ISO country MY

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 useful behavioral traits: the gateway is 'public pay-per-call' and 'Task text discarded' signals privacy behavior. However, it does not explain whether remote MCP hops are executed, whether network access or payment is involved, what authorization is needed, or failure 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?

Two terse sentences front-load the primary action and output, with no wasted words. The unexplained 'Monid' and the dangling phrase 'Task text discarded' create minor comprehension costs, but overall the description is compact 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?

For a tool with nine optional-looking parameters, no output schema, and no annotations, this description is too thin. It names return artifacts but does not say which inputs to provide, whether any are needed for the lookup, what the returned data structure looks like, or how to validate success.

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. The description adds little beyond a vague reference to task text being discarded; it does not clarify how the parameters map to the gateway lookup or which ones matter.

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?

States a concrete action and resource: 'Find a public pay-per-call tool gateway (Monid)' and lists what it returns (CLI setup, how-it-works, skill file, remote MCP hops). This distinguishes it from many sibling tools at a high level, though 'Monid' is unexplained and the relationship to the tool name 'agent-tool-index' is somewhat 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 for when to use this tool versus alternatives, and no sibling tools are referenced. The description implies one use case but does not provide conditions, exclusions, or context that would help an agent choose it over the 27 siblings.

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 of behavioral disclosure. It discloses that no browser is launched but does not state whether network requests are made, whether there are timeouts or side effects, what 'opened' means, or that several input parameters are discarded. This leaves important behavioral traits 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, purposeful sentences. The core action is front-loaded in the first sentence, and the key behavioral qualifier, 'No browser is launched,' is clearly separated in the second. 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?

With 9 parameters, no output schema, and no annotations, a one-sentence description is insufficient. It does not explain what the tool returns, which parameters are required for a meaningful call, or how the URL openability check is performed. The completeness is inadequate for safe and 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 tool description itself adds no parameter guidance, but the input schema has 100% description coverage, so the baseline is 3. The schema descriptions do add some context, though many note that values are 'discarded,' which does not clarify how the url parameter is actually used for the check.

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: 'Check whether a URL can be opened.' The qualifier 'No browser is launched' helps distinguish it from browser-driven siblings like playwright-url-ok. However, it does not define what 'can be opened' means in terms of HTTP status or URL shape, leaving some overlap with fetch-status and normalize-url.

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 'No browser is launched' implies a lightweight, non-browser check, which gives some usage context. However, it does not explicitly say when to prefer this tool over alternatives such as playwright-url-ok, web-fetch, or normalize-url, nor does it mention any 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 carries the full burden of behavioral disclosure, but it only says 'Expression discarded,' which is ambiguous and incomplete. It does not state whether the result is returned, whether all inputs are discarded, what side effects occur, or what the tool actually does with any of the nine schema parameters.

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 and 'Evaluate a+b style arithmetic' is front-loaded, but the second phrase 'Expression discarded' is confusing rather than informative. This is under-specification rather than effective conciseness; the brevity does not help the agent understand invocation.

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, no output schema, and no usage guidance, this description is grossly incomplete. It omits the expression parameter, the return behavior, the relationship to the schema fields, and any operational context, leaving an agent unable to 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?

Although schema coverage is 100%, the description does not connect 'expression' to any of the nine parameters. An agent cannot determine which field, if any, holds the arithmetic expression, and the param descriptions are about URLs, files, JSON, and search queries—none of which match the tool's advertised purpose.

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

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

The description names a specific verb ('Evaluate') and a resource ('a+b style arithmetic'), so it is not a tautology. However, it is vague because no schema parameter corresponds to an arithmetic expression, and it does not distinguish this tool from the many shape-checking siblings like domain-shape or validate-json.

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 calc-eval versus any alternative tool. The sibling list includes several validation and shape-checking tools, but the description gives no conditions, exclusions, or routing hints to help an agent choose 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, the description carries the burden of disclosing behavioral traits. It does add a useful privacy guarantee: 'Page content is not stored.' However, it does not mention whether the tool makes a network request, follows redirects, or retains any other data, so the behavioral disclosure is only partial.

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 primary function is front-loaded, and the privacy note is relevant and concise.

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 annotations, no output schema, and a large set of URL-related sibling tools, this description is too thin to be fully actionable. It omits when to use the tool, how it differs from alternatives, and any output or error details. The schema covers parameters, but the operational context is largely missing.

