ISO country PG

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

With no annotations, the description carries the full burden. It does disclose that the tool 'Returns' specific artifacts and that 'Task text discarded,' which is useful transparency. However, it does not explain whether network access occurs, whether pay-per-call charges apply beyond the name, what happens with the nine optional parameters, or what failure modes exist.

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 short, front-loaded with the main action, and each sentence adds distinct information: what it finds, what it returns, and that task text is discarded. It is appropriately sized even if somewhat cryptic.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, no annotations, nine optional parameters, and an unusual tool name, the description is not complete enough. It fails to explain why those nine parameters exist, how they relate to finding the gateway, what a 'remote MCP hop' is, or how an agent should choose and populate the parameters.

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 and the description is not required to repeat parameter details. It does not add meaningful parameter-level guidance, and the phrase 'Task text discarded' seems disconnected from the actual parameters. Still, each parameter is individually documented in 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 names a specific resource ('public pay-per-call tool gateway (Monid)') and a verb ('Find'), but the purpose remains vague because 'Monid' and 'pay-per-call tool gateway' are unexplained jargon. It does not clearly distinguish this tool from the many sibling utility tools, and 'agent-tool-index' as a name does not align with the stated gateway-finding behavior.

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 when-to-use guidance is provided, and no alternatives or exclusions are mentioned. The description implies you should call it when you need Monid gateway information, but it does not say how this relates to the sibling tools or what kind of task should route here.

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 disclosure. It reveals only that no browser is launched, but does not state whether a network request is made, what 'opened' means, or any side effects. This is thin coverage for an action verb like 'check.'

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 short sentences with no filler. The key behavioral scoping fact, 'No browser is launched,' is front-loaded and earns its place by differentiating from sibling tools.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has a complex, heterogeneous schema and no output schema. The description only states the primary action, ignoring parameter semantics, expected return values, or the role of extraneous fields. An agent would lack essential information to call it 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 description never mentions parameters, while the schema contains seven unrelated-looking fields (ref, city, feed, path, etc.). The url field is described as 'HTTPS URL to normalize or cite' in the schema, which conflicts with the tool's 'can be opened' purpose. The description adds no connective tissue to resolve this ambiguity.

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 clear verb-resource pair: 'Check whether a URL can be opened.' The second sentence, 'No browser is launched,' distinguishes it from sibling tools like playwright-url-ok. However, it does not define what 'opened' means (e.g., HTTP status vs. syntax), which keeps it from being fully 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?

No explicit when-to-use guidance or alternatives are given. The 'No browser is launched' note implies a lightweight, quick check compared to browser-based siblings, but this is left to inference rather than stated.

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 burden of explaining behavior, but it only says 'Expression discarded,' which is ambiguous about return values and side effects. It does not explain how the nine parameters are used, what the output looks like, or whether the tool is read-only or mutating.

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 short and front-loaded, which is good, but it is under-specified rather than appropriately concise. Two sentences do not provide enough structure to connect the stated purpose to the nine-parameter input 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 tool with nine parameters, no annotations, and no output schema, this description is completely inadequate for correct invocation. An agent cannot determine which parameter holds the expression, what the tool returns, or when it should be used.

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?

Although schema coverage is 100%, the description's core concept—an arithmetic expression—maps to no parameter in the schema. The per-parameter descriptions mention URLs, cities, JSON, and hostnames, which are unrelated to 'a+b style arithmetic,' so the description adds confusion rather than parameter clarity.

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 verb ('Evaluate') and a resource ('a+b style arithmetic'), but the input schema contains no arithmetic expression parameter. The phrase 'Expression discarded' also undermines the stated purpose, leaving an agent unsure whether evaluation actually happens or what input to provide.

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 no guidance about when to use calc-eval versus any of the sibling shape-check, validation, or fetch tools. It neither states a preferred context nor mentions alternatives 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?

With no annotations, the description must carry behavioral disclosure; it does add one useful guarantee ('Page content is not stored') and implies a read-only status check. However, it does not state that the tool performs a network request, what happens for invalid or missing URL, or how the host/scheme/status are returned.

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 front-loaded sentences, no filler: the result is stated first and the privacy caveat second. 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?

