America/Santo_Domingo clock

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 explicitly notes that 'Task text discarded', which is a meaningful privacy and execution trait, and it lists what the tool returns. For a read-only lookup tool, this is adequate transparency without overclaiming 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, front-loaded sentences convey purpose, outputs, and a key behavioral caveat with no filler or redundant schema repetition. Every sentence 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?

With no output schema, the description compensates by explicitly listing the return artifacts (CLI setup, how-it-works, skill file, remote MCP hops). It does not specify whether any parameters are required or how they select the gateway, leaving minor invocation ambiguity, but the core context is sufficient.

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

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

The input schema already describes all seven parameters with 100% coverage, so the baseline is 3. The description adds no parameter-level meaning beyond the schema; it only clarifies that task text is discarded, which is not tied to a specific schema field.

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: 'Find a public pay-per-call tool gateway (Monid)'. It also enumerates concrete outputs (CLI setup, how-it-works, skill file, remote MCP hops), making the tool's role clear and distinct from the sibling shape-checkers and 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?

The description implies the intended use case: call this when you need a Monid pay-per-call gateway and its setup/skill files. However, it does not explicitly state when to prefer this tool over alternatives or when not to use 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?

With no annotations, the description must disclose behavioral traits itself. It does state 'No browser is launched,' which is a meaningful safety-oriented detail. However, it does not explain side effects, network usage, return behavior, or why several unrelated parameters (city, feed, json, path, zone, query) exist. The description is minimal and leaves key operational details unstated.

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

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

The description is two short sentences, front-loaded with the core purpose and a key behavioral caveat. It is efficient with no redundant phrasing. However, given the tool's complexity (9 parameters) and the absence of annotations, the brevity verges on under-specification; still, for what it does say, it is well-structured.

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

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

The description is incomplete for an agent to use the tool correctly. It does not clarify which parameter is the primary input (url), why the other parameters are present, or what the output looks like (e.g., a boolean or status). With no output schema and no annotations, the description should explain the return contract and the relevance of the extra parameters, but it does not.

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

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

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no parameter-specific meaning. According to the rubric, a baseline of 3 is appropriate when the schema carries the semantic weight. The description's lack of parameter details is acceptable given full coverage.

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

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

The description clearly states the tool checks whether a URL can be opened and explicitly notes no browser is launched. This conveys a specific action and resource. It does not explicitly name sibling tools, but the distinction from playwright-url-ok (which likely launches a browser) is implied. Given the many siblings, a little more differentiation would help, 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 gives no guidance on when to use this tool versus alternatives. It does not mention scenarios such as lightweight checks versus full browser rendering, nor does it exclude cases like normalization or fetching. An agent is left to infer usage from the name and the sibling list, which is insufficient for a tool with 9 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?

The annotations declare readOnlyHint=false, destructiveHint=true, and idempotenceHint=false, but the description never discloses what destructive or non-idempotent behavior occurs. 'Expression discarded' adds a small retention clue, but 'Evaluate' sounds like a pure read-only computation, which conflicts with the annotated destructive profile. There is no explicit contradiction strong enough to flag, but the behavioral disclosure is clearly inadequate.

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, which is superficially concise, but it is under-specified rather than efficiently specified. 'Expression discarded' is unhelpful because no expression parameter exists, and the brevity comes at the cost of omitting essential purpose and behavior 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?

This tool has seven heterogeneous parameters, no output schema, and annotations indicating destructive behavior, yet the description supplies almost none of the context needed to call it correctly. An agent cannot determine expected inputs, outputs, side effects, or appropriate invocation 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 coverage is 100%, so the baseline is 3, but the description actively harms parameter understanding by referencing 'a+b style arithmetic' when no such parameter exists. The schema descriptions themselves are the only useful signal, and the description adds no meaningful linkage to them.

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

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

The description claims the tool evaluates 'a+b style arithmetic', but the input schema exposes seven unrelated parameters (ref, url, city, feed, host, json, path) and no expression or operand field. This is actively misleading: an agent cannot tell what calc-eval actually does with these inputs, and the stated purpose is unsupported by the schema.

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

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

The description gives no guidance on when to use this tool versus its many siblings, and no conditions or alternatives are mentioned. Worse, the only implied use case—evaluating an arithmetic expression—is impossible given the schema, so the guidance is misleading rather than merely absent.

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

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

With no annotations, the description carries the full behavioral burden. It adds a useful non-storage guarantee: 'Page content is not stored.' However, it does not disclose network side effects, error behavior, rate limits, or what happens when no URL is 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?

Two sentences with front-loaded core output and a meaningful privacy note. Every sentence earns its place; there is no filler or redundancy.

