ISO country PK

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

With readOnlyHint, idempotenceHint, and side-effect hints already present, the annotations carry the safety profile. The description adds value beyond that by disclosing that task text is discarded — the tool ignores the payload and acts purely as an index — and by stating what it returns. Nothing contradicts the annotations.

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

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

Three short sentences front-load the purpose, then the returns, then the key behavioral caveat. Every clause earns its place with no filler and no repetition of schema or annotation content.

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

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

For a tool with no output schema, the description adequately names the return items and flags that task text is discarded; combined with 100% schema coverage and read-only annotations, an agent has what it needs to invoke correctly. Minor ambiguity remains around what Monid is and why the gateway index accepts city/feed/json parameters, but the schema's 'discarded' notes mitigate this.

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 input schema already documents all six string parameters, including the 'discarded after the shape check' notes. The tool description adds no parameter-specific meaning beyond the schema, so the baseline of 3 applies.

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

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

The description opens with a specific verb and resource — 'Find a public pay-per-call tool gateway (Monid)' — and enumerates the deliverable contents (CLI setup, how-it-works, skill file, remote MCP hops). This clearly separates it from the sibling tools, which are URL, shape, and validation utilities.

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?

Usage context is implied: an agent would invoke this when it needs Monid's CLI setup, skill file, or remote MCP hops. However, the description names no explicit conditions, exclusions, or alternatives among the siblings, leaving the when-to-use decision largely 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?

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose one important behavior: 'No browser is launched.' However, it does not explain whether the check performs a network request, whether it is read-only, what 'can be opened' means, or what kind of result is 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?

The description is two short sentences with no filler. The primary action is front-loaded, and the second sentence provides a meaningful clarification that prevents an incorrect assumption about launching a browser.

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 tool having 9 parameters and no output schema, the description leaves major context unexplained: which parameter is actually used, what kind of check is performed, whether it contacts the network, and what the return value looks like. More behavioral and usage context is needed for an agent to call it confidently.

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 9 parameters already have descriptions in the input schema, so the schema coverage is 100%. The tool description itself adds no parameter-level meaning beyond the word 'URL,' but it does not need to because the schema fully documents each field. Baseline 3 is appropriate.

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

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

The description states a specific verb and resource: 'Check whether a URL can be opened.' The clarifying 'No browser is launched' adds useful precision. However, it does not distinguish this from sibling tools like playwright-url-ok, web-fetch, or fetch-status, 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 explicit guidance on when to use this tool versus the many URL-related siblings. The description implies a lightweight check but does not state conditions, exclusions, or alternatives such as playwright-url-ok, web-fetch, or normalize-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 description provides minimal behavioral context: it says the expression is discarded, implying no persistence. However, there is no mention of what the tool returns, whether evaluation is synchronous, what expression syntax is supported, or any side-effect profile. With no annotations, the description carries the full burden and falls short.

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

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

The description is compact and front-loaded: the core purpose appears in the first sentence. The second sentence adds a behavioral note without fluff. It is concise, though too terse to compensate for the missing parameter mapping.

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 annotations, and no output schema, a one-sentence description is not nearly enough. An agent cannot determine which field holds the expression, what the expected output format is, or how this tool compares to the many sibling utilities. The definition is incomplete for correct invocation.

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

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

The schema covers all 9 parameters descriptively, but none of them is clearly the arithmetic expression. The description says 'Evaluate a+b style arithmetic' yet does not indicate which parameter receives the expression, creating a significant mapping gap. The description adds no useful parameter-level meaning beyond the schema.

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

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

The description clearly states that the tool evaluates simple 'a+b style arithmetic', which is a specific verb and resource. It does not explicitly differentiate from sibling tools, but the arithmetic-evaluation purpose is reasonably distinct among the listed shape-check and fetch 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 about when to use this tool versus the many sibling tools, no mention of alternatives, and no criteria for when arithmetic evaluation is appropriate. The description leaves the agent to infer usage entirely.

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

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

With no annotations, the description carries the burden of behavioral disclosure. It does add one meaningful trait: page content is not stored. However, it does not disclose whether a network request is made, how redirects or errors are handled, or what side effects exist for the non-URL 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?