Given nine optional parameters, no output schema, no annotations, and many overlapping siblings, this description is too thin. It omits which fields to use or ignore, invocation context, and error or return behavior, so an agent cannot confidently select and invoke it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the parameter descriptions already carry the meaning; the tool description adds only the link between URL and the returned host/scheme/status. It does not explain how the other eight parameters relate to the stated purpose, which is acceptable only because the schema documents them.

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 concrete operation—return host, scheme, and HTTP status for a URL—and adds a privacy statement. It is clear about what the tool does but does not differentiate it from siblings such as fetch-status, normalize-url, or web-fetch.

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 instead of the many URL-related siblings, and no mention of which parameter(s) to pass among the nine optional fields. The only implicit hint is that it expects a URL.

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 statement 'No identifiers are retained' provides a useful privacy/retention guarantee, which is especially relevant because multiple schema parameters describe discarded inputs. However, with no annotations, the description still does not disclose whether the tool is read-only, makes external calls, or returns any meaningful state change. It gives one behavioral fact but not a complete operational picture.

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 short sentences with no filler. The privacy statement earns its place. However, the first sentence is so vague that brevity comes at the cost of clarity, so it does not quite reach a 5.

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 tool has nine optional parameters, no annotations, no output schema, and a large set of siblings. The description does not explain what the classification output looks like, what categories or formats are produced, or how an agent should choose inputs. The schema descriptions help per-parameter, but the overall context is inadequate for a tool this complex.

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, with each parameter explaining what it is and often that its value is discarded. The tool description itself adds no parameter-level meaning beyond the generic 'request' wording. Since the schema carries the burden, 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 says the tool will 'Show how this request is classified,' but it never specifies what a request is, what classification categories exist, or what resource the tool operates on. The name 'compatibility' hints at a purpose, but the description does not connect that name to the behavior, and it does not distinguish this tool from the many sibling shape/validation tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No conditions, contexts, or alternatives are given. The description does not explain when an agent should prefer this tool over siblings like validate-json, file-path-ok, or domain-shape, and it offers no exclusions. The only guidance is implicit and too weak to route an agent correctly.

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 disclosure burden, but it only reveals that the tool does not consult WHOIS or ownership data. It does not state whether the operation is read-only, what it returns, how invalid input is handled, or how the many non-host parameters are treated. The schema's 'discarded' notes add some context, but they are outside the description itself.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with an active verb and no filler. It loses a point because its brevity omits the tool's broader input surface, making it concise but under-explanatory relative to the actual 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?

The tool has nine optional parameters, no output schema, and no annotations, so the description must explain the general input model and expected behavior. It only addresses `host`, leaving the other eight properties unexplained at the description level, and it never states whether parameters should be used individually or in combination. The schema descriptions help, but the overall contract is too incomplete for reliable agent selection.

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 even though the description adds no parameter-level detail. The schema already explains each optional property, such as `json` being 'JSON text to validate; discarded after the check.' The description's mention of hostname maps only to `host` and provides no additional semantic value 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 names a concrete action ('Split a hostname into labels') and an exclusion ('without WHOIS or ownership data'), so it is not a tautology. However, it covers only one of the nine input properties in the schema (`host`), leaving `url`, `json`, `path`, `query`, and others unaddressed. The tool's actual scope is therefore ambiguous: it reads like a hostname-only parser while the schema suggests a broader shape-validation utility.

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 phrase 'without WHOIS or ownership data' implies a boundary around pure shape parsing, but the description never states when to choose this tool over siblings like `normalize-url`, `browser-url-ok`, `file-path-ok`, or `validate-json`. No alternatives, exclusions, or explicit conditions are given. The intended usage is only inferred from the verb 'split a hostname.'

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 and does disclose the key facts: it issues a HEAD request (so no body is retrieved), targets public URLs only, and returns only status. It does not mention redirects, timeouts, or error behavior, but the core side-effect profile 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?

The description is a single front-loaded sentence with no filler: verb, target, and output constraint. 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 tool with 9 optional parameters, no annotations, no output schema, and many sibling URL/status tools, this one-sentence description is incomplete. It lacks parameter-selection guidance, relationship to siblings, and the shape of the returned status.

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?

Every parameter has a schema description, but those descriptions describe unrelated operations such as normalizing/citing URLs, weather hints, RSS titles, JSON validation, and timezone names. The description never identifies `url` as the target for the HEAD request, and with 0 required parameters among 9 the agent cannot reliably know what to pass.