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

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

The input schema already documents all parameters, so the description does not need to repeat that information. The description only implicitly ties the behavior to the 'url' parameter and does not explain how the other parameters relate to the returned host, scheme, and status. With high schema coverage, 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 clearly states what the tool does: it returns host, scheme, and HTTP status for a URL. It also adds a meaningful note that page content is not stored. However, it does not explicitly distinguish itself from sibling tools like fetch-status or normalize-url, so it stops short of a 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?

There is no guidance about when to use citation versus fetch-status, web-fetch, normalize-url, or domain-shape. The description only states the behavior and leaves the agent to infer when this tool is the right choice among many similar 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 itself carries the burden; it does add a meaningful behavior: 'No identifiers are retained,' and the per-parameter schema descriptions reinforce that inputs are 'discarded' or 'not retained.' However, it does not disclose what the classification return value looks like, whether multiple inputs are allowed, or any 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?

The text is only two sentences and is front-loaded with the intended action, so it is concise with no wasted words. For a nine-parameter tool with no output schema and many siblings, this level of brevity is under-specified, making the structure too thin to be fully appropriate.

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 leaves critical operational details unexplained: no output schema exists to define the return value, all nine parameters are optional so parameter selection is ambiguous, and there is no guidance on whether to pass one or multiple fields. The privacy guarantee is helpful, but the description is not complete enough 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 tool-level description contributes no parameter meaning, but schema description coverage is 100% and each parameter's purpose is clearly documented in the schema. Per the baseline for high schema coverage, the description does not need to repeat parameter 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 says the tool will 'Show how this request is classified,' which provides a verb and a general subject but leaves 'this request' and the classification scheme undefined. It does not identify a concrete resource or distinguish this tool from its 27 siblings, so the purpose is vague rather than tautological.

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 call compatibility rather than a sibling tool, nor about which of the nine optional parameters to set. The only contextual hint is the privacy note, which does not explain selection 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 full burden of behavioral disclosure. It adds one useful fact—no WHOIS or ownership lookup—but does not state the output format, error behavior, side effects, or how the many non-host parameters are handled. The schema parameter descriptions mention 'discarded' behaviors, but the tool description itself is too thin for a 9-parameter 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 one concise, front-loaded sentence with no filler; it states the core action immediately. This is efficient, though it may be too sparse given the complexity of 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 tool with nine optional parameters, no annotations, and no output schema, the definition is incomplete. It lacks instructions on which parameter to provide, what the return value looks like, and how the discard behaviors combine. The schema does some work, but the agent still cannot confidently determine 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?

Schema description coverage is 100%, so the baseline is 3; the parameter descriptions already explain each field individually. The tool description adds no parameter-level meaning and fails to clarify which of the nine optional parameters is relevant to hostname splitting. The schema compensates but does not resolve the overall 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 names a concrete operation ('split a hostname into labels') and scopes out WHOIS or ownership data, so it is not a tautology. However, the input schema exposes eight additional unrelated parameters (ref, url, city, feed, json, path, zone, query), and the description never explains how they relate to hostname splitting. This mismatch makes it a weak selection cue among 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?

There is no guidance on when to use this tool instead of sibling tools such as github-repo-shape, jira-key-shape, normalize-url, or validate-json. No preconditions, alternatives, or context-based selection rules are provided. The only hint is an exclusion ('without WHOIS or ownership data'), which is not enough to choose 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 provided, the description carries the full burden. It does disclose the HTTP method and output scope ('HEAD' and 'status only'), implying a read-only operation with no body returned. However, it does not mention failure modes, redirects, timeouts, or whether 'status' means an HTTP status code, which leaves some behavioral uncertainty.

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 direct sentence with no filler, and the key action is front-loaded. It is concise and easy to parse, though the brevity contributes to missing context elsewhere.

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, no annotations, and 27 sibling tools, this description is incomplete. It fails to explain parameter roles, response shape, or when to prefer it over closely related tools, so an agent cannot reliably select and use it.

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 9 optional parameters, but the description only mentions `url`, and the url property's schema description ('HTTPS URL to normalize or cite') conflicts with the stated purpose of fetching status. Other parameters are marked 'discarded' without any explanation of how they relate to this tool, making it difficult for an agent to know which input matters.

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, and result: 'HEAD a public URL and return status only.' This is clear and easily understood. However, it does not explicitly differentiate itself from close siblings like browser-url-ok, playwright-url-ok, 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 alternatives such as browser-url-ok or web-fetch, and no exclusions are stated. The only contextual hint is 'public URL,' which is a constraint rather than a usage guideline.