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

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

The description names the return values and a key behavioral guarantee, but there is no output schema and no annotations. Given nine optional parameters and no required parameters, the description does not clarify the expected invocation shape or failure behavior. The schema compensates for parameter semantics but not overall 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add meaningful parameter-level detail beyond naming URL; the schema already documents each parameter, including discard behavior. No extra semantic value is provided.

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

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

The description states a specific verb and output: 'Return host, scheme, and HTTP status for a URL.' It clearly identifies what the tool does. However, it does not explicitly differentiate this from sibling URL/status tools such as fetch-status 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?

The description gives no guidance about when to use this tool versus alternatives. It does not mention exclusions, preferred conditions, or the fact that the other eight parameters appear to be discarded. The agent must infer usage from the schema.

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

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

No annotations are present, so the description carries the full behavioral burden. It discloses a meaningful privacy trait ('No identifiers are retained') and the verb 'show' implies a read-only operation, but it does not describe output format, side effects, or errors. This is partial but not full 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 only two short sentences with no filler, and the main action is front-loaded. The privacy statement earns its place, though the wording is so terse that it under-explains the tool's behavior.

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 heterogeneous string parameters, no annotations, and no output schema, the description does not explain what classifications are returned or how the parameters relate to each other. An agent cannot reliably determine the correct parameter choice or interpret the result.

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

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

All seven parameters have descriptions in the input schema, so schema coverage is high and the baseline of 3 applies. The tool description adds no per-parameter meaning and does not clarify whether parameters are exclusive or combined, but the schema already documents each field reasonably well.

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 ('show') and a resource ('how this request is classified'), but the classification scheme and what constitutes 'this request' are left vague. It does not differentiate the tool from sibling shape/check tools such as 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 this tool versus alternatives like normalize-url, validate-json, or domain-shape. The privacy statement implies safe handling, but no exclusions or selection criteria 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?

Annotations already carry readOnly/destructive/idempotence hints, so the description only needs to add behavior beyond safety. It does so by clarifying that the tool deliberately omits WHOIS/ownership data and by describing the splitting operation. It does not discuss invalid-hostname behavior, but that gap is minor for a read-only shape 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?

One sentence, front-loaded with the operation and immediately followed by the scope limitation. No filler or repetition of schema 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 simple read-only label-splitting tool, the description covers the core behavior and the output concept (labels) despite no output schema. It leaves edge-case behavior unspecified, but the schema's per-parameter discard notes and the low complexity make this acceptable.

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

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

The input schema already describes all properties, including 'host' as 'Public hostname', so the description adds little parameter-level meaning. It aligns 'hostname' with the host parameter but does not explicitly state which property to populate or that other fields are 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 names a specific verb ('Split'), a concrete resource ('a hostname'), and the product ('labels'), while the qualifier 'without WHOIS or ownership data' sets the scope boundary. This distinguishes it from sibling shape/URL tools without opening the schema.

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

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

The description implies usage for pure label extraction by stating what it does not include (WHOIS/ownership data), but it does not state when to choose this tool over alternatives or name a sibling tool. The when-not is present only by implication.

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 disclose the HTTP method (HEAD), the public-URL scope, and the status-only output, which implies a low-cost, side-effect-free read. However, it does not explain what happens for non-URL parameters or describe any error/rate-limit behavior; the discard behavior is only visible in parameter descriptions.

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 sentence with no filler: it front-loads the verb, states the resource, and specifies the output. It is as concise as possible while still conveying the core operation.

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

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

For a tool with 9 optional parameters, no annotations, and no output schema, this one-line description is incomplete. It explains only the URL case, gives no guidance for the other parameter types, and does not help the agent understand the response format or choose among the many sibling tools. The schema hints at broader capabilities, but the description does not tie them together.

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 main description adds little per-parameter meaning beyond 'URL', and the url parameter description ('normalize or cite') does not fully align with 'HEAD a public URL'. The individual parameter descriptions are informative, but the tool description does not connect them to the tool's overall 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 and resource: HEAD a public URL and return only the status. This is clear and can be distinguished from content-fetching tools. However, it does not address the additional parameters in the schema (ref, city, feed, json, path, zone, query), making the stated purpose narrower than the schema suggests.

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 'return status only' implies a lightweight status-check use case, but there is no explicit when-to-use or when-not-to-use guidance. With several URL-related siblings like web-fetch, browser-url-ok, playwright-url-ok, and normalize-url, the description does not clearly route the agent to this tool over 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 must carry the behavioral disclosure burden. It reveals one behavioral trait: the path is discarded. But it does not explain whether the tool validates, extracts, normalizes, or fetches anything, nor what happens with malformed URLs.

