool, this level of brevity earns a solid score.

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?

While the tool is simple (2 params, no output schema), the description leaves gaps: it does not explain what the result looks like, any limitations, or when to prefer this over sibling tools. The schema covers parameters, but without usage or output context, an agent may not fully understand the tool's scope.

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 clear descriptions for both 'domain' and 'type' (including default A). The description adds no additional meaning beyond what the schema provides, 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 action ('DNS records lookup') with a clear resource. While it doesn't explicitly differentiate from siblings like x402_whois, the 'DNS' qualifier makes the purpose unambiguous and distinguishable from other lookup tools to a reasonable degree.

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 no guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or exclusions, so an agent gets no help in routing between this and the many x402_* sibling 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?

With no annotations, the description must carry the full behavioral burden. It does disclose one meaningful trait (the $0.01 USDC/call fee), which is useful for an agent deciding whether to invoke it. However, it does not state read-only behavior, what the call returns, or failure/error characteristics, leaving significant gaps.

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 compact phrase with no wasted words. The price disclosure earns its place by adding operational information an agent needs before invoking a paid 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 zero-parameter tool with no output schema and no annotations, the description is adequate but thin. It identifies the resource and cost, yet does not explain what the tool returns (e.g., current index value, scale, interpretation) or how to use the result.

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 covers 100% of them, so the description is not required to add parameter meaning. The baseline of 4 applies; the description neither needs nor adds param details.

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 a specific, recognizable resource ('Crypto Fear & Greed index') which clearly identifies what the tool provides. It lacks an explicit verb like 'get' or 'returns', but the noun phrase makes the purpose inferable and distinguishes it from siblings like x402_crypto or x402_sentiment.

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 given on when to use this tool versus alternatives. The description only states the resource and cost, with no context about use cases, exclusions, or comparisons to sibling tools like x402_crypto.

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 does add useful behavioral context—per-call cost and the full-table mode—but it does not disclose what happens when both parameters are omitted, error behavior, or any rate-limit/auth concerns.

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?

A single sentence packs in the operation, the key usage exception, and the cost, all front-loaded with no filler. Every element 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?

For a simple two-parameter, read-like converter, the description covers the core call pattern, the table mode, and cost. It does not describe the response shape or the behavior when both arguments are absent, but those are minor given the tool's simplicity and the absence of an output schema.

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%, so the baseline is 3. The description adds meaning beyond the schema by explaining that omitting 'to' triggers the full-table response, which the schema's optional-parameter declaration does not convey.

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 concrete operation—currency conversion—rather than repeating the tool name. The added 'omit to for the full table' hint clarifies scope, though it does not explicitly differentiate from siblings like x402_crypto or x402_stock.

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 the use case (when currency conversion is needed) and gives one specific usage rule: omit 'to' to get the full table. However, it names no alternatives and provides no exclusions or conditions for 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?

With no annotations, the description carries the full burden of behavioral disclosure, but it only reveals the cost model ($0.01 USDC/call) and not what the call does, what data it accesses, whether it is read-only, or what side effects or rate limits exist. The pricing note is useful, but the operational behavior remains opaque.

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 extremely short and contains no wasted words, which is structurally clean. However, it is so terse that it veers into under-specification rather than effective conciseness, omitting crucial details an agent needs.

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 the low complexity (single parameter, no output schema), the description is incomplete: it never states what 'stats' means, what the response contains, or how success/failure is represented. With no output schema and no annotations, the description should compensate by explaining the return value, but it does not.

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 covers the single parameter fully with the description 'owner/name', and the tool description adds no further detail about how to format the repo string or what combinations are valid. Since schema coverage is 100%, 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 says 'GitHub repo stats', which identifies the domain and general resource, but it lacks a specific verb and does not say what kind of stats are returned (stars, forks, contributors, etc.). It is more informative than a bare tautology but still vague about the tool's exact function.

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 given about when to use this tool versus the many x402_* siblings, nor any mention of alternatives or exclusions. The only added context is the price, which says nothing about appropriate usage scenarios.

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 the full burden of behavioral disclosure. It only mentions the cost ($0.01 USDC/call), which is useful but not behavioral. It does not describe what happens for invalid inputs, missing data, response format, or any side effects. For a read-only data retrieval tool, this is a significant gap since the agent has no idea what to expect from the call.

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 core purpose and includes the cost, which is an important operational detail. It has zero fluff and is easy to parse. It could arguably be even more informative, but for what it covers, it is well-structured.

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 two simple parameters, no output schema, and no annotations, the description is the only source of context beyond the parameter names. It fails to specify the output format, whether the tool returns a list, how errors are handled, or any limitations. An agent calling this tool would not know if the result is a JSON array, a summary, or something else. This is a notable gap for a tool that otherwise has minimal 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?