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 (HEAD), a target (public URL), and an output constraint (status only), which clearly separates it from content-fetching tools like web-fetch. It is clear but does not explicitly name sibling alternatives, so it stops short of full differentiation.

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 phrase 'public URL' and 'status only' imply it is for lightweight reachability checks of public endpoints, not for content or authenticated URLs. However, there is no explicit when-to-use versus browser-url-ok, web-fetch, or normalize-url, and no exclusions or prerequisites.

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 bears full responsibility for behavioral disclosure. It only mentions that the path is discarded, but gives no indication of whether the tool validates, extracts, normalizes, or returns anything, nor how it handles invalid or non-Figma URLs. This is a significant transparency gap for a parse operation.

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, with no filler words. It front-loads the purpose and adds one behavioral note. The fragment 'Path discarded' is a bit terse but not verbose, and the overall length is appropriate for a simple shape-check 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 9 parameters with none required, no output schema, and no annotations, the description leaves too much unspecified. It doesn't explain which parameter contains the Figma URL, what the return value looks like, how the discarded parameters interact, or how the tool is meant to be used among the family of shape tools. The mismatch between the single-purpose description and the broad generic schema makes the tool confusing to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so each parameter already has a description, giving a baseline of 3. The tool description adds the important context that the URL should be a Figma file URL, which the schema's generic 'HTTPS URL to normalize or cite' does not convey. However, it doesn't clarify the roles of the other eight parameters or which are relevant, so it doesn't fully compensate for the schema's ambiguity.

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 ('Parse') and resource ('Figma file URL'), making the core action clear and distinguishing it from generic URL tools like normalize-url or browser-url-ok. The second sentence adds a scoping constraint, but it doesn't clarify what the parse produces, so it stops short of perfect 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?

There is no guidance on when to use this tool instead of sibling shape/URL tools such as github-repo-shape, domain-shape, or normalize-url. The description doesn't state prerequisites, intended input format, or exclusions, 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?

With no annotations, the description carries the full burden of behavioral disclosure. It reveals one useful trait (no disk access) but does not describe return values, what counts as safe, validation behavior, or side effects. This is especially limited for a tool with nine parameters and no output schema.

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 short and front-loaded with the core purpose. Both clauses are meaningful and avoid filler. It is concise, though arguably too terse for a tool with this many parameters and no output 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?

The tool has nine parameters, no annotations, and no output schema, so the description needs to explain return values and call context. It only addresses paths and ignores the url, json, city, feed, and other parameters. This is a significant completeness gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% parameter description coverage, so the baseline is 3. The tool description itself adds no parameter-level meaning; it only mentions 'path' while the schema documents many other optional parameters. The schema descriptions carry the semantic load, so no penalty beyond baseline is warranted.

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 and resource: checking whether a path looks safe, and adds a meaningful qualifier ('No disk access'). It is not a tautology and gives some separation from tools that access the filesystem or network. However, it does not explain what 'safe' means, and the schema lists many unrelated parameters that are not addressed.

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 no explicit guidance about when to use this tool versus siblings like normalize-url, validate-json, or browser-url-ok. The 'No disk access' hint implies a lightweight shape check, but there are no prerequisites, exclusions, or conditions stated.

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 reveals the output and data source, but does not disclose that most of the nine schema fields are 'discarded,' which parameters are actually used, what the coordinate format is, or that an external API call may be made.

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 single sentence is concise, front-loaded, and free of filler. However, it is so minimal that it provides little structure to help an agent navigate the 9-parameter 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?

With nine optional parameters, no output schema, and no annotations, the tool needs substantially more contextual detail. The one-sentence description omits which parameter to use, what happens with the other fields, the return format, and external API implications, leaving the agent to guess.

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 even though the description adds no parameter-level detail. The description does not clarify that 'city' is the relevant input for coordinates, nor does it reconcile the other eight parameters with the stated purpose, so it provides no added semantic 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 states a specific output ('latitude and longitude') and a data source ('Open-Meteo'), so an agent can identify this as a coordinate lookup tool. However, it does not name the relevant input such as 'city' and does not differentiate it from the sibling weather-hint tool, which also deals with places and Open-Meteo.

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 geo-hint versus alternatives, no mention of exclusions, and no reference to sibling tools. Given the large sibling list including weather-hint and timezone, the agent is left to infer when this tool 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?