Two short sentences, front-loaded with the primary behavior and no filler. The storage note earns its place as a privacy-relevant qualifier, and every word contributes to the agent's understanding.

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, nine optional parameters, and several overlapping sibling tools, the description is too thin. It does not say which parameters are expected, what happens when no parameters are supplied, or the exact return contract beyond host/scheme/status. The schema helps but does not resolve overall tool-selection 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?

Schema description coverage is 100%, so the baseline is 3. The description adds little beyond reinforcing that the tool is URL-focused and does not explain the role of the other optional parameters. The schema must carry the full parameter-semantics burden.

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 clear verb and resource: return host, scheme, and HTTP status for a URL. The second sentence adds a useful boundary, noting that page content is not stored, which separates it from content-fetching tools. It does not explicitly differentiate it from fetch-status, so it stops short of full sibling 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?

No when-to-use or when-not-to-use guidance is provided. The agent is left to infer when this should be chosen over similar siblings like fetch-status, normalize-url, or web-fetch. With such an overlapping sibling set, the absence of explicit routing is a clear gap.

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

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

Because no annotations are provided, the description carries the full burden. It does disclose a meaningful data-handling behavior ('No identifiers are retained'), which is useful, and the schema reinforces per-parameter discarding. However, it omits other behavioral context such as whether the operation is read-only, whether external requests are made, or what the classification result contains.

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 and front-loaded, with no filler: the main action comes first and the privacy guarantee second. However, the brevity contributes to the vagueness, so it is not a perfect score.

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

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

With nine optional parameters, no output schema, no annotations, and many sibling classification/shape tools, the description is insufficient. It does not state how the classification is represented, which parameter to use, or how compatibility is determined.

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 tool description adds no parameter-level meaning beyond what the schema provides, so the baseline 3 applies.

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

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

States a verb and a classification task, but 'Show how this request is classified' is vague: it does not explain what classification means, what compatibility refers to, or what output the agent should expect. It also does not distinguish the tool from sibling shape/check tools like domain-shape, validate-json, or file-path-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 sibling. It gives no conditions, prerequisites, exclusions, or references to alternatives. The privacy note does not explain when the tool should be selected.

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 adds a useful behavioral boundary, 'without WHOIS or ownership data', which is not expressed in the schema. With no annotations, though, it still does not disclose read-only behavior, side effects, or what happens for non-host inputs, leaving meaningful gaps.

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

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

The description is a single, front-loaded sentence with no filler. It states the core action and an important limitation 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?

There is no output schema and the description does not explain return values, so an agent cannot predict what the tool returns. The description covers only hostname splitting while the schema exposes eight other parameter types and there are no annotations to fill the gap. This is severely incomplete for a nine-parameter 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?

All nine parameters have their own schema descriptions, so the baseline is met. The tool description adds semantics only for 'host', clarifying that a hostname is split into labels, while the other parameters remain disconnected from the described behavior.

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, 'Split a hostname into labels', and the qualifier 'without WHOIS or ownership data' helps position it against lookup-style tools. However, it only describes one of the nine accepted input parameters and does not explicitly differentiate it from sibling shape/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?

There is no guidance about when to use domain-shape versus related sibling tools such as normalize-url, validate-json, or jira-key-shape. The schema exposes many unrelated parameter types, but the description does not tell an agent which input is appropriate or when to prefer this 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?

No annotations are present, so the description carries the full disclosure burden. It does disclose the method (HEAD), the target class (public URL), and the output restriction (status only), which are useful basics. But it omits how the many optional parameters are treated (the schema says they are 'discarded'), what 'status' means (HTTP code vs. ok flag), and any redirect, timeout, or 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 description is a single short sentence with no filler, and the key action is front-loaded. Every word earns its place; any incompleteness is a coverage issue, not a conciseness issue.

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 a large set of sibling tools, this one-sentence description is not enough. It does not specify the return format, which parameters to use or ignore, or how this tool differs from web-fetch and browser-url-ok. The conflicting parameter descriptions in the schema make the gap worse.