The input schema has 100% description coverage for both parameters (year and country), so the schema already explains them adequately. The description adds no extra meaning beyond the schema—it merely restates that holidays are by country and year. Thus, a baseline of 3 is appropriate; the schema does the heavy lifting and the description offers no additional context.

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 the resource ('Public holidays') and the parameters (by country and year) clearly. It distinguishes itself from sibling tools like weather or stock by naming the specific domain. However, it uses a noun phrase rather than an explicit verb like 'get' or 'list', which leaves slight ambiguity about the exact operation (e.g., fetching a list vs. a single date).

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 the tool is for retrieving public holidays, which is obvious from the name and context. It does not explicitly state when to use it versus alternatives, but the sibling tools are so distinct (weather, crypto, etc.) that confusion is unlikely. No explicit 'use when...' guidance is given, so it relies on the agent inferring the purpose.

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?

Since no annotations are provided, the description carries the full burden. It does disclose the output type (PNG) and a key behavioral trait (cost of $0.05 USDC/call), but it omits other potentially relevant details like authentication requirements, rate limits, or non-deterministic generation behavior. This is adequate for a simple tool but not thorough.

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, efficient sentence that front-loads the core action and includes the output format and cost. Every word carries value, with no redundant or tangential 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 simple one-parameter tool with no output schema and no annotations, the description covers the essential invocation context: what it does, what it returns, and what it costs. It does not explain selection among sibling tools, but that gap is already addressed under usage guidelines.

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 baseline is 3. The description adds no meaning to the single 'prompt' parameter beyond what the schema already provides ('Image prompt'), relying entirely on the structured 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 tool performs AI image generation and returns a PNG image, which is a specific verb+resource pair. It does not explicitly differentiate from sibling tools like x402_render or x402_screenshot, so it misses the top score for sibling distinction.

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?

There is no guidance on when to use this tool versus alternatives such as x402_render, x402_screenshot, or x402_video. The description gives no contextual conditions or exclusions, leaving the agent to infer when image generation is appropriate.

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 present, the description carries the full burden of behavioral disclosure. It transparently reveals a cost of $0.02 USDC per call and the async nature (job ticket + polling), which are critical for an agent to decide whether to invoke the tool. 'Report' implies a read-only operation, which is acceptable even if not explicitly stated.

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 purpose is front-loaded, followed by cost and async handling. Every word serves a purpose.

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 cost, async return, and polling procedure including the job_type. Since there is no output schema, the final result is obtained through polling, which is explained. It is sufficiently complete for an agent to invoke and retrieve the result 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?

The input schema already provides 100% coverage for all three parameters (url, file, filename) with descriptive text. The description does not add new parameter-level meaning, but the either/or relationship between url and file is implied in the schema descriptions. 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 states the purpose precisely: it returns a full EXIF/file metadata report as JSON. This clearly distinguishes it from sibling tools like x402_read (file content) or x402_search, and the resource (file metadata) is 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?

It provides explicit operational guidance: the tool is async and returns a job ticket, which must be polled with x402_poll_job using job_type 'box'. This tells the agent exactly how to obtain the result. It does not mention when not to use it or alternatives, but the async flow is sufficiently clear for correct usage.

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 for behavioral disclosure. It discloses the cost per call ($0.01 USDC), which is a useful behavioral trait (pricing), but it does not mention side effects, rate limits, authentication requirements, or what the response contains. For a tool with no annotation safety hints, this is insufficient.

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 purpose and includes cost information. It is concise with no wasted words. However, it could be slightly more structured by separating purpose from cost, but for its brevity it is efficient and earns its place by adding the cost detail.

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 (one string parameter, no output schema), the description still lacks key context. It does not mention return format, pagination, or how the 'q' query affects results. It also doesn't explain how it differs from other content-fetching siblings (e.g., x402_read, x402_rss). The cost is the only extra context beyond the schema, which is insufficient for an agent to fully understand the tool's 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?

Schema description coverage is 100% – the parameter 'q' has a description 'News query' in the schema. The description adds no additional meaning beyond that. According to the rubric, baseline is 3 when schema covers parameters; the description does not compensate or elaborate beyond the schema, so a 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 states the tool returns 'latest news headlines' which clearly indicates a news query tool. It is specific enough to distinguish from siblings like x402_weather or x402_crypto, though it could be more explicit about whether it returns full articles or just headlines. The verb 'get' is implied but not stated; still, the resource 'news headlines' is clear.

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?

There is no guidance on when to use this tool versus alternatives. It does not mention when not to use it, nor does it reference any sibling tools. The only contextual hint is the cost, which is not a usage guideline. The agent is left to infer that it is for news queries from the resource name.

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 full transparency burden. It discloses two critical behaviors: the call is ASYNC and returns a job ticket, and it costs $0.02 USDC. It also names the polling tool and job type. It does not mention failure modes or rate limits, but the key side effect (billing) and execution model are clearly stated.