There are no annotations, so the description carries the full burden, but it only states the parse action. It doesn't disclose whether the tool returns parsed owner/repo, validates URL shape, rejects invalid URLs, or ignores the many unrelated parameters (city, feed, timezone, etc.) present in the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler or repetition. Every word contributes to stating the core operation.

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 9 optional parameters, no annotations, and no output schema, a one-sentence description is badly incomplete. It fails to explain the presence of unrelated parameters, return behavior, error handling, or how to choose/call the tool 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 documentation coverage is 100%, so the baseline is 3; each parameter already has a description. The tool description adds the useful clarification that the url parameter is meant to be a GitHub URL whose owner/repo should be extracted, but it adds no detail about the other eight parameters or how they interact.

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 action ('parse'), a specific resource ('a GitHub URL'), and the expected extracted values ('owner and repo'), so an agent can distinguish this from generic URL tools like normalize-url or domain-shape. However, it doesn't clarify how it relates to the odd set of input parameters, which weakens clarity slightly.

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 when-to-use guidance is given beyond the implication of 'GitHub URL'. It doesn't say when to prefer this over sibling tools such as normalize-url, figma-url-shape, or domain-shape, nor does it mention exclusions such as non-GitHub URLs, invalid formats, or malformed input.

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 does disclose that titles are discarded and implies a read-only count operation. However, it doesn't explain whether any of the nine accepted parameters are used or ignored, how 'current' data is obtained, or what the result shape is beyond a count.

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 short sentences, each with a purpose. The core action is front-loaded and 'Titles discarded' is a useful clarification with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description makes the no-required-parameter invocation reasonably clear and notes a key output detail, but with no output schema and nine optional parameters, it fails to state the output type or how the parameters (especially feed) relate to the tool. An agent can call it, but may be uncertain about custom inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema documents all parameters without help from the description. The description adds no parameter-specific meaning and doesn't clarify which optional parameter, if any, is actually relevant to the HN count.

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 operation: count current Hacker News front-page stories. It doesn't explicitly align or contrast with sibling tools, but the specific resource (HN front page) makes 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 select this tool over siblings like web-fetch, fetch-status, or memory-key-count, and no mention of prerequisites or alternatives. The description simply states the function, leaving usage decisions to inference.

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?

There are no annotations, so the description carries the full burden. It hints that the tool provides a static list of common names, but it never discloses what a call returns, whether the many parameters affect the result, or any side-effect profile. This is too thin to predict tool 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?

The description is a single, compact phrase with no wasted words and the key noun ('IANA timezone names') front-loaded. It is concise, though it reads as a noun phrase rather than a complete sentence, which slightly reduces structural clarity.

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, no annotations, 9 parameters, and a large sibling set, a one-phrase description is far from complete. It does not explain what the tool returns, how parameters are used (or ignored), or how this relates to sibling clock/timezone tools.

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 each of the 9 parameters individually described, so the schema already carries the parameter semantics. The description adds no parameter-level meaning, but the baseline of 3 applies because the schema documents the parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies the resource ('IANA timezone names') and a context ('for clock calls'), but lacks any verb stating what the tool does — it does not say it returns, lists, or validates these names. It also does not distinguish it from sibling tools like 'timezone' or 'utc-time', leaving the purpose somewhat vague.

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 phrase 'for clock calls' offers an implied usage context: use this when you need timezone names to feed into clock-related tools. However, there is no explicit when-to-use guidance, no mention of alternatives, and no exclusions, so the agent must infer from the 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?

The description discloses that this performs a network fetch and returns only group counts, not the full robots.txt content. However, there are no annotations and no mention of error behavior, response format, or side effects, so the behavioral disclosure is only partially complete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no filler. It communicates the action, target, and output constraint efficiently.

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 nine optional parameters, no output schema, and no annotations, this one-sentence description is not enough for an agent to confidently invoke the tool. It lacks guidance on which parameter supplies the robots.txt URL, what 'group counts' look like, and how failures are reported.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents each parameter individually. The description does not clarify which parameter carries the robots.txt target URL, and several schema descriptions ('HTTPS URL to normalize or cite', 'Public hostname', 'File path to check') leave that mapping ambiguous, but the schema coverage keeps this at baseline.