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-loads the key resource, which is good. However, 'Path discarded.' is a fragment, and the brevity crosses into under-specification rather than deliberate concise 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?

There is no output schema and no annotations, and the tool has nine parameters. The description only says to parse a Figma file URL and discard the path, leaving the return value, validation behavior, and parameter relevance largely unexplained.

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; 'Path discarded' at most reiterates the schema's note about the path parameter. With nine optional parameters, the intended relevant input is still somewhat ambiguous.

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: 'Parse a Figma file URL.' This is not a tautology and clearly names the target input. However, it does not say what the parse produces or how this differs from sibling URL-parsing tools like 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 about when to use this tool versus alternatives such as normalize-url, browser-url-ok, or github-repo-shape. The only contextual hint is 'Figma file URL,' but no exclusions, prerequisites, or alternative-selection conditions are provided.

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

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

With no annotations, the description carries the full burden; 'No disk access' is a useful explicit disclosure that this is a pure validation call. But it omits what counts as 'safe', whether it returns a boolean or error, and what happens with the other 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?

Two short sentences with no fluff and the key safety behavior front-loaded in the second sentence. The wording is efficient, though 'looks safe' is vague enough to keep it from being a perfect structural model.

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, and nine schema properties, this description is under-specified. It does not explain the return format, which parameter to pass, or why unrelated parameters like `url`, `city`, and `zone` are present, so an agent cannot reliably invoke it correctly.

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

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

Schema description coverage is 100%, so the baseline is 3; each parameter already has its own description. The tool description itself adds no parameter-level meaning and never points to `path` as the primary input beyond the tool name.

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 a specific verb ('Check') and resource ('whether a path looks safe') and adds a distinguishing constraint ('No disk access'), which separates it from URL or filesystem-access siblings. However, 'safe' is not defined, and the schema's many unrelated parameters slightly obscure the intended target.

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

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

No guidance is given about when to choose this tool over alternatives like browser-url-ok, normalize-url, or github-repo-shape. 'No disk access' implies it is appropriate for purely syntactic checks, but no explicit when/when-not conditions are provided.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Via Open-Meteo' hints at an external network dependency, but the description does not disclose that many schema fields are discarded after checks, whether a live lookup occurs, or what failures or return behavior to 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 one short, front-loaded sentence with no filler. It is arguably too terse given the 9-parameter optional schema, but as far as pure conciseness it is efficient.

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

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

For a tool with 9 optional parameters, no required parameters, no output schema, and no annotations, the description is far from complete. It leaves unclear how to invoke the tool, which parameter to use for a place, whether extra parameters are ignored or harmful, and what the exact response shape is.

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 themselves are informative. The tool description adds no parameter-level meaning and fails to identify which parameter represents the 'place' referenced in the description.

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

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

The description states the core output (latitude and longitude) and the provider (Open-Meteo), so an agent can infer this is a geocoding tool and distinguish it from weather-hint or timezone siblings. However, it is a noun phrase rather than a clear verb+resource statement, and it never maps "a place" to any of the 9 input parameters.

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

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

There is no guidance about when to use geo-hint versus alternatives like weather-hint, timezone, or iana-zones. It also does not state whether city is the intended input, whether multiple parameters can be combined, or what conditions make this tool the right choice.

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 'Parse owner and repo from a GitHub URL.' It does not explain that the tool likely discards irrelevant inputs, what it returns, or how it behaves on invalid, non-GitHub, or malformed URLs. The schema's mention of 'discarded after the shape check' hints at behavior the description itself never confirms.

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

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

The description is a single, front-loaded sentence with no filler or repetition. It is efficient, but it is so terse that it omits important behavioral and usage context, so it is not maximally effective for an agent.

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 seven optional, seemingly unrelated schema parameters, no output schema, no annotations, and no usage guidance, the description is not sufficient for correct invocation. An agent cannot determine whether to pass url, ref, or some other field to obtain owner and repo, nor what the result will look like.

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 description coverage is 100%, the property descriptions are generic and mismatched: 'url' is described as 'HTTPS URL to normalize or cite' rather than a GitHub URL to parse, and the other parameters (city, feed, host, json, path) appear unrelated to the tool's stated purpose. The tool description adds no mapping from these parameters to the parser's intended use, leaving an agent uncertain 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 states a specific verb ('Parse') and resource ('owner and repo from a GitHub URL'), making the tool's primary function immediately obvious. It also distinguishes it from sibling shape tools like domain-shape, figma-url-shape, and jira-key-shape by naming the GitHub context.