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 extremely compact: two sentences that front-load the purpose and cost, then immediately convey the async polling contract. Every clause earns its place and no redundant information appears.

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 tool with no output schema and no annotations, the description does well to explain the async job flow and cost. However, it does not clarify that at least one of url or file should be provided, even though the schema lists all parameters as optional. An agent could attempt a call with no inputs and fail. The final result content is also unspecified, though the polling pointer mitigates that 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 already has 100% description coverage for all three parameters (url, file, filename). The tool description adds no additional parameter-level meaning, so the baseline score of 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 tool's function: 'Image text extraction (OCR)'. This is a specific verb-resource pairing that distinguishes it from sibling tools like x402_image, x402_screenshot, and x402_pdftext. The async behavior is also flagged up front.

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 explicit post-invocation workflow guidance ('poll with x402_poll_job (job_type box)'), but it does not state when to choose this tool versus alternatives or when not to use it. Usage is mostly implied by the OCR purpose rather than explicitly scoped.

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 provided, so description carries full burden. It discloses async behavior, cost per call, and the polling mechanism. It does not mention error cases or authentication, but the core behavioral traits are covered.

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 wasted words. Key facts (cost, async, polling) are front-loaded. The structure is efficient and scannable.

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 essential context: async operation, cost, and how to get results. No output schema exists, but the job ticket and polling instruction are sufficient for a simple tool. Minor gap: no mention of error handling, but overall it's 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?

Schema description coverage is 100%, so each parameter already has a description. The tool description adds no extra meaning beyond the schema. Baseline 3 applies; no additional param semantics are provided.

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?

Description clearly states the tool does 'PDF text extraction' with a specific verb and resource. It is distinct from siblings by name and function, though it doesn't explicitly name a sibling it is not. The cost and async nature are also mentioned, adding clarity.

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 the async flow: returns a job ticket and instructs to poll with x402_poll_job with job_type 'box'. This gives clear follow-up steps. It does not mention when not to use it, but for a specialized tool, that's acceptable.

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 and does add one useful behavioral fact: the $0.01 USDC/call cost. It also implies the result includes coordinates. However, it does not disclose whether lat/lon are required inputs for coordinate-based search, how limits behave, or any rate/error behavior.

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?

A single sentence that front-loads the core purpose and includes the cost, with no filler or repetition of schema details. It is appropriately sized for a simple search 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 simple 4-parameter read tool with complete schema coverage, the description plus schema is minimally sufficient to make a basic query call. However, the ambiguous phrase 'with coordinates' and the lack of any return-format or default-limit information leave gaps, especially with no output schema and no annotations.

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 baseline is 3; the schema already documents query, lat, lon, and limit. The description adds only the example categories and the coordinate output, neither of which clarifies parameter meanings 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 action ('Find') and a clear resource category ('restaurants, shops, landmarks') with a notable output ('coordinates'), so an agent can tell this is a location/places search rather than a generic web search. It does not explicitly contrast with siblings like x402_search, but the resource scope is distinct enough to avoid confusion.

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 given about when to choose this tool over alternatives such as x402_search or x402_weather, nor any conditions or exclusions. The only extra context is the price, which does not help with tool selection.

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 burden. It discloses the async job-ticket return, the required polling destination and job type, and the USDC cost per call. It does not cover failure modes or permission requirements, but it communicates the core behavioral traits needed to invoke and track the job.

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 purpose and cost, then immediately gives the async polling behavior and the exact job_type to use.

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 two-parameter async tool with no output schema, the description supplies the essential workflow: input, cost, job ticket, and polling instructions. It could add authentication or failure details, but the referenced poll tool and schema cover most of what an agent needs to call and track the job.

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 schema already documents topic and script as alternatives. The description restates the 'topic or full script' relationship but adds no parameter-level detail such as length limits, mutual-exclusion enforcement, or format requirements.

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 the tool's function as producing an AI podcast episode from either a topic or a full script. It names the resource and input mode, and the async mention helps distinguish it from related media tools like x402_video or x402_tts, though it does not explicitly contrast them.

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?

It gives clear usage context: call this to create a podcast from a topic or script, then poll with x402_poll_job using job_type 'media'. It does not state when not to use it or name alternatives, but among siblings there is no direct podcast equivalent, and the async workflow is explicit.

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 of behavioral disclosureologist. It usefully states that polling is FREE, that it runs until the job finishes, and that it returns a download URL on completion. However, it does not disclose timeout/failure behavior, such as what happens when max_wait_seconds is exceeded or the job fails.

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 efficient sentence that front-loads the action, then packs in the prerequisite usage context, job_type mapping, and return value. Every clause earns its place and avoids unnecessary 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?