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 ('Fetch') and a specific resource ('a public robots.txt'), and it constrains the output ('return group counts only'). It is clear enough to identify the tool's core purpose, though it does not explicitly differentiate it from sibling fetch or URL tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to use this tool versus alternatives like web-fetch, fetch-status, or normalize-url. There are no stated exclusions, prerequisites, or conditions that would help an agent choose between this and similar 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 at all, the description carries the full burden of behavioral disclosure. It only says 'Key discarded,' hinting that the input is not retained, but it does not state whether the tool returns a boolean, throws on invalid input, performs network calls, or has side effects. This is too thin for an unannotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two compact sentences with no filler, and the core purpose is front-loaded. It is efficient, though extremely terse. The missing information is a completeness issue rather than a conciseness issue, so conciseness itself is good.

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 nine parameters, no annotations, and no output schema, this description is far from complete. It does not identify which parameter receives the Jira key, what result to expect, or what 'key discarded' means operationally. The tool is practically impossible to invoke correctly from the provided context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds no parameter meaning. More critically, the schema has nine string parameters, none of which is explicitly described as a Jira issue key. The only param mentioning 'shape check' is 'ref,' described as a 'Git ref name,' which is not the same as a Jira key. An agent cannot map 'Jira issue key' to any schema property with confidence.

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 and resource: 'Check a Jira issue key shape.' This is more than a tautology because it adds a verb and a domain-specific object, and the appended 'Key discarded' gives a small behavioral clue. However, it does not distinguish among sibling shape-checking tools (e.g., github-repo-shape), so it stops short of full differentiation.

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. The description gives no context, exclusions, or alternative tool suggestions. An agent would have to infer use cases from the name alone, which is insufficient for reliable 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 present, so the description carries the full behavioral disclosure burden. It reveals only that the body is discarded, but it does not explain whether this makes a network request, what the response shape looks like, or how the other input parameters behave. For a tool with many potential inputs and no annotation safety signals, 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 only two short sentences with no filler or repetition. The key behavioral fact, that the body is discarded, is front-loaded. However, it is concise to the point of omitting important context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 9 parameters, no annotations, and no output schema, the description is far too incomplete. It does not explain the return value beyond 'HTTP status,' does not specify which parameter is relevant, and provides no context for the unrelated schema fields. An agent cannot confidently invoke this tool correctly across its supported inputs.

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 even though the description adds no parameter-level information. The description does not help clarify which of the 9 parameters should be used for the stated library-docs purpose, but the schema itself documents each parameter adequately.

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 outcome — HTTP status for a public library docs URL — but lacks a clear action verb and is much narrower than the 9-parameter input schema, which also accepts city, feed, host, json, path, zone, query, and ref. This mismatch makes the tool's actual scope ambiguous. It does not distinguish itself from siblings like fetch-status or browser-url-ok.

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 any of its many siblings. No alternatives, exclusions, or context are provided, so an agent must guess whether this is the right tool for a given URL-checking task.

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

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

With no annotations, the description carries the behavioral disclosure burden. It adds one useful behavioral trait: values are discarded, meaning the result is just a key count rather than a parsed object. However, it does not disclose the return shape, behavior on invalid or empty JSON, or whether the operation has any side effects beyond the discard note.

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 very compact and front-loaded: two short sentences with no filler. It is efficient, though the omission of input mapping and output details makes it slightly under-specified rather than optimally informative.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, nine optional parameters, and a large set of sibling tools, this two-sentence description leaves important decisions unresolved: which parameter to provide, what the count is returned as, and what happens on invalid input. It is not complete enough for confident 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?

Schema description coverage is 100%, so the baseline is 3 even without parameter detail in the description. The description adds no explicit mapping between 'JSON object' and the 'json' string parameter, and its singular object language is somewhat at odds with a schema of nine optional string parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a clear verb-resource pairing ('Count keys in a JSON object') and states that values are discarded, which conveys the core operation. However, it does not connect 'JSON object' to any of the nine input parameters, and the tool name suggests memory-related semantics that the description does not explain.

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, and no sibling tools are mentioned. The description does not state conditions such as 'when you need only the number of keys' or 'instead of validate-json', leaving invocation decisions to inference.

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 fully disclose behavior. It does reveal that query and fragment are dropped, but it does not explain that most of the nine schema parameters appear to be ignored or discarded, nor does it clarify the relationship between the output 'path'/'host' and the similarly named input parameters. Error behavior and return format are also unspecified.