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, domain-shape, or other URL-oriented tools. The description implies usage when a GitHub URL is present, but it does not state any when-to-use conditions, exclusions, or alternative 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 disclosing behavioral traits. It does not mention side effects, permissions, rate limits, or any other operational details, leaving the agent without critical information about the tool's runtime 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 concise, consisting of two short sentences. It avoids unnecessary verbosity, though the second sentence ('Titles discarded.') is somewhat cryptic and could be integrated more clearly into the main statement.

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 and no output schema, yet the description fails to explain what these parameters do or what the expected output/results look like. This leaves the agent without essential context to call the tool effectively or interpret its outcomes.

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

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

The schema lists 9 parameters, each with a description, but these descriptions are entirely mismatched with the tool's purpose (e.g., 'Git ref name', 'City name for a public weather hint'). They appear to be placeholders from a template and provide no meaningful semantic explanation of how the parameters relate to counting Hacker News stories, effectively misleading the 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 clearly states the action ('Count') and the target ('Hacker News front-page stories'), making the tool's purpose immediately understandable. The phrase 'Titles discarded' adds a minor ambiguity, but the core intent is unmistakable.

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

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

The description provides no guidance on when to use this tool versus any alternative. It lacks any mention of conditions, prerequisites, or scenarios where this tool is preferred or required.

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 says nothing about behavior—no mention that inputs are largely discarded, that it performs a shape check, or what calling it returns. The schema's terse 'discarded after' notes hint at the behavior, but the description itself carries none of this burden, and no annotations were visible to fill the 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 front-loaded seven-word sentence with no wasted wording. It earns its place, though the brevity comes at the cost of the detail penalized 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?

For a tool with a large, confusing parameter list and closely related siblings, one clause is insufficient. The description does not explain what a 'clock call' is, how the tool relates to timezone/utc-time, or what output an agent should expect, and there is no output schema to compensate.

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?

Each of the many schema parameters has at least a one-line description, so schema coverage is high and the baseline of 3 applies. However, the description adds nothing to clarify these parameters, and the parameter set (ref, url, city, feed, host, json, path) appears mismatched with a timezone-name tool, which the description does nothing to reconcile.

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?

"Common IANA timezone names for clock calls" conveys the resource domain (IANA timezone names) and hints at a supporting role for clock-related tools, which loosely distinguishes it from siblings like timezone and utc-time. However, it lacks an explicit verb (list? validate? return?) and does not state the deliverable, so the tool's exact function is left to inference.

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 such as timezone, utc-time, or geo-hint. No alternatives, exclusions, or triggering conditions are mentioned, leaving the agent to guess whether this is a lookup, a validation, or a reference source.

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 behavioral burden. It frames the tool as a read-only network fetch and explicitly warns that only counts, not full content, will be returned. It does not disclose failure behavior, limits, or how extraneous parameters are handled.

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

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

The description is one short, front-loaded sentence with no filler. The key action and the 'counts only' limitation are communicated 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?

The tool has no output schema or annotations, and the seven parameters look unrelated to robots.txt. The description does not specify how to identify the target robots.txt or what the returned group counts look like, so an agent cannot reliably 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?

All seven schema parameters have descriptions, so the high-coverage baseline applies. The description adds no parameter-level meaning and does not state which parameter supplies the robots.txt URL, leaving some invocation 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 uses a specific verb ('Fetch'), names the resource ('public robots.txt'), and states the output ('group counts only'), so the intent is clear. It does not explicitly differentiate among sibling fetch/URL tools, but the distinctive result format helps.

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 web-fetch, fetch-status, or domain-shape. No conditions, exclusions, or preferred scenarios 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only says "Key discarded", which hints at no retention, but it does not describe the return value, validation strictness, error behavior, or side effects. This is a minimal hint, not a transparent contract.

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 sentences are brief and front-loaded, but the brevity is under-specification rather than effective conciseness. A validation tool with an apparently unrelated input schema needs more than a two-sentence summary.

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 a complex multi-field input schema. The description must explain which parameter holds the Jira key, what qualifies as a valid shape, and what the result looks like, but it explains none of these. The definition is severely incomplete for an agent to 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?

The schema contains many properties (ref, url, city, feed, host, json, path) with their own descriptions, but none clearly corresponds to a Jira issue key, and the description does not map the "key" to any parameter. Although schema coverage is high, the description adds no parameter-level meaning and leaves the agent unable to determine what to pass.

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

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

The description uses a specific verb, "Check", and names a specific resource, "Jira issue key shape", which distinguishes it from sibling shape-checking tools like github-repo-shape or domain-shape. However, it never states what a valid Jira issue key shape actually is, so the purpose is clear only at a high level.