For a 4-parameter tool with no output schema, the description explains the workflow context clearly and specifies that the output is a download URL once the job completes. The schema covers timing parameters, and the description handles the crucial usage and return semantics, though it could add a note about error/timeout outcomes.

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 already has 100% parameter description coverage, including enum values and defaults. The description reinforces the job_type mapping but does not add meaning beyond what the schema provides, so the baseline score of 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 ('Poll an async x402.eleeth.com job') and explicitly identifies it as the follow-up to specific job-creating tools. It distinguishes itself from the many sibling x402_* tools by describing exactly which job_type values correspond to which preceding 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?

It explicitly says 'Use after' and maps the two job_type values ('media' and 'box') to the correct set of upstream tools. This tells an agent exactly when the tool applies, including the prerequisite workflow of first creating an async job.

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 must carry the full burden of behavioral disclosure. It reveals that the tool incurs a cost of $0.01 USDC per call and returns a PNG image, which are useful behavioral traits. However, it doesn't mention side effects, error handling, rate limits, or authentication requirements. For a simple generator, this is adequate but not comprehensive.

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 purpose (QR code generator) and includes the key behavioral note (returns PNG, cost). Every word earns its place, with 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 tool with two parameters and no output schema, the description covers the essential points: what it does, the output format, and the cost. It doesn't specify how the PNG is delivered (e.g., URL, base64) or any required headers, but given the tool's simplicity and lack of output schema, it is mostly complete. A mention of the response format would push it to a 5.

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%—both 'text' and 'size' are described in the schema. The description does not add additional parameter meaning beyond what the schema provides. The baseline for high schema coverage is 3, and the description doesn't elevate it by offering format details or edge-case guidance.

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 explicitly states the tool generates QR codes and returns a PNG image, with a clear verb and resource. This distinguishes it from sibling tools like x402_search or x402_image, which have different purposes. The cost note is additional context but doesn't obscure the core function.

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 no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where a different tool (e.g., x402_image for general image generation) might be preferred, nor does it state exclusions or prerequisites. The purpose is clear enough to infer usage, but explicit guidance is absent.

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 the disclosure burden. It does add important context: the call costs $0.01 USDC and the result is cleaned article text rather than raw HTML. However, it omits failure behavior, dynamic-content limitations, paywall handling, non-article pages, and rate limits, and 'any web page' may overpromise.

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?

A single, front-loaded sentence that conveys the action, output, and pricing without filler. Every phrase 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?

For a one-parameter tool with no output schema, the description adequately explains what it fetches, what it returns, and what it costs. It could be more complete with caveats about page types and failures, but the core contract is sufficient for simple 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 input schema already documents url as 'Page URL' with 100% coverage. The description adds no parameter-specific meaning beyond that, so it meets the baseline 3 but does not exceed it.

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 ('Fetch any web page') and the output ('return its clean article text'). This distinguishes x402_read from siblings like x402_search (web discovery), x402_screenshot/x402_render (visual output), and x402_metadata (page metadata).

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?

There is no guidance about when to use x402_read versus its many siblings, nor any exclusions or alternative routing. The description implies use for extracting article-like text from a specific URL, but it never says 'use this when...' or 'for X, use...'.

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 and does an excellent job: it discloses that the tool runs a real browser with JavaScript, is asynchronous (returns a job ticket), requires polling with a specific job type, and has a cost per call. It also notes the output format (clean text) implicitly. This gives the agent a clear behavioral model without relying on 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 concise—two sentences—with the core purpose front-loaded, followed by cost and async behavior. Every clause adds value: the real browser/JS detail, cost, async job ticket, and polling instructions. There is 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?

For a tool with a single parameter, no output schema, and no annotations, the description is complete. It tells the agent how to invoke it (url), what to expect (job ticket), how to get the result (poll), and the cost. The mention of job_type 'box' ensures the polling call is correctly parameterized. Nothing essential is missing for a 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 input schema has 100% description coverage for the single 'url' parameter, so the schema already documents it as 'Page URL'. The tool description adds little beyond referencing 'render a page', which aligns with the parameter. This meets the baseline of 3; it does not introduce additional semantics or format constraints.

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 ('Render') and resource ('a page in a real browser'), and clarifies that it includes JavaScript and returns clean text. It distinguishes itself from sibling tools (e.g., x402_read, x402_screenshot) by being the rendering tool. The async/polling note adds nuance without obscuring the core 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 description provides clear usage context: it is asynchronous and must be polled via x402_poll_job with job_type 'box'. It explicitly instructs the agent on how to handle the asynchronous response. However, it does not explicitly mention when not to use this tool or compare it to alternatives like x402_read, leaving some inference to the agent.