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 tool description adds only that url is the target of the HEAD request, which is helpful because the schema's url description says 'normalize or cite' and does not mention fetching. For the other eight parameters, the description provides no guidance on whether or how they affect 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 states a specific verb and resource ('HEAD a public URL') and limits the output to status, which is clear at a glance. However, the input schema accepts nine unrelated optional parameters (ref, city, feed, json, path, query) with 'discarded' semantics, so the description does not explain the tool's actual scope. An agent cannot tell whether this is a URL-only HEAD utility or a broader shape-check/status tool.

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

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

No when-to-use guidance is provided. The description does not mention any sibling alternatives such as web-fetch, browser-url-ok, playwright-url-ok, or normalize-url, nor does it explain when HEAD-status is preferable to fetching content. An agent must infer usage from the tool name and one terse sentence.

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 'Path discarded.' It does not state whether the tool makes network calls, validates or transforms the URL, what it returns, how it handles invalid input, or why non-URL parameters are accepted and 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 very short and front-loaded; the main action appears in the first sentence. There is no unnecessary wording. However, it is so terse that some important context is missing, so it is strong on conciseness but not exemplary for structure.

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, no annotations, and no output schema, the description is far too sparse. An agent is not told what the tool returns, which parameter is primary, how to distinguish valid from invalid Figma URLs, or why the schema accepts city, feed, json, zone, and query. The definition is not sufficient for reliable 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 description adds no real value beyond the schema and even creates ambiguity: 'Path discarded' could relate to the URL path, but the schema defines a separate 'path' parameter as 'File path to 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 clearly states a specific verb and resource: 'Parse a Figma file URL.' This is enough to distinguish it from siblings like domain-shape or github-repo-shape by target resource. However, it does not explicitly differentiate it from normalize-url or browser-url-ok, and 'Path discarded' is 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 versus alternatives such as normalize-url, browser-url-ok, or other shape-check tools. There are no exclusions, conditions, or context that help an agent decide between this and a sibling.

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 reveals one important behavioral trait: no disk access, meaning it is a non-destructive syntactic check. However, it does not define what counts as 'safe', whether it returns a boolean or throws, or whether the path must be absolute or normalized. With no annotations, the description carries the burden but only partially meets it.

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. It front-loads the purpose and then adds a useful safety qualifier. Nothing extraneous is present.

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

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

For a simple validation tool with no output schema, the description gives the core purpose and a key safety trait, but it omits the return format, defines no notion of 'safe', and does not address the unusually broad nine-parameter schema. An agent would still need additional inference to use 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 description coverage is 100%, so the baseline of 3 applies. The description adds no parameter-level meaning beyond the schema and does not clarify that only 'path' is relevant while the other eight parameters appear unrelated to the stated tool purpose. This could leave an agent uncertain about which parameter 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 states a clear action and resource: check whether a path looks safe. The tool name reinforces that this is about file-path validation. It is specific enough to be distinguishable from URL/domain checkers, though it does not explicitly contrast with sibling tools.

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

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

There is no guidance on when to use this tool versus alternatives like browser-url-ok, domain-shape, or wiki-title-ok. The description implies it is for path safety checks but provides no exclusions, prerequisites, or conditions that would help an agent decide between related shape-checking 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 provided, the description carries the full burden of behavioral disclosure. It states the output and source but does not explain what inputs are accepted, that unrelated inputs are discarded, what failure looks like, or what the returned coordinate format is. This is minimally transparent.

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 clean sentence with no filler or repetition. It is concise and front-loaded, though it is so terse that it sacrifices useful usage and parameter guidance.

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 description is too incomplete. It does not state which parameter to provide, what the response shape is, or how the Open-Meteo lookup is triggered, leaving an 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 coverage is 100%, so the schema already documents every parameter. The description does not add parameter-level meaning and, notably, never maps 'a place' to any specific parameter such as city or query. Baseline 3 is appropriate because the schema carries the detail.

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 output (latitude and longitude) and the data source (Open-Meteo), making the core purpose clear. It is not a tautology and it distinguishes geo-hint from weather- or time-focused siblings, though it lacks an explicit verb like '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?

No guidance is given about when to use this tool instead of weather-hint, timezone, or other siblings. The description also does not say which input parameter should carry the 'place' value, so an agent cannot infer the correct invocation pattern.