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, and the primary behavior is front-loaded. The description is appropriately terse in style, though the tool's nine-parameter schema might justify a bit more 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?

There is no output schema and no annotations, and the description covers only the single happy-path case of a URL. It leaves unexplained the rest of the input schema, the meaning of 'cite', the exact return structure, and what happens with invalid or non-URL input, so an agent cannot confidently call it in varied contexts.

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 the URL-centric behavior but does not clarify how url relates to the other eight parameters or resolve the naming collision between output path/host and input path/host. It neither significantly enhances nor contradicts 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 names a specific verb ('Return') and a concrete resource ('origin, host, and path for a URL'), and it adds the key behavior that query and fragment are dropped. It is clear but does not contrast with sibling URL tools such as browser-url-ok or web-fetch, so it stops short of full differentiation.

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 explicit when-to-use guidance, no mention of alternatives, and no statement of what cases are excluded. An agent can infer that the tool is for extracting URL components, but the description never says when to choose normalize-url over a sibling 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 available, the description carries the full burden of behavioral disclosure. It only states that no browser is launched, but does not say whether a network request is made, whether the check is read-only, how results are returned, or what 'opened' means. The schema's 'discarded' notes hint at non-persistence, but the description itself 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 genuinely concise and front-loads the main action, with no wasted words. However, the brevity is achieved by under-specification: for a tool with seven parameters and multiple implied behaviors, two sentences are not an appropriately sized description.

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 complex seven-parameter schema, no annotations, and no output schema, this description is severely incomplete. It does not explain the return value, the meaning of 'opened,' how the other parameters relate, or any side effects. An agent cannot confidently call this tool correctly based on the description alone.

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 100% description coverage, so the baseline is 3, but the tool description fails to add context and actually conflicts with the schema: the `url` parameter is described as 'HTTPS URL to normalize or cite' while the tool description says it checks whether a URL can be opened. The description also gives no explanation for the unrelated parameters (ref, city, feed, host, json, path), increasing confusion.

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 clear verb and resource ('Check whether a URL can be opened') and adds a key modifier ('No browser is launched'), which lightly distinguishes it from browser-launching siblings. However, 'can be opened' is ambiguous—it could mean syntactic validity, HTTP reachability, or something else—and the description ignores the seven input parameters, leaving the tool's real scope unclear.

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 sibling tools such as normalize-url, fetch-status, web-fetch, or browser-url-ok. The only implicit hint is the negative 'No browser is launched,' which suggests using it when avoiding a browser, but it never spells out the selection criteria or 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?

No annotations are provided, so the description carries the disclosure burden. The statement 'Query discarded' usefully signals that the input is not stored or persisted, which is a genuine behavioral trait. However, the description omits the return format, error behavior, and what happens when multiple parameters are supplied, leaving important behavior undisclosed.

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 short sentences with no filler. 'Count characters in a search query' is front-loaded, and 'Query discarded' is a relevant, non-redundant addition. 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?

There is no output schema and no annotations, so the description alone must explain return values and usage context. It does not state that the result is a character count integer, nor does it clarify whether only the 'query' parameter should be supplied despite the nine optional schema properties. For a tool with this much schema surface area, the description is too thin for an agent to invoke it correctly without guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all nine parameters, including 'query' as 'Search text; discarded after the length check.' The tool description adds no new parameter meaning beyond the word 'search query,' and it does not clarify the role of the other eight optional parameters. Baseline of 3 applies because the schema carries the semantic load.

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 action ('Count characters') and a clear resource ('a search query'), and the phrase 'Query discarded' adds a meaningful scope detail. It does not explicitly set itself apart from sibling count/shape tools like memory-key-count or hn-front-count, but the verb-resource pair is specific enough.

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 memory-key-count, hn-front-count, or other length/shape utilities. The description implies a simple character-count use case but gives no exclusions, prerequisites, or comparison to 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 carries the full behavioral transparency burden, but it only says 'short catalog'. It does not disclose whether the tool performs network access, reads files, validates input, returns data, or simply presents static information.

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 short, but it is under-specified rather than efficiently concise. Important operational and usage details are absent, so the brevity does not serve the agent well.

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 9 optional parameters, no output schema, and no annotations, a one-line noun-phrase description is severely inadequate. It does not explain how to invoke the tool, what parameters are for, what the response contains, or when this tool is relevant.