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 the full burden of behavioral disclosure. It mentions a cost of $0.01 USDC per call, which is useful, but does not disclose error handling for invalid URLs, response structure beyond 'JSON', timeout behavior, or whether authentication is required. For a paid API, this lack of transparency is a significant 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, concise sentence that immediately states the action and return type, then appends the cost. Every word serves a purpose, with no filler. It is appropriately front-loaded and avoids redundancy.

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 fetch tool, the description is mostly complete but leaves out important practical details. It does not specify the JSON structure (e.g., whether items are arrayed), how malformed feeds are handled, or if there are URL length limits. Given the absence of an output schema and annotations, the description could be richer, but for such a simple tool it 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?

Schema coverage is 100% with the parameter 'url' described as 'Feed URL'. The description adds the qualifier 'any RSS/Atom feed', which reinforces that the URL must point to a feed and not a general webpage. However, this is minimal added meaning beyond the schema, so a 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 tool fetches RSS/Atom feeds and returns them as JSON. It specifies the resource type (RSS/Atom) and the action (fetch), which distinguishes it from sibling tools like x402_news or x402_read that serve different content types. The one-sentence description is unambiguous about its core function.

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 RSS/Atom feeds but does not explicitly contrast with alternative tools or state when not to use it. While the purpose is specific, there is no guidance on edge cases like whether it handles only feed URLs vs. general web pages, or how it differs from x402_read. The absence of exclusions or alternatives leaves the agent to infer applicability.

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 full burden. It discloses the async behavior, the return of a job ticket, the PNG output, the per-call cost, and the dedicated hardware rendering. It does not mention error handling or ticket expiration, but the essential behavioral contract is clear.

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 wasted words. The first sentence delivers the core purpose and cost; the second provides the critical async polling procedure. The description is front-loaded and every clause 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?

For a tool with one parameter and no output schema, the description is remarkably complete: it specifies the return (PNG), the async ticket, the polling sibling with its job_type argument, and the cost. An agent can correctly invoke and complete the workflow without additional information. The only minor omission is the structure of the job ticket, but that is not needed 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 schema already documents the single URL parameter with 100% coverage. The description adds the nuance that the URL should be a full-page website, implying a web page rather than arbitrary content. This is marginal additional meaning above the schema, so the baseline of 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 states a specific action: taking a full-page website screenshot and rendering it as PNG. It distinguishes from sibling tools like x402_image and x402_render by specifying 'full-page website' and the async job ticket pattern. The format (PNG) and cost are also included, making the purpose unmistakable.

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 clearly explains the async workflow: call to get a job ticket, then poll x402_poll_job with job_type 'box'. This tells the agent the immediate next step and which sibling to use. It does not explicitly contrast with other screenshot-like tools (e.g., x402_render), but for a one-purpose tool this 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 carries the full burden of behavioral disclosure. It discloses the monetary cost ($0.01 USDC/call) and the return format (titles, URLs, snippets), which is useful. However, it does not explicitly state that the tool is read-only (though implied), nor does it mention rate limits, errors, or any side effects. The disclosure is partial but covers key functional aspects.

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 packs essential info: purpose, cost, and output. It is front-loaded with the core function. There is zero redundancy or fluff, making it highly efficient for an agent to parse.

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 search tool with only two parameters and no output schema, the description is largely sufficient. It states the return content and cost. It does not mention optional parameters or default behavior, but those are covered in the schema. The only notable gap is missing context about when to prefer this tool over sibling search variants, but for a bare search tool, it is fairly complete.

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 provides full descriptions for both parameters (query and num_results), covering 100% of the schema. The tool description does not add any new meaning to the parameters beyond what the schema states. It merely mentions what the tool returns, not details about the parameters. Baseline 3 is appropriate given the 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 tool performs a web search and returns titles, URLs, and snippets. It is specific enough to indicate general web search, but it does not explicitly distinguish itself from sibling tools like x402_news or x402_wiki, which are domain-specific searches. The verb 'search' and resource 'web' 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?

There is no guidance on when to use this tool versus alternatives. It does not mention that this is a general web search and that specialized searches (news, wiki, etc.) should use dedicated tools. The description offers no exclusions or contextual selection criteria, leaving the agent to infer usage from the name alone.

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?

Because no annotations are provided, the description carries the burden of behavioral disclosure. It does add useful context by stating the per-call cost in USDC, which is a meaningful side effect. It does not, however, describe the output format, failure behavior, rate limits, or whether any authentication is 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 a single short sentence with the core subject front-loaded and the cost parenthetically appended. It is scannable and contains no filler, though it is brief enough that some behavioral and usage responsibilities fall on the schema.

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-required-parameter tool, the ticker schema plus the description is enough to make a basic call. However, with no output schema, no annotations, and no relation drawn to sibling tools, it leaves the response shape and exact data scope unspecified.