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, but it only states 'Path discarded.' It does not say whether the tool is read-only, whether it makes a network request, what it returns, or how it treats the rest of the URL. The single behavioral claim (discarding the path) is too minimal to inform a caller.

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 two-sentence description is concise with no wasted words, and the core object is front-loaded. However, the second sentence is a fragment and under-specifies a tool with nine parameters and no annotations, making it more under-specified than elegantly concise.

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 is far too thin for a tool with 9 optional parameters, no output schema, and no annotations. It fails to explain what input to pass, what operation is performed, what the output looks like, or whether any side effects exist. An agent cannot confidently invoke this tool correctly based on the available information.

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 per the baseline, a 3 is appropriate even without additional parameter explanation. The description does not add parameter-level detail, and the schema's 'url' description ('HTTPS URL to normalize or cite') does not align with the tool's stated Figma-focus, leaving some ambiguity about the primary input.

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

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

The description names a specific resource ('Figma file URL') and a verb ('Parse'), which points at the tool's domain. However, 'parse' is vague about the outcome (validation? extraction? normalization?), and 'Path discarded' does not clarify what result the agent should expect. Without more, it is hard to distinguish from normalize-url or a generic URL checker.

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 instead of the many shape/URL siblings such as domain-shape, github-repo-shape, or normalize-url. The only implicit hint is that it applies to Figma URLs, but no explicit conditions, exclusions, or alternative recommendations 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. It does disclose a key behavioral trait: 'No disk access.' It also hints that this is a syntactic/heuristic check ('looks safe') rather than a filesystem guarantee. However, it does not state return behavior, failure behavior, or whether values other than 'path' are 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?

Two short sentences, front-loaded with the core purpose and followed by the key safety guarantee. There is no filler, repetition, or buried detail. The description earns its length despite being incomplete in 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?

Given 9 optional parameters, no annotations, and no output schema, the description is too thin. It does not say what the tool returns, how a caller should interpret 'safe,' or whether only the 'path' parameter is meaningful. An agent cannot confidently know how to invoke this tool correctly among its many parameters and 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?

The input schema provides descriptions for all 9 parameters, so the schema already handles parameter-level meaning. The description adds no parameter information beyond the schema. This is a baseline 3 case, though the presence of many apparently unrelated parameters (url, city, feed, host, json, zone, query) makes the schema confusing and the description does nothing to clarify which parameter actually drives the 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 uses a specific verb and resource: 'Check whether a path looks safe.' Combined with the schema's 'File path to check' parameter, it is clear this validates file-path shape and not, say, a URL or hostname. It does not explicitly distinguish itself from sibling shape-checking tools, but the name and wording are 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?

The description gives no when-to-use guidance, no exclusions, and no alternatives. With siblings like browser-url-ok, normalize-url, and wiki-title-ok, an agent gets no help choosing this tool over a related shape-checking tool. The only implied context is that the tool is for checking path safety, which is minimal.

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 only mentions 'via Open-Meteo,' implying an external network call, but says nothing about failure modes, rate limits, side effects, or the fact that many input fields are discarded after use.

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 with no filler, which is efficient. But it is under-specified for a nine-parameter tool with no annotations or output schema, making the conciseness a liability rather than a strength.

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 are no annotations, no output schema, and nine optional parameters, yet the description only states the high-level purpose. It does not explain output format, which parameter is required for the lookup, error behavior, or how this differs from related hint tools, leaving an agent with insufficient information to 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?

The schema has 100% description coverage across all nine parameters, so the baseline is 3 even though the description adds no parameter mapping. However, the schema itself is confusing: 'city' is described as 'for a public weather hint' and 'discarded after the call,' so an agent still cannot confidently determine which parameter supplies the geographic place.

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 tool's result as latitude and longitude for a place and names Open-Meteo as the source, so it is not a tautology. However, it lacks a clear verb like 'get' or 'resolve' and does not indicate which input field supplies the place, nor does it differentiate geo-hint from sibling tools like weather-hint or normalize-url.

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 weather-hint, timezone, or web-fetch. No context, exclusions, or alternative tool suggestions are provided, so an agent must guess the appropriate use case.

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 but only says 'Parse.' It does not disclose return format, behavior on invalid URLs, or that the many other schema parameters are discarded or ignored. The schema hints at 'discarded after...' behavior, but the description itself adds little transparency.

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, tight sentence with no filler and a front-loaded verb. However, it may be undersized given the schema's nine parameters and lack of annotations.