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

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

With no annotations, the description must carry the behavioral burden. 'Parse' implies a read-only extraction, which is helpful, but the description does not disclose what happens for invalid/non-GitHub URLs, whether other parameters are ignored, or what the result looks like. This is adequate but thin.

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 seven-word sentence with no filler. The core purpose is front-loaded and every word contributes.

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 no annotations, no output schema, and nine optional parameters, so the description needs to do more. It fails to identify the exact parameter to use, the return shape, or the behavior on invalid input. The sparse description is not enough for an agent to confidently invoke this tool among 27 siblings.

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

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

Schema coverage is 100%, so the baseline is 3. The description adds value by pinning the generic 'HTTPS URL to normalize or cite' schema field to a GitHub URL and implying the other eight optional parameters are not the relevant input. This disambiguation goes beyond the schema, but it still leaves the parameter list noisy.

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 object: 'Parse owner and repo from a GitHub URL.' This clearly identifies the input type and expected extraction result, and it distinguishes the tool from siblings like normalize-url or domain-shape. Even though the schema is cluttered, the stated 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 intended use is implied: call this tool when a GitHub URL needs to be decomposed into owner and repo. However, there is no explicit when-to-use/when-not-to-use guidance or comparison with the many related URL/shape siblings, so the agent has to infer the conditions.

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 does reveal that titles are discarded and that the count reflects current front-page stories, which implies a read-only aggregate operation. However, it doesn't explain how the nine parameters are treated, what happens on failure, or whether any arguments are required or 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 concise and front-loaded, with the core action in the first sentence and a compact output-boundary note in the 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?

Despite the simple purpose, the tool has nine optional parameters and no output schema or annotations. The description doesn't specify the return type/format, which parameters are relevant, or whether calling with no arguments is the intended usage. This is insufficient for confident invocation 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 each of the nine parameters already has its own description, setting a baseline of 3. The tool-level description adds no additional parameter meaning: it never says which parameters, if any, are relevant to counting HN front-page stories, or whether all are optional and effectively ignored.

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: count current Hacker News front-page stories. 'Titles discarded' further clarifies that it returns only a count, not story titles. It doesn't explicitly name a sibling alternative, so it falls 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?

The description implies when to use the tool: when you need a count of current HN front-page stories and not titles. However, it provides no explicit alternatives or when-not-to-use guidance, and it doesn't relate the usage to the many optional parameters.

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, and the description does not disclose return format, side effects, network behavior, or argument requirements. It also fails to clarify why nine unrelated parameters exist 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 brief, but brevity here is under-specification rather than conciseness. A single fragment omits essential functional information and is not structured for scanning.

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 one-line description is not enough to invoke this tool correctly. It does not specify expected arguments, output shape, or relationship to the nine parameters, leaving an 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?

The input schema already contains descriptions for all 9 parameters (100% coverage), so the baseline applies. The description adds no parameter-level meaning and does not reconcile the zone-list purpose with parameters like ref, url, or json.

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 'Common IANA timezone names for clock calls' is a noun phrase, not a statement of function. It largely restates the tool name ('iana-zones') and does not say whether the tool lists, returns, or checks zones, nor how it relates to the timezone/utc-time siblings.

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

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

No guidance is given about when to call this tool instead of alternatives like timezone or utc-time. The phrase 'for clock calls' is too vague to constitute actionable usage direction.

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

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

With no annotations, the description carries the behavioral burden. It discloses a read-only network fetch and the output restriction, and 'public' implies no auth. However, it does not state behavior for missing or invalid robots.txt, which inputs are used or ignored, 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?

The description is one front-loaded sentence with no filler. It is efficient, though slightly too sparse given the mismatched 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, seemingly unrelated parameters, no output schema, and no annotations, the description is too thin to resolve how to invoke the tool or what the returned group-count structure will be. Critical context for correct invocation is missing.