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 ticker property already includes its type and an example ('AAPL'), so the structured schema carries the parameter meaning. The description adds no additional parameter detail, which aligns with the baseline score for full 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 phrase 'SEC company financial facts' names a concrete resource and makes the tool's domain clear, and the required ticker parameter tells the agent what input is expected. However, there is no explicit action verb like 'get' or 'fetch', and the description does not differentiate it from siblings such as x402_stock or x402_search.

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 no guidance on when to use x402_sec instead of related financial or search tools. No when-to-use conditions, exclusions, or alternatives are mentioned, so the agent must infer the appropriate 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?

The description discloses the per-call cost ($0.01 USDC/call), which is a behavioral trait not present in annotations or schema. It also implies the output is one of three sentiment labels. However, with no annotations, the description carries the full burden and does not cover auth, rate limits, or side effects, leaving some gaps.

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 includes the core task, output categories, and pricing. Every word is functional and front-loaded, with no filler or redundancy.

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 tool with one parameter and no output schema, the description is largely complete: it states the task, the expected output categories, and the cost. However, it does not specify the exact response format (e.g., string label vs. confidence score) and lacks usage context relative to siblings, though the simplicity keeps these gaps minor.

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%; the 'text' parameter is already documented as 'Text to analyze'. The description adds no further parameter-level detail (e.g., length limits, language support), so the 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 performs sentiment analysis and enumerates the output categories (positive, negative, neutral). It is specific and distinguishable from siblings by name and domain, but it does not explicitly contrast with any alternative 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 like x402_summarize or x402_translate. The description only states what the tool does, with no context for selection or 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 full behavioral disclosure. It only mentions the cost per call, which is useful, but it omits whether the operation is read-only, what exactly the audit covers, what the score means, or any potential side effects. The lack of output schema or return details leaves the agent guessing about the response format and content.

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 core purpose and includes a cost note. Every word earns its place; there is no filler or redundant phrasing. It is appropriately short for a simple 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?

Given the tool's simplicity (one parameter, no output schema), the description is still incomplete for an agent to decide when to use it. It does not explain what constitutes an SEO audit, what the score represents, or how it compares to related tools like x402_metadata or x402_render. The agent is left without enough context to determine suitability or interpret the result.

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 only parameter (url) with 100% coverage, so the description does not need to repeat it. The description adds no extra meaning beyond the schema, which matches the baseline of 3 for full schema coverage. No additional context like URL format or constraints is provided.

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 performs an instant SEO audit of a URL and returns a score. The verb 'audit' and resource 'URL' are specific, and the '$0.02 USDC/call' cost distinguishes it from sibling tools that serve other domains (search, read, chat, etc.). It is unambiguous about the core function.

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 no guidance on when to use this tool versus alternatives. It does not mention any conditions, exclusions, or comparisons to sibling tools like x402_metadata or x402_render. An agent has to infer that an SEO audit is distinct, but there is no explicit 'use this for SEO analysis' or 'not for other URL checks'.

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 present, so the description carries the full disclosure burden. It adds the useful pricing detail of $0.01 USDC/call, but it does not state whether quotes are real-time or delayed, what fields are returned, or whether any side effects exist. For a read-only quote tool, this is adequate but minimal.

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 extremely concise and front-loads the core operation. The pricing parenthetical is the only extra detail and is relevant for a paid tool, so every element 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?

This is a simple one-parameter, read-only tool with no output schema, and the description is nearly sufficient for an agent to select and use it. It could mention whether quotes are US-only or delayed, but the low complexity makes these omissions minor.

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 already documents the single 'ticker' parameter with an example, providing 100% coverage. The description adds no additional meaning about ticker format, supported exchanges, or market scope, so it stays at the baseline for 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 identifies the operation as a 'quote' and the resource as 'stock', which is specific and unambiguous. This clearly distinguishes it from siblings like x402_crypto, x402_fx, and x402_news even without naming them.

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 intended use is implied by the phrase 'Stock quote', but the description does not explicitly say when to prefer this tool over alternatives. There is no mention of when not to use it or which sibling might be more appropriate for related asset classes.

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 the full burden of behavioral disclosure. The description mentions the cost ($0.02 USDC/call), which is a behavioral trait, but it does not disclose the output format, error handling, or any side effects. It doesn't clarify whether this is a read-only operation or if it might have side effects (e.g., fetching and storing content). This is a significant 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, concise sentence that includes the core function and the cost. It is front-loaded with the action and resource, and every word serves a purpose. There is no unnecessary elaboration, making it highly efficient for an agent to parse.

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 only one parameter, and the schema covers that parameter. However, the description is extremely terse and lacks important context. It does not explain what the summary looks like (e.g., length, format, whether it's a text string or structured data), nor does it mention any limitations (e.g., paywalled articles, language support). Without an output schema or annotations, the description should compensate, but it does not.