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

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

There is no output schema and no annotations, so this one-liner is insufficient for correct invocation. It does not explain how the owner/repo result is returned, what counts as a valid GitHub URL, or why the schema includes unrelated fields like city, feed, host, json, path, zone, and query.

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 of 3 applies even though the description adds no parameter-level detail. The description implies owner/repo as an outcome, but does not clarify which of the nine parameters is the GitHub URL or reconcile with the schema's 'url' description of 'normalize or cite.'

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 ('Parse') and outcome ('owner and repo'), scoped to 'a GitHub URL.' This distinguishes it from sibling tools like figma-url-shape and jira-key-shape. It does not, however, clarify the broader 'shape' behavior suggested by the tool 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 phrase 'from a GitHub URL' gives an implied usage context, so an agent could infer it is for GitHub URLs rather than other URL types. There is no explicit when-to-use guidance, no mention of alternatives, and no exclusion criteria.

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 disclosure burden, but it only reveals that titles are discarded. It does not describe whether the tool performs a live fetch, caches results, or how it behaves on failure, rate limits, or network errors.

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, and the primary purpose is front-loaded. It is concise and readable, though brevity comes at the cost of missing useful 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?

For a tool with nine optional parameters, no output schema, and no annotations, this description is not complete enough. An agent cannot determine the response shape beyond 'a count', which parameters are relevant, or what edge cases 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?

All nine parameters have schema descriptions, so the baseline is 3. The description does not add information about which parameters affect the count or explain why unrelated-looking parameters like ref, city, json, and zone are present.

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 ('Count') and a specific resource ('current Hacker News front-page stories'), so the core purpose is clear. The added note 'Titles discarded' further clarifies what the tool will not return, though it does not explicitly differentiate from sibling tools like web-fetch or fetch-status.

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 an agent needs the count of current Hacker News front-page stories. However, it does not state when not to use it, mention alternatives, or clarify whether any of the nine optional parameters should be supplied.

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 behavior disclosure. It does not state whether the tool returns a list, validates names, fetches data, or has side effects. The description also conflicts sharply with the input schema: parameters like url, json, path, and ref have nothing to do with IANA timezone names and are described as being 'discarded', which is unexplained.

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 phrase with no wasted words, but this is under-specification rather than effective conciseness. It lacks any structure, front-loaded action, or supporting details that would help an agent use the tool correctly.

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, no annotations, and nine optional parameters, yet the description provides almost no contextual information. It fails to explain what the tool returns, why the parameters exist, how they relate to timezone names, or how this tool differs from the sibling timezone tools. An agent cannot reliably decide to call this tool or construct a valid call from the provided information.

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 itself contributes no parameter meaning. The schema includes per-parameter descriptions, but many of those parameters are unrelated to the stated tool purpose, and the description does nothing to reconcile that mismatch or clarify which parameters actually matter.

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 the intended use case ('for clock calls'), but it lacks a specific verb such as list, return, or fetch, making the tool's action ambiguous. It also does not distinguish this tool from the sibling tools timezone and utc-time, which are both clock-related.

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' gives a minimal usage hint, but there is no explicit guidance about when to use this tool versus the sibling timezone or utc-time tools. No alternatives, exclusions, or conditions are mentioned, so the agent is left to 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?

No annotations are present, so the description carries the transparency burden. It discloses that a network read occurs ('Fetch'), that no auth is expected ('public'), and that the full body is not returned ('counts only'). It does not cover failure modes, but the core 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?

The description is a single front-loaded sentence with no filler. Action, resource, and output scope are all present and each word contributes meaning.

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 annotations, and no output schema, a one-line description is too thin. It omits which parameter carries the robots.txt URL/host, what 'group counts' means structurally, and how failures are reported, so correct invocation depends on inference.

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 nine parameters already have schema descriptions, so the baseline is 3, and the tool description adds no parameter-specific meaning. It never maps the robots.txt target to either `url` or `host`, leaving the agent to infer which field to populate.

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 ('Fetch'), a precise resource ('public robots.txt'), and a constrained output ('group counts only'). This clearly distinguishes it from siblings like web-fetch or fetch-status, which would return full content or status information.

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 word 'only' provides clear context that this tool is for count-level results rather than full robots.txt inspection. It does not explicitly name alternatives or state when-not-to-use, but the count-only framing gives the agent a solid usage signal.

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 says 'Key discarded' but says nothing about return values, validity criteria, error handling, or side effects, leaving the agent in the dark about expected 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 extremely short, but 'Key discarded' adds little useful semantic content and the missing parameter mapping makes the brevity harmful rather than helpful. Under-specification outweighs any benefit of conciseness.