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

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

Although schema coverage is 100%, the parameter descriptions are generic and mostly unrelated to robots.txt. The description does not identify which of the nine optional parameters supplies the robots.txt source, so an agent cannot reliably map the stated purpose to 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 verb and resource ('Fetch a public robots.txt') and an explicit output contract ('return group counts only'). This clearly distinguishes it from generic siblings like web-fetch and 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 a use case—when robots.txt group counts are needed—but provides no when-not-to-use guidance and names no alternative tools. An agent cannot tell when this should be preferred over web-fetch or normalize-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 only disclosed behavioral trait is 'Key discarded,' which suggests the input is not retained. But with no annotations and no output schema, the description does not explain what a 'shape check' returns, what counts as valid, or how errors are surfaced. The agent is left guessing about observable 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 and front-loads the core purpose. It contains no filler, and the second sentence does add a behavioral note about discarding the input. It loses one point because the brevity leaves 'Key discarded' ambiguous and does not compensate for the schema mismatch.

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 severely incomplete. It does not specify the expected Jira key format, which parameter to pass, what the result looks like, or whether the check returns a boolean or an error. An agent cannot reliably invoke this tool based on the provided definition.

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 every schema parameter has a description, the description refers to a 'key' that does not appear anywhere in the input schema. The schema exposes ref, url, city, feed, host, json, path, zone, and query, none of which is identified as the Jira key. The description fails to resolve this mismatch, so an agent cannot know which parameter 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 clearly states the operation and target: 'Check a Jira issue key shape.' This is specific enough to distinguish it from sibling shape-checkers like domain-shape, figma-url-shape, and github-repo-shape, since it names the exact resource type being validated.

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: when an agent needs to validate the shape of a Jira issue key. However, it provides no explicit guidance about when not to use it, nor does it mention alternatives from the sibling list.

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 behavioral disclosure burden. It clearly states that only the HTTP status matters and that the body is discarded, which is a meaningful behavioral trait that prevents an agent from expecting content. It does not cover network side effects, redirects, or error semantics, but for a simple status check the disclosed behavior is useful.

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 core fact is front-loaded and the behavioral caveat is placed immediately after. Every word earns its place.

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

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

For a simple status-check tool, the description conveys the core return and the no-body behavior. However, with no annotations, no output schema, and several optional heterogeneous fields in the input schema, the description does not fully explain which parameter to provide or how this tool relates to the many URL/status siblings.

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 does not map the 'public library docs URL' to a specific parameter such as url or host, nor does it clarify that many of the schema properties are discarded after related checks. It adds minimal meaning beyond what the schema already provides.

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

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

The description clearly indicates that the tool returns an HTTP status for a public library docs URL and that the body is discarded. However, it does not explicitly distinguish this from overlapping siblings like fetch-status or browser-url-ok, and the term 'hint' leaves the exact action slightly implicit.

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

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

The intended context is implied: use this when you need the HTTP status of a public library docs URL. There is no explicit when-not guidance or mention of alternatives among the many URL-related sibling tools, so an agent must infer the selection 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?

The description discloses the key behavioral trait that values are discarded, which is useful given that no annotations are present. However, with no annotation coverage, it does not say whether nested keys are counted, whether invalid JSON is an error, or how the count behaves on non-object inputs.

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 core operation is front-loaded. 'Values discarded' earns its place by communicating an important 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 optional parameters, no output schema, and no annotations, this description is too thin. It does not clarify which parameter is the JSON input, whether counting is top-level only or recursive, or what exact result the agent should expect beyond the word 'count.'

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 already individually documented and the baseline is 3. The description adds no additional parameter-level meaning, such as which parameter should contain the JSON object or how the other eight optional parameters relate to the counting operation.

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: count keys in a JSON object, and adds a meaningful semantic in 'Values discarded.' It is clear enough to separate this from validation-style tools, though it does not explicitly distinguish itself from sibling tools or explain the 'memory' part of the name.

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

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

There is no guidance about when to use this tool versus alternatives such as validate-json, hn-front-count, or search-query-len. No exclusions, conditions, or alternative tool names are provided, so an agent must infer the intended use from the name and one-line description.

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

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

With no annotations, the description carries the burden, and it does disclose a meaningful behavioral trait: query and fragment are dropped from the returned URL components. However, it does not state return format, failure behavior, validation rules, or whether any network activity occurs, so the disclosure 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?