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 describes the single parameter 'url' as 'Article URL', and the schema coverage is 100%. The tool description adds nothing beyond this; it merely states the purpose without elaborating on the parameter's syntax or expected format. Since the schema already documents the parameter, the baseline of 3 applies, and the description provides no additional value.

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 function: generating an AI summary of any article URL. It includes the specific verb 'summarize' and the resource 'article URL', making the purpose unambiguous. It also mentions the cost, which is a useful differentiator. Though it doesn't explicitly compare with siblings, the intent is clear.

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?

There is no guidance on when to use this tool versus its alternatives. The description does not mention any exclusions, prerequisites, or alternative tools (e.g., x402_read for full text). The agent is left to infer that this is for summaries, but no explicit direction is given.

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 present, so the description carries the full behavioral burden. It usefully discloses the $0.01 USDC/call fee and asserts broad language coverage, but it does not describe the response format, how target languages are specified beyond the schema, or whether any rate limits or payment prerequisites apply.

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 core action and then adds the only substantive non-schema detail, the per-call price. There is no filler, repetition, or unnecessary qualification.

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 two-parameter tool with complete schema coverage, the description and schema together provide the essential details: the required text input, optional target language, default behavior, and cost. A brief mention of what the tool returns could improve completeness, but the operation is simple enough that this is not a major 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 already describes both parameters fully: 'Text to translate' and 'Target language (default English)'. With 100% schema description coverage, the description adds no meaningful parameter-level information, so the baseline score of 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 uses a direct verb ('Translate') with a clear resource ('text') and scope ('into any language'), making the tool's function unambiguous. It is also distinct from sibling tools such as x402_summarize, x402_ocr, and x402_chat, so an agent can tell when translation is the relevant operation.

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 the usage context: use this tool when text needs to be translated. However, it provides no explicit when-not-to-use guidance, no alternatives, and no mention of limitations such as supported language coverage or formatting constraints.

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 full burden. It discloses the async behavior (returns a job ticket), the output format (mp3), and the monetary cost ($0.25 USDC/call). This is transparent for an operation that generates a file without destructive effects.

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 entire description is a single, information-dense sentence. It leads with the purpose, then covers cost, async behavior, and polling instruction — every word 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?

For a simple TTS tool, it covers the essentials: output format, cost, async workflow, and how to retrieve the result. It doesn't mention authentication or rate limits, but those are likely inherited from the broader x402 system and not unique to this 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% — the schema already explains 'text' and 'voice'. The description adds the cost and async context but doesn't introduce new parameter semantics beyond what the schema provides, 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 states the tool performs text-to-speech, producing spoken-word mp3 files. It names the resource (spoken-word mp3) and differentiates itself from siblings like x402_image or x402_chat by its specific function.

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 explicitly notes the async nature and instructs to poll with x402_poll_job, providing clear follow-up steps. It doesn't mention when not to use it, but for a single TTS tool, this is sufficient 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?

With no annotations provided, the description carries the full behavioral disclosure burden. It discloses the async nature (returns a job ticket), the polling requirement, cost ($0.50 USDC/call), and output characteristics (~10s 720p). It does not cover failure modes, auth, or rate limits, but the critical behavioral traits are present.

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 tightly packed sentences with zero fluff. The core action and output specs are front-loaded, followed by the essential async/polling instruction. Every clause adds operational 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 one-parameter tool with no output schema and no annotations, the description covers the full invocation path: input (prompt), output expectation (job ticket), follow-up action (poll x402_poll_job with job_type 'media'), and cost. It could detail the job ticket shape, but the agent has enough to call and proceed 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 description coverage is 100%, so the baseline is 3. The description adds that the prompt generates a video clip, which is somewhat redundant with the schema's 'Video prompt'. It does not enrich param semantics with prompt style, length limits, or formatting guidance, but no major gap exists given the single simple param.

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-resource pair ('AI video generation') with concrete output specs (~10s 720p clip from a prompt). This clearly differentiates it from sibling tools like x402_image and x402_tts, leaving no ambiguity about what the tool produces.

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 context for when to use the tool (when AI-generated video is needed) and explicitly instructs the follow-up step: poll with x402_poll_job using job_type 'media'. It lacks an explicit 'when not to use' or named alternatives for video vs. image/audio, but the async workflow and polling handoff are well specified.

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 the full burden of behavioral disclosure. It does usefully mention the source (archive.org) and the per-call cost ($0.01 USDC/call), but it never states what the returned 'snapshot' contains, whether it returns page content or metadata, or what happens when no snapshot exists.

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 compact sentence that conveys the tool's purpose, source, and cost with no filler. It is easy to parse and 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?

With no output schema and no annotations, the description should clarify what the tool returns and any operational caveats. It does not explain the return format, how 'closest' is determined, or behavior on missing snapshots, so the definition is not fully self-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?