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 shape-check tool with no annotations and a multi-parameter schema that appears unrelated to the stated purpose, the description is grossly incomplete. It omits how to pass the Jira key, what shape is expected, and what the tool returns, so an agent cannot reliably select or invoke it.

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 the schema descriptions cover all listed properties, those properties are unrelated to Jira issue keys, and the description references a 'Key' that does not appear anywhere in the schema. This is a critical mapping failure: the agent cannot determine which, if any, parameter contains the Jira key.

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 operation ('Check a Jira issue key shape') and the resource type, which distinguishes it from sibling *_shape tools. However, the input schema exposes no 'key' parameter and instead lists unrelated fields like ref, url, city, and feed, so an agent cannot map the stated purpose to an actual argument.

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 like github-repo-shape or domain-shape. The only implied use is a Jira key shape check, but there are no conditions, exclusions, or alternative routing hints.

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 behavioral burden. It does disclose a meaningful behavior: the response body is discarded and only the HTTP status matters. It does not mention network request behavior, return format, error handling, or side effects, but it is not silent about behavior either.

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 short and front-loaded: two sentences with no wasted words. It earns a high conciseness mark, though it is slightly under-specified for a 9-parameter tool, so it is not a perfect 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?

For a tool with 9 optional parameters, no output schema, and no annotations, this description is incomplete. It does not explain how parameters like city, json, path, or zone relate to 'public library docs URL', what the exact return value looks like, or what happens when multiple parameters are supplied.

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 descriptions for all 9 parameters, so the baseline applies; the tool description adds no parameter-level meaning beyond pointing at a URL. The description does not clarify optionality, which parameter to use for a given call, or how parameters relate to each other.

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: it returns the HTTP status of a public library docs URL and discards the body. It avoids tautology and gives enough of a resource (library docs URL) to separate it from generic content-fetching tools, though it does not explicitly distinguish itself from sibling status tools like fetch-status.

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?

Use is only implied: the qualifier 'public library docs URL' and 'Body discarded' suggest using it when only a status is needed and the body is irrelevant. There is no explicit when-not-to-use guidance or reference to alternatives such as web-fetch or normalization tools, so an agent has to infer the right 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 full behavioral burden; it does meaningfully disclose that all values are discarded, reinforced by per-parameter notes like 'discarded after the shape check' and 'titles discarded.' This honestly signals that none of the tempting parameter names trigger real fetches, normalization, or validation side effects. However, it never states the return format, whether the operation is strictly read-only, or whether any external call could occur, leaving the disclosure only partial.

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 zero filler: the verb and object are front-loaded, and the second sentence carries the single most important caveat. Every word earns its place, and nothing could be cut without losing meaning.

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 low-complexity tool, the core function is stated clearly and the schema fully documents all parameters, so the description is not cripplingly incomplete. But there is no output schema and no annotations, and the description never states the return value or format, does not resolve which JSON object is being counted, and does not address behavior when called with zero of the 9 optional parameters. These are real but moderate gaps for a tool whose entire output is a single number.

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 every one of the 9 parameters is already documented in the schema, setting the baseline at 3. The description adds a mild unifying frame — that all inputs are merely keys to be counted and values to be discarded — which helps the agent avoid expecting per-parameter behavior. It does not clarify how missing versus provided keys affect the count or how the params map onto the object being counted.

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 ('Count keys in a JSON object') plus the value-discard policy, so it is not a tautology. However, the input schema exposes nine unrelated string parameters and no object-typed parameter, leaving ambiguous whether the counted object is the whole input object or a JSON string value. It also does nothing to differentiate the tool from counting/validation siblings such as validate-json, hn-front-count, or search-query-len.

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 when-to-use or when-not-to-use guidance, and no alternative or exclusion is named. With 27 siblings spanning validation, URL normalization, weather, and counting tools, the agent is left to infer routing entirely from the name and the terse purpose sentence. The only implied signal is that this tool counts keys and ignores values, so it is not the tool for real normalization or validation work.

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 does disclose a genuine behavioral trait by stating that 'Query and fragment are dropped', which is useful. However, it does not explain error behavior, output formatting, or whether HTTPS is enforced beyond the schema hint, so transparency is partial.

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 core purpose is front-loaded, and the second sentence adds a meaningful behavioral constraint without 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 nine parameters, no annotations, and no output schema, this description is too thin. It does not state the return format, error behavior, or how to handle the many parameters that appear irrelevant to URL normalization, so an agent cannot reliably predict the full result of a call.