Two tightly written sentences with the main return value front-loaded and no filler. Every phrase earns its place.

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

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

For a tool with no output schema, no annotations, nine optional parameters, and a large family of URL-related siblings, this description is too sparse. It omits the output format, prerequisites such as requiring url, and any decision guidance among the sibling tools, so an agent cannot fully 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 description adds no parameter-level meaning beyond the schema; it only implicitly highlights url as the relevant input. The many unrelated optional parameters remain confusing, but the schema already documents each one.

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 — return origin, host, and path — and specifies that query and fragment are dropped, which distinguishes URL normalization from the many sibling URL/check tools. It is clear enough that an agent can tell what the tool does, though it does not explicitly name alternatives or define the exact output 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?

No guidance is given about when to use normalize-url versus siblings such as browser-url-ok, figma-url-shape, domain-shape, web-fetch, or citation. The description does not mention context, exclusions, or alternatives, leaving the choice 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?

The description does disclose one notable behavior: 'No browser is launched.' However, it does not clarify whether the tool performs a live network fetch, a syntactic shape check, or something else. The schema's repeated 'discarded after the shape check' phrasing suggests a non-executing validation, which partially contradicts the 'can be opened' wording. With no annotations, this ambiguity leaves important behavioral characteristics 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 only two sentences and gets to the point immediately: the primary verb, target resource, and a critical qualifier. It is economical and front-loaded. A slightly richer explanation of what 'opened' means would be helpful, but the structure itself is strong.

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 eight disparate parameters, no output schema, and no annotations, the description leaves too much unresolved. It does not explain which parameter to set for a given request, whether the parameters are mutually exclusive, or what result the agent should expect. Schema descriptions help per-parameter but do not compensate for the missing overall invocation 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?

The input schema provides descriptions for all parameters, so the baseline is 3. The tool description itself adds no parameter-specific meaning and, if anything, obscures the relationship between the URL-focused name and the wide variety of alternate inputs. Since schema coverage is high, the description's lack of param detail is acceptable, but the mismatch between description and param list prevents a higher score.

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

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

The description states a specific verb and resource: 'Check whether a URL can be opened.' This is clear and actionable. However, it does not distinguish itself from sibling tools like browser-url-ok or web-fetch, and the input schema includes many unrelated parameters (city, feed, json, path) that muddy the apparent URL-only purpose.

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

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

No guidance is provided on when to use this tool versus alternatives. The only hint is 'No browser is launched,' which implicitly contrasts with browser-based checkers, but no sibling name or explicit condition is given. An agent must infer the applicable 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 behavioral burden. It does disclose a key behavioral trait: 'Query discarded.' However, it does not describe the return value, error behavior, or what happens when non-query parameters are supplied.

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 action is front-loaded, and the discard note is a relevant secondary detail. Every sentence contributes meaningful information.

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

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

The tool has no annotations, no output schema, and nine optional parameters, yet the description gives no indication of which parameters are relevant, whether the others are ignored, or what the returned value looks like. This is insufficient for an agent to confidently invoke the tool correctly among the many schema fields.

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 confirming that the 'query' parameter is the subject of the length count; it does not clarify the roles of the other eight optional 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 clearly states the operation: count characters in a search query, and the resource is specific ('search query'). It is consistent with the 'query' parameter in the schema, though it does not explicitly distinguish itself from sibling count-like 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 about when to use this tool versus alternatives, no exclusions, and no mentions of sibling tools. The description simply states the operation, leaving the agent to infer appropriate usage without any context or conditions.

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 says 'Short catalog' and says nothing about side effects, return shape, or the fact that all 9 parameters are optional and mostly discarded. It also does not explain why a status-code catalog accepts unrelated parameters like 'city' or '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 one-sentence description is short, but it under-specifies the tool's action and usage instead of earning its place. It reads more like a label than a useful definition.

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?

No output schema or annotations exist, yet the description fails to explain what the agent should pass, what it will get back, or why the catalog accepts 9 optional input fields. An agent cannot reliably decide whether to invoke this tool or what result 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 each of the 9 parameters, including notes like 'discarded after the shape check.' The description adds no parameter-level meaning, which matches the baseline 3 for high schema coverage.