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 parameter descriptions in the input schema already provide baseline meaning. The tool description adds no extra parameter-level context and does not explain why the nine optional parameters relate to an HTTP status code catalog.

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 resource ('common HTTP status codes') but never states an explicit operation such as 'returns', 'lists', or 'looks up'. It is more informative than a pure tautology, but the 9 unrelated optional parameters in the schema leave the actual purpose ambiguous.

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 about when to use this tool instead of sibling tools like fetch-status, web-fetch, or normalize-url. The agent must infer the intended use case with no explicit context 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?

The description discloses a key behavioral trait: 'Prompt discarded.' Combined with the per-parameter schema notes saying each value is 'discarded after the shape check,' an agent can infer that inputs are not used for the final output and there are no side effects. However, with no annotations, the description carries the burden and still does not explicitly state that the returned template is fixed or that all parameters are safely ignored.

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: two sentences with the core purpose front-loaded. 'Prompt discarded' is economical and conveys an important behavior. Slightly more clarity about what the template actually contains would be beneficial, but nothing in the description is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should explain what the returned template looks like or at least state that it is fixed and can be produced with no arguments. Instead, it only says 'three-step thinking template' and 'Prompt discarded.' The tool has nine optional parameters, and while the schema shows they are optional, the description never clarifies that invoking with no parameters is the intended or sufficient usage.

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 provides 100% description coverage for all nine parameters, so the baseline is 3. The tool description itself adds no parameter-level meaning. The schema descriptions, while noting each parameter is discarded, also give plausible semantic hints like 'HTTPS URL to normalize or cite,' which could mildly confuse an agent about whether the tool performs those actions.

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 and resource: 'Return a three-step thinking template.' This clearly distinguishes the tool from the sibling utilities, none of which promise a thinking template. However, the phrase 'thinking template' is not expanded, and 'Prompt discarded' adds a slightly ambiguous note about the tool's relationship to the user prompt.

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 no guidance about when to use this tool versus any alternative. It neither names sibling tools nor explains conditions under which a three-step thinking template would be appropriate. The only implicit signal is 'Prompt discarded,' which suggests the prompt should not be relied on, but that is not usage 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?

No annotations are provided, so the description carries the full burden. It communicates a read-only time lookup but fails to mention invalid timezone handling, return format, underlying data source, or whether any network access is involved.

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 short, front-loaded sentence with no redundancy. It is concise, even though it omits operational detail that belongs to other dimensions.

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 definition should at least clarify return format and parameter mapping. It does neither, and the schema's unrelated parameters make the tool difficult or impossible to call 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?

Although schema parameter descriptions exist, the visible properties are ref, url, city, feed, host, json, and path—none of which is an IANA timezone identifier. The description does not connect its 'named IANA timezone' requirement to any actual parameter, making correct invocation impossible from this definition.

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 resource: current time for a named IANA timezone. It is distinguishable from siblings like utc-time and iana-zones, though it lacks an explicit verb such as 'get' or 'return'.

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—retrieving current time for an IANA timezone—but it does not explicitly state when to prefer this tool over utc-time or iana-zones, and it gives no exclusions or prerequisites.

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 only states the output and does not disclose that the many accepted parameters are discarded or ignored, that no disk/network access occurs, or what timestamp format is returned. The description is result-focused, not behavior-focused.

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 noun phrase with no filler or repetition. It is concise and easy to process, though it is so terse that it borders on under-specification.

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 a seven-parameter input schema containing unrelated-looking fields, the description should explain how those parameters relate to the call or at least note that they are ignored. It provides neither, and it also fails to specify the timestamp format, so the agent must inspect the schema and infer behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema documents all seven parameters with per-property descriptions, such as 'discarded after the shape check' and 'no disk access,' so schema coverage is high. The tool description itself adds no parameter-level meaning, which is acceptable given the schema's rich coverage, but it also does not clarify why such unrelated parameters exist on a UTC-time tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description, "Current UTC timestamp," communicates that the tool returns the current time in UTC, which is a clear enough resource and timezone qualifier. However, it lacks a verb and is almost a restatement of the tool name, and it does not differentiate this tool from sibling tools like timezone.