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, with parameter-level notes such as 'discarded after the shape check', so the schema already carries most semantic weight. The description adds the context that the operation is URL-based, but it does not clarify which of the nine parameters is the primary one or how the discarded parameters interact with the call.

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 and resource: it will 'Return origin, host, and path for a URL'. It clearly states the tool's core function, but it does not explicitly differentiate it from sibling URL-oriented tools such as browser-url-ok or figma-url-shape.

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 mention of sibling tools. The description only implies URL normalization, leaving the selection decision entirely 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 provided, the description carries the full burden of behavioral disclosure. It only says no browser is launched; it does not explain whether a network request is made, what 'can be opened' means, whether there are side effects, what statuses are considered acceptable, or what output the agent should expect.

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 core action is stated first, and the key behavioral constraint 'No browser is launched' is included immediately, making it easy to parse and act on.

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 9 optional parameters, no output schema, no annotations, and many siblings, yet the description does not explain what the output looks like, how parameters are used, or what 'opened' means in practice. This is too sparse for an agent to confidently invoke the tool in varied scenarios.

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 parameters are individually documented. The tool description itself adds no parameter-specific meaning, and the relationship between the URL check and parameters like city, json, or path is unclear, but the schema descriptions provide enough baseline information for a score of 3.

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 as checking whether a URL can be opened and explicitly notes that no browser is launched, which helps distinguish it from browser-based sibling tools. However, the input schema includes many unrelated parameters like city, json, path, and zone, so the true scope of the tool is somewhat ambiguous from the description alone.

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 'No browser is launched' implies this tool is appropriate when a lightweight, browserless URL checks is needed, but no explicit when-to-use or when-not-to-use guidance is provided. It does not name alternatives such as browser-url-ok or fetch-status, leaving the selection logic mostly 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?

The phrase 'Query discarded' provides useful behavioral information about data handling, which is valuable since no annotations are present. However, the description does not disclose other behavioral traits such as whether any network call occurs, what the output format is, or why the other eight parameters exist and are also discarded. It partially carries the transparency burden but leaves 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 extremely concise, consisting of two short sentences with no filler. The main action is front-loaded, and the second sentence adds a relevant behavioral note. It earns a high score for efficiency, though it could be slightly more informative without losing conciseness.

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 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain the role of the other eight parameters, which parameter to treat as the search query, or what the tool returns besides a character count. An agent would likely need additional inference to use 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 description coverage is 100%, so each parameter already has a clear description. The tool description adds no parameter-level meaning, but the schema fully compensates. Baseline of 3 is appropriate because the schema carries the heavy lifting.

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 verb ('Count characters') and the resource ('a search query'), making the core purpose easy to grasp. It does not explicitly contrast with sibling tools, but the operation is distinct enough from the validation/fetch tools in the list. Minor ambiguity remains about which parameter constitutes the 'search query'.

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. The description gives no context about scenarios, prerequisites, or when another tool might be more appropriate. The agent must infer usage from the tool 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?

There are no annotations, so the description must shoulder the behavioral burden, but it only states what the catalog contains and not what happens during a call. It does not disclose output behavior, side effects, or the fact that several schema parameters are discarded.

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, which is appropriately concise for a simple reference tool. It errs on the side of under-specification, but conciseness itself is handled 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?

With seven documented parameters, no annotations, and no output schema, a one-line description is not enough for an agent to know what to pass or what the returned catalog will look like. It communicates the general subject area but leaves the invocation contract largely 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?

The input schema already provides descriptions for all seven parameters, which establishes the schema-coverage baseline of 3. The description contributes nothing about how parameters relate to the catalog, so it adds no additional parameter-level meaning.

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 a catalog of common HTTP status codes, which conveys the resource and scope well enough to separate it from fetch/validation siblings. It lacks an explicit action verb such as 'look up' or 'return,' but the noun 'catalog' makes the intended read-only reference purpose reasonably 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 about when to choose this tool over fetch-status, web-fetch, or other status-related siblings, nor any mention of preconditions or exclusions. The only implicit signal is the word 'catalog,' which is too weak to route an agent confidently.

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 annotations empty, the description carries the full burden and does add one genuinely useful behavioral fact: 'Prompt discarded' warns the agent not to expect reasoning over its input. However, this largely duplicates the schema's per-parameter 'discarded' notes, and it never discloses that the tool returns the same static template regardless of input or that it has no 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 totaling seven words, with the core behavior front-loaded and the caveat second; every word earns its place. It teeters on under-specification, which keeps it from 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?