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

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

The description is a noun phrase, 'Short catalog of common HTTP status codes,' with no verb stating what the tool does or returns. It largely restates the tool name 'status-catalog' and does not differentiate it from siblings like 'fetch-status' 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?

No when-to-use or alternative guidance is provided. The description does not mention siblings or any conditions for choosing this tool over related tools in the list, leaving the agent without a clear selection 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 burden. It does disclose the key non-obvious behavior, 'Prompt discarded,' which prevents the agent from expecting prompt-dependent output. However, it does not state whether the listed parameters are used or ignored, nor describe side effects or permissions, though the tool is unlikely to have any.

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 the result front-loaded and no filler. Every word contributes either the core purpose or the essential caveat.

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 stateless template-returning tool this is acceptable, but it leaves ambiguity: no output schema exists to clarify the template's contents, and the description does not explicitly say all parameters are optional/ignored or that the tool can be called with no arguments. The 9-parameter schema is fully documented, which partly compensates.

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 and the description need not restate parameter meanings. The description only adds the ambiguous 'Prompt discarded' note, which does not map to any schema property, and adds little to the already descriptive parameter comments.

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 and result: 'Return a three-step thinking template.' It is clear what the tool does and the resource is unique among the sibling tools, though it does not explicitly contrast itself with any sibling.

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 this tool over alternatives or when not to use it. The only implicit hint is that a prompt is discarded, so it should be used when a generic template is wanted, but no conditions or exclusions are given.

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

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It states the result but does not describe output format, error behavior for invalid timezones, network behavior, or side effects. It also does not acknowledge that the input schema contains many unrelated parameters and no obvious timezone field.

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 filler. It is front-loaded and easy to parse. However, the conciseness comes at the cost of essential invocation details, so it is not maximally effective as a complete tool definition.

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 input parameters, no output schema, and no annotations, a one-sentence description is inadequate. It does not specify how to provide the timezone, what the response looks like, or why the schema lists unrelated parameters. An agent cannot reliably invoke this tool correctly from the given 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 coverage is 100%, which normally earns a baseline of 3, but the description adds no parameter-level meaning and, more critically, there is no schema parameter for a timezone despite the description's central requirement. The agent cannot determine how to supply the IANA timezone, so the high coverage does not compensate for this mismatch.

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

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

The description clearly states the tool's purpose: returning the current time for a specified IANA timezone. The qualifier 'named IANA timezone' distinguishes it from siblings like utc-time and iana-zones. It is specific and immediately understandable.

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 choose this tool over alternatives such as utc-time or iana-zones. There are no exclusions, prerequisites, or contextual hints beyond the basic implied use case of looking up a local time. An agent must infer appropriate usage without explicit direction.

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 of explaining behavior. It does not disclose that the seven input parameters appear to be irrelevant or discarded, nor does it state whether there are side effects, network access, or a specific timestamp format.

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

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

The description is extremely short and front-loaded, containing no wasted words. It is concise, though arguably too terse to convey the full context needed for the tool's unexpected 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?

With no annotations, no output schema, and a seven-property input schema, the description is materially incomplete. It does not specify the timestamp format (e.g., ISO 8601 vs Unix epoch), whether parameters are ignored, or how this tool relates to relevant siblings like 'timezone'.

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 seven parameters, giving more than 80% schema coverage, so the baseline is 3. However, the tool description itself adds no parameter context, and the parameter descriptions are oddly unrelated to a UTC timestamp tool, leaving ambiguity about whether they are actually used.

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 identifies the output value the tool provides, and the UTC qualifier distinguishes it from generic time tools. It lacks a verb and does not explicitly contrast with the sibling 'timezone' tool, so it does not quite reach 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?

No guidance is given about when to prefer this tool over alternatives such as 'timezone', nor are any exclusions or prerequisites mentioned. The implied usage—when you need the current UTC time—is not explicitly 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, the description must carry the behavioral disclosure burden. It does disclose that the body is discarded, implying no persistence or side effects, which is useful. But it does not describe the return value, error behavior, or whether anything else happens after validation.