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 explicit guidance about when to use this tool versus alternatives such as timezone or iana-zones. The intended usage is only implied by the tool name and the word 'UTC'; no exclusions or alternative routing 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 disclosing side effects. It does state that the body is discarded, which is useful behavioral information, but it does not disclose return behavior, error handling, or what happens with invalid JSON.

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 short sentences with no filler. The side-effect disclosure earns its place and the core purpose is 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?

There is no output schema and no annotations, so the description should explain expected results. It does not state whether the tool returns a boolean, an error, or a report, and it does not clarify which of the nine optional parameters should be treated as the body.

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 parameter-level guidance beyond what the schema already provides, and it does not explicitly connect 'body' to the 'json' parameter.

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 action and resource: check whether a body is valid JSON. It distinguishes the tool's core function, though it does not explicitly differentiate it from sibling shape-checking tools and leaves the term 'body' slightly ambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: whenever JSON validity needs to be checked. It provides no explicit exclusions or pointers to alternative tools, so the usage guidance is adequate but not strong.

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 not mention that this is a read-only external lookup, how errors for unknown cities are handled, or that all other input parameters are effectively ignored. The schema descriptions mention discarding, but the main description adds little beyond the data source.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. It communicates the essential purpose and provider in few words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite the high schema coverage, the overall tool context is under-specified: there is no output schema, no annotation, and no explanation of how the nine optional parameters relate to the weather lookup. An agent seeing this description may not know which parameter to populate or what exact result shape to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents every parameter, including that non-relevant values are discarded. The description adds only the provider context and reinforces 'city' as the relevant input, but it does not meaningfully extend the schema's parameter explanations.

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 resource (current temperature), the target (a city), and the data provider (Open-Meteo). It is distinguishable from siblings like geo-hint, but it is phrased as a noun phrase rather than an explicit operation like 'Returns current temperature...'.

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 no guidance on when to use this tool versus alternatives such as geo-hint, nor does it clarify that among the nine input parameters, only 'city' is the meaningful one. It is left to the agent to infer usage from the schema.

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 behavioral disclosure burden. It does disclose a key trait, 'Body discarded,' and limits scope to public URLs, but it omits details such as HTTP method, redirect handling, error behavior, or any server-side 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?

Two short sentences front-load the purpose and then state the most important behavioral caution. There is no filler, and both sentences earn their 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 seven input parameters, no output schema, and no annotations, this description is too thin. It leaves unclear which parameter to pass, what the response shape is, and how this tool relates to several similar sibling tools.

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?

All seven parameters have schema descriptions, including explicit 'discarded' notes for several fields, so schema coverage is high. The description does not clarify which parameter is the authoritative URL to fetch or how 'url' (described as 'normalize or cite') relates to fetching, but the baseline of 3 is appropriate given the rich schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it returns HTTP status and content type for a public URL, and adds that the body is discarded. This is clear about what the tool does, though it does not explicitly distinguish itself from siblings like fetch-status or status-catalog.

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 choose web-fetch over alternatives such as fetch-status, browser-url-ok, normalize-url, or status-catalog. The description implies a use case but provides no exclusions or routing cues.

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?

There are no annotations, so the description carries the burden. It discloses only that the title is discarded after the call, suggesting no retention, but it says nothing about network access, side effects, errors, or output semantics for a check that presumably queries Wikipedia.

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 text is short, front-loaded with the main purpose, and has no filler words. It omits essential invocation detail, but that is a completeness issue rather than a structure issue; as a concise statement it is efficient.

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 seven-parameter schema, no output schema, and no annotations, the description is severely incomplete. It does not specify the expected input, the return value, network behavior, or error conditions, so an agent cannot reliably select and call 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?

The schema exposes seven fields (ref, url, city, feed, host, json, path), none of which is a 'title' field, and the description never names which parameter receives the Wikipedia title. This is a critical mapping failure: the description adds no meaning beyond the schema and leaves the agent unable to know how to invoke the tool correctly.

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 ('Check whether') on a specific resource ('a Wikipedia title exists'), which is clear at a high level. It does not explicitly differentiate itself from sibling validators like domain-shape or file-path-ok, nor does it connect to the tool's actual input fields, so it is not a full 5.

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 purpose implies when to use it (when an agent needs to verify the existence of a Wikipedia title), so there is some implied guidance. However, it names no alternatives, nor does it explain when not to use it or how it compares with web-fetch or other URL shape tools.

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