The input schema already documents the single 'url' parameter with 100% coverage, so the baseline is 3. The description adds mild context by indicating the URL is the one to look up in archive.org, but it does not enrich the parameter with format or example guidance 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 identifies the resource ('a URL from archive.org') and the specific function ('closest archived snapshot'), which distinguishes it from sibling tools like x402_read or x402_metadata. It lacks an explicit verb like 'retrieve' or 'fetch', but the meaning is 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?

There is no guidance about when to use this tool versus alternatives, such as preferring it for historical/archived content or when a live URL is unavailable. With 35 sibling tools, the absence of any routing context is a notable gap.

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 disclose behavioral traits. It does mention the cost ($0.01 USDC/call), which is a key behavioral trait (transactional). However, it doesn't state whether the tool is read-only, has side effects, or requires authentication. For a simple query tool, the cost disclosure adds value but is incomplete given the absence of 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 sentence, extremely concise and front-loaded with the core functionality, then the cost. It contains no filler. However, it could be structured slightly better by explicitly mentioning the input (city) or output format, but it remains efficient and easy to parse.

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's simplicity (one required parameter, no output schema), the description provides the essential information: what it returns (current conditions and forecast) and the cost. It doesn't elaborate on response format or error handling, but for a weather query, this is likely sufficient. The absence of an output schema is mitigated by the description's mention of the returned data.

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% because the 'city' parameter has a description ('City name'). The tool description does not add any additional meaning or usage hints for the parameter. With full schema coverage, the baseline of 3 is appropriate; the description doesn't compensate further.

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 provides 'Current conditions + today's forecast' – a specific resource and outcome. The verb is implicit but the resource (weather) and the scope (current + forecast) are unambiguous. It distinguishes from siblings by domain, as no other weather-related tool exists among the listed siblings.

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?

There is no guidance on when to use this tool versus alternatives. It doesn't state conditions like 'Use for weather queries' or exclude scenarios. The agent must infer usage from the name and description alone, without explicit context or alternatives.

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 of disclosing behavior. It does disclose the $0.01 USDC/call cost and the use of RDAP, which is useful operational context, but it does not mention authentication, rate limits, response format, or explicitly confirm the operation is read-only.

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 that states the core function and the cost. There is no filler, and every word contributes essential 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 one-parameter lookup tool, the description is reasonably complete and includes the critical cost detail. However, it does not describe the return value or any limitations, and with no annotations the absence of safety or prerequisite information leaves some gaps.

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 has 100% description coverage for the single domain parameter, so the baseline is 3. The description does not add meaningful format or example details beyond 'Domain', but no compensation is required given the 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 identifies the resource (domain) and the operation (WHOIS via RDAP), so an agent can tell this is a domain WHOIS lookup. It is distinct from siblings like x402_dns or x402_certs by protocol and purpose, though it lacks an explicit verb such as 'retrieve' or 'lookup'.

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 given on when to choose this tool over alternatives, such as x402_dns or x402_certs, nor are prerequisites or exclusions mentioned. The only extra hint is the cost, which does not help with tool selection.

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 the full burden of disclosing behavior. It mentions the cost ($0.01 USDC/call), which is useful, but it does not disclose output format, error handling (e.g., topic not found), rate limits, or any other behavioral traits. The description is too sparse to inform the agent about what to expect beyond a 'summary'.

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, short sentence that front-loads the purpose ('Wikipedia summary') and includes the cost. It is appropriately concise for a simple tool with one parameter. However, it is almost too terse, but it does not waste words. The structure is clean and easy to parse.

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's simplicity (one parameter, no output schema), the description is minimally adequate but lacks depth. It does not describe the nature of the summary (e.g., length, language, format) or what happens if the topic is invalid. An agent might need to infer that the output is a text summary. For a micro-tool like this, it is functional but not rich; a slightly more detailed description would improve completeness.

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: the only parameter 'topic' is described as 'Topic'. The description adds no additional semantics about the parameter, such as expected format, length, or examples. Since the schema already fully documents the parameter, a baseline of 3 is appropriate; the description does not need to repeat it but could have added context like 'search term for Wikipedia'.

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 'Wikipedia summary' which clearly identifies the resource and action: retrieving a summary from Wikipedia. It is distinct from sibling tools like x402_search or x402_read because it explicitly names Wikipedia. However, it is terse and could be more explicit about the action (e.g., 'Fetches a Wikipedia summary for the given topic'), but it is unambiguous enough for an agent.

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 provide explicit when-to-use or when-not-to-use guidance relative to alternatives. The context is implied: if an agent needs a Wikipedia summary, this is the tool. But there are no exclusions or mentions of alternatives, such as using x402_search for broader queries or x402_read for full articles. It is minimal but not misleading.

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