For an eight-parameter tool with zero annotations and no output schema, two sentences are thin. The description never explains why eight heterogeneous parameter types exist, what the returned template is for, or when to call this instead of simply proceeding, leaving selection among a large sibling set to guesswork.

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 eight parameters already carry descriptions in the schema (e.g., 'Git ref name; discarded after the shape check', 'JSON text to validate; discarded after the check'), so schema_description_coverage is 100% and the baseline of 3 applies. The tool description adds no parameter-level meaning beyond those 'discarded' notes and does not tell the agent which of the eight unrelated params to populate.

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 specifies a concrete deliverable ('a three-step thinking template') with a clear verb ('return'), and this output type distinguishes it from the sibling tools, which are all domain-specific validators/checkers like browser-url-ok, validate-json, and normalize-url. It loses a point because it never says what the template contains or what purpose it serves once returned.

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

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

There is no guidance on when to invoke this tool versus any of the 27 siblings, no named alternatives, and no context triggers. 'Prompt discarded' is a behavioral caveat rather than usage guidance, so an agent has little basis for deciding 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?

With no annotations, the description carries the full behavioral burden, yet it only states the outcome and does not disclose the output format, read-only nature, or how the timezone is supplied. The mismatch with the input schema (no timezone parameter) further undercuts transparency. This reads as a benign time lookup, but an agent cannot predict behavior from the description alone.

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 sentence with no filler; the main purpose is front-loaded in the first words. It is as concise as a one-line tool description can be.

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 9-parameter tool with no annotations and no output schema, this description is far from complete. It does not explain which parameter carries the IANA timezone, what response shape to expect, or how the unrelated parameters interact, so an agent cannot reliably invoke 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?

Although schema coverage is 100%, every parameter (ref, url, city, feed, host, json, path) is unrelated to a timezone lookup. The description adds the concept of an IANA timezone but never maps it to a parameter, so it does not help an agent choose a 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 names a specific action ('Current time') and resource ('named IANA timezone'), which distinguishes it from the sibling utc-time and iana-zones tools. It does not explicitly contrast it with those siblings, but the core purpose 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?

The phrase 'current time in a named IANA timezone' implies the tool should be used when a non-UTC/local time lookup is needed. However, it gives no exclusions or explicit alternatives, so an agent must infer when to prefer this over utc-time or iana-zones.

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, but it only says the output is a current UTC timestamp. It does not disclose the output format (e.g., ISO 8601, epoch seconds), whether the tool is side-effect-free, or how the unusual input schema parameters relate to 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 short sentence with no wasted words and is easy to parse. It is appropriately concise for what appears to be a simple utility, though it sacrifices useful 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?

For a tool with no annotations and no output schema, the description leaves important context missing: the exact timestamp format, confirmation that the input parameters are ignored, and how this compares to the timezone tool. The mismatched schema makes the tool harder to use correctly than a simple timestamp description would suggest.

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 includes seven properties and each has some explanatory text, so schema coverage is high and the baseline is 3. However, the description itself adds no parameter meaning, and the listed parameters (ref, url, city, feed, etc.) seem unrelated to obtaining a UTC timestamp, which could confuse an agent.

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' clearly states the resource and output, and the explicit mention of UTC distinguishes it from the sibling 'timezone' and 'iana-zones' tools. It lacks a verb like 'returns' or 'gets', 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 on when this tool should be used instead of related siblings such as 'timezone' or 'iana-zones', and no exclusions or alternative suggestions are provided. The description only names what it does, not when to invoke it.

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

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

The description discloses one behavioral trait: 'The body is discarded.' This is useful because it indicates the tool is stateless and does not retain inputs. However, with no annotations available, the description carries the full burden of behavioral disclosure; it does not mention what the tool returns on valid versus invalid JSON, any error behavior, or side effects beyond discarding the input.

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: two short sentences with no filler. The core purpose is front-loaded, and the second sentence adds a meaningful behavioral note about data handling. Every word earns its place, making this an exemplary model of concise tool documentation.

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 annotations and no output schema, the description is too sparse. It does not explain the expected return value (e.g., boolean, success/failure), how to provide the JSON body (which parameter), or when to choose this tool over other validation siblings. The schema contains extraneous parameters like 'url' and 'city' that could confuse an agent, and the description does nothing to resolve that ambiguity.