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 core action is front-loaded and the discard behavior is stated in a second sentence that earns its place. This is appropriately concise for a validator 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?

The tool has nine optional parameters, no annotations, and no output schema, yet the description only explains the core validation action. It does not identify which parameter is the 'body', why the other parameters exist, or what the caller will receive as a result, making the definition incomplete for a tool with this much schema complexity.

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

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

Schema description coverage is 100%, so the baseline is 3 even without additional explanation in the tool description. The description adds no parameter-level meaning and loosely refers to 'body' rather than the `json` parameter, but the schema already 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 verb and resource: check whether a body is valid JSON. This clearly distinguishes the tool from the sibling validators, which target URLs, file paths, wiki titles, and other shapes. However, the term 'body' is not tied to any parameter name, which leaves mild ambiguity about what to pass.

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

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

The intended use is implied by the action itself: use this when you need to confirm that a piece of text is valid JSON. There is no explicit when-to-use guidance, no exclusion of alternatives, and no mention of how this relates to the many sibling validator 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 burden of behavioral disclosure. It implies a read-only network lookup but does not disclose potential side effects, error behavior, rate limits, or that the tool appears to accept many unrelated parameters that 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 words. It is concise, though slightly under-specified given the complexity of the schema and the number of 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 9 optional parameters, no annotations, and no output schema, yet the description only addresses one narrow aspect. It does not clarify what is returned, what units are used, whether a city is effectively required despite being optional in the schema, or how errors are handled.

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 meaning beyond the schema; it merely mentions 'city' while the schema already describes the city parameter and the discard behavior of the other parameters.

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

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

The description states a specific operation: retrieving the current temperature for a city via Open-Meteo. It is clear about the resource and action, but it does not differentiate itself from sibling tools or explain why weather-hint exists alongside similar 'hint' tools.

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

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

There is no guidance on when to use this tool versus alternatives. The description does not mention exclusions, prerequisites, or situations where a sibling tool would be more appropriate, 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 behavioral burden; it usefully discloses that response bodies are discarded. However, it omits other relevant behavior such as redirect handling, timeout/error behavior, and whether any headers beyond content type 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 short sentences with no filler; the core function and the body-discarding behavior are front-loaded. 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 a confusing multi-field schema, no output schema, and several sibling tools, the description is too sparse: it does not state the return format, error semantics, or which URL-like parameter is relevant. An agent would likely need to experiment or inspect other 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 parameters are documented in the schema, but the description does not identify which parameter it consumes, and the schema's url description ('normalize or cite') conflicts with the described fetch behavior. The presence of many seemingly unrelated params (city, json, path) makes it unclear what an agent should supply.

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 operation—returning HTTP status and content type for a public URL—and adds a decisive constraint that the body is discarded. This is clear enough to distinguish it from URL-normalization or body-fetch tools, though it does not explicitly name a sibling such as 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?

It implies the tool should only be used for public URLs, but gives no guidance about when to choose it over related tools like fetch-status, browser-url-ok, or normalize-url, and no when-not-to-use conditions.

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 does disclose that the title is discarded after the call, which suggests no persistence, but it omits the return format, network behavior, failure semantics, and any side effects. This is minimal disclosure.

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 the purpose front-loaded and no wasted words. The discard note is a bit unusual but not redundant enough to lower the score further.

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 parameters, no annotations, and no output schema, this description is severely incomplete: it does not define the return value, the required input, Wikipedia language/edition context, or the mismatch between the stated purpose and the actual schema.

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

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

The schema contains seven properties, all with descriptions, but none of them represents a Wikipedia title; they reference Git refs, URLs, cities, RSS feeds, JSON, hosts, and paths. The description introduces a 'title' concept that maps to no parameter, so an agent cannot determine 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 clearly states a specific verb ('Check') and resource ('whether a Wikipedia title exists'), which distinguishes it from sibling URL/shape validators. However, it does not explicitly differentiate itself from alternatives or explain how the title is supplied, so it is not 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 on when to use this tool versus siblings like status-catalog, domain-shape, or normalize-url. The only implied context is needing to verify a Wikipedia title, but no when-not or alternative routing is provided.

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