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 provides descriptions for all parameters, including 'json: JSON text to validate; discarded after the check', so schema coverage is high (100%). The description itself adds no additional parameter semantics and does not clarify which parameter is the primary one, leaving the agent to rely on the schema. Thus, 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 a specific action and resource: 'Check whether a body is valid JSON.' This clearly signals the tool's purpose and differentiates it from siblings like file-path-ok or url-ok, which validate other resource types. However, it does not explicitly mention the 'json' parameter or clarify what 'body' means in the context of an API call, so the purpose is clear but not fully specified.

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. There is no mention of conditions, exclusions, or references to sibling tools such as file-path-ok or url-ok. An agent must infer usage solely from the tool name and description, which is insufficient for deciding between similar validation 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?

No annotations are provided, so the description bears full responsibility for disclosing behavior. It only states that the tool returns a temperature via Open-Meteo; it does not say whether this is a read-only network call, whether parameters other than city are ignored, what error behavior looks like, or whether any state changes occur. For an unannotated tool, 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 sentence with no filler. It front-loads the essential information—what the tool returns and for what kind of input—making it easy to scan.

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 simple surface description, the tool has nine optional parameters, no required parameters, no annotations, and no output schema. The one-line description does not explain how to select among the many schema parameters, what the response format is, or what happens when multiple parameters are supplied. This creates significant ambiguity for an agent attempting a correct call.

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 descriptions cover all nine parameters at 100% coverage, so the baseline is 3. The tool description adds only the idea that 'city' is the relevant input, but it does not clarify how to format the city or explain that the other eight parameters are unrelated/discarded. The schema already handles the parameter documentation, so the description provides little additional 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 clearly identifies the resource ('current temperature for a city') and the data source ('Open-Meteo'), and it is distinct from sibling tools like timezone or geo-hint. It lacks an explicit action verb such as 'Get' or 'Return', and it does not acknowledge the schema's many unrelated parameters, but the core purpose 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?

The description implies a use case: when an agent needs the current temperature for a city. However, it provides no explicit when-to-use/when-not-to-use guidance, no exclusions, and no mention of alternative sibling tools. This is better than no guidance but still leaves the decision 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 carries the transparency burden. It discloses a key behavioral trait: the response body is discarded, so the agent will not receive page content. It also scopes the operation to public URLs, implying no auth, and the operation appears side-effect-free; however, it doesn't mention redirects, timeouts, or error handling.

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 zero filler. The main result is stated first, and the important body-discarded constraint is placed second.

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 is adequate for a simple status/content-type fetch, but given nine optional parameters and no output schema, it should clarify how the URL parameter relates to the others. It also lacks usage context relative to the many sibling tools, leaving the agent to infer selection and 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; each parameter has a description. The tool description adds no parameter-level meaning, and it does not clarify which of the nine optional fields is the intended 'public URL' input, though the schema's 'url' field is reasonably discoverable.

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

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

The description clearly states the tool returns HTTP status and content type for a public URL, and explicitly notes the body is discarded, which helps distinguish it from fetch tools that return content. It does not name sibling tools, and the resource/scope is not elaborated beyond 'public URL', 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 on when to use web-fetch versus siblings such as fetch-status, browser-url-ok, or normalize-url. The only implicit signal is 'Body discarded', which hints it is not for content retrieval, but no exclusions or alternatives are 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 present, so the description must carry the full burden. It discloses that the title is 'discarded after the call,' which is a lightweight privacy trait, but it does not explain return behavior, whether external network requests are made, or what 'exists' means. For an existence-checking tool, this is under-specified.

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, and the operation is front-loaded. However, the second sentence is somewhat redundant with the discard language already echoed in several parameter descriptions.

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 eight parameters, no output schema, and no annotations, the description is far too sparse. It omits the return value, which parameter represents the Wikipedia title, and any caveats about URL forms or alternative tools, making reliable invocation difficult.

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 documents all eight parameters, so the baseline is 3, but the description names a 'title' concept that maps to none of the schema parameters. The parameter descriptions (e.g., 'Git ref name,' 'City name for a public weather hint') appear unrelated to Wikipedia titles, so the description does not help the agent choose the correct 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 states a specific operation: 'Check whether a Wikipedia title exists,' which is clear and distinct from the sibling URL/shape tools. However, the input schema contains no 'title' parameter—only ref, url, city, feed, host, json, and path—so the stated purpose does not map cleanly to a usable input.

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 normalize-url, web-fetch, or validate-json. The description gives no prerequisites, exclusions, or contextual conditions for choosing this tool.

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