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 wiki-title-ok or file-path-ok, and no exclusions or prerequisites are mentioned. The only implied usage is that Jira issue key validation is needed, but nothing helps the agent decide between this and similar shape-checking 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?

No annotations are present, so the description carries the transparency burden. It only states 'Body discarded', implying a read-only HTTP check, but gives no explicit side-effect information, error behavior, or handling of the multiple optional 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 text is very short and contains no fluff, which is positive. However, the brevity is achieved by omitting essential context, and the sentence 'HTTP status for a public library docs URL.' is a fragment rather than a complete explanation.

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

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

With nine optional parameters, no output schema, and no annotations, the description is far from complete. An agent cannot determine which input to provide, what the response format will be, or how the described HTTP status relates to the other parameters such as city, zone, or 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 descriptions cover all parameters but are formulaic and unhelpful, e.g. 'discarded after the shape check' and 'discarded after the length check'. They do not explain how each parameter relates to the stated HTTP-status purpose, making real semantics unclear.

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 ('HTTP status ... Body discarded') but the verb is implicit and does not clarify the tool's broader role. It also fails to account for the nine unrelated parameters, leaving the actual purpose ambiguous.

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

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

There is no guidance about when to use this tool instead of sibling tools such as fetch-status, browser-url-ok, or normalize-url. No conditions, comparisons, or selection criteria are provided.

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

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

With no annotations, the description carries the behavioral burden, and it does disclose the key trait that values are discarded. However, it does not state whether the tool reads persistent memory, whether it has side effects, or what the return value looks like, which is a notable gap for a tool with no output schema.

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

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

The description is two short front-loaded sentences with no filler, and both sentences contribute (the operation and the value-discarding behavior). It is concise, though the brevity comes at the cost of the missing context noted above.

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 output schema, and no annotations, the description is under-specified. It does not explain the expected return, how the optional parameters combine to form the JSON object, or whether the count is based on the arguments versus an internal memory object, so an agent cannot confidently invoke it correctly.

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

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

Schema coverage is 100%, so the baseline is 3, and the description adds no parameter-level meaning. The schema's per-parameter descriptions are comprehensive but describe values in unrelated tool contexts, leaving unclear how each optional string maps to the count; 'Values discarded' is the only relevant semantic hint.

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

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

The description states a clear verb and object ('Count keys in a JSON object') and adds the useful note that values are discarded, so it is not a tautology. However, it does not identify which JSON object is being counted (the call arguments, a memory store, or the `json` parameter) and does not differentiate itself from siblings like 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?

No when-to-use or when-not-to-use guidance is provided, and no alternative tools are named. The only implied use case is 'need a key count,' which an agent would have to infer from the tool name and the generic first 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?

Without annotations, the description carries the behavioral disclosure burden. It does reveal that query and fragment are dropped, which is useful, but it does not disclose how the many schema parameters are handled (e.g., ref, city, feed, json being discarded), potential errors, or response 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?

Two concise sentences with no filler. The core behavior is front-loaded ('Return origin, host, and path') and the key transformation ('Query and fragment are dropped') follows immediately.

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 URL-normalization tool, the description gives the essential output and transformation. However, the schema contains several seemingly unrelated parameters, and the description does not explain how they fit into the tool's behavior, leaving ambiguity for an agent choosing or invoking the tool.

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

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

The input schema already describes all parameters, including 'discarded after' notes. The description adds meaning for the url parameter by specifying output components, but it does not clarify the role of the other seven parameters 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 states the tool's function: 'Return origin, host, and path for a URL' and specifies that query and fragment are dropped. This distinguishes it from generic URL tools, though it does not explicitly name sibling alternatives.

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 related siblings like browser-url-ok, figma-url-shape, or playwright-url-ok. The description implies URL normalization but does not state exclusions or alternative 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 bears the full disclosure burden, yet it only reveals that no browser is launched. It does not state whether the tool makes a network request, what side effects (if any) occur, whether authentication is needed, or what the result means beyond 'can be opened'.

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 action and followed by a key qualifier. No filler or repetition.

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

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

For a tool with nine optional parameters, no annotations, and no output schema, the description is too sparse. It does not clarify which parameter should be supplied, what the expected return value looks like, or how 'can be opened' is determined, 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 description coverage is 100%, so the baseline is 3. The description itself adds no parameter-level meaning, but each parameter already has a description in the schema; the odd mix of unrelated parameters (city, query, ref) is not explained, which 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 names a specific action ('Check whether a URL can be opened') and resource (URL), and the sentence 'No browser is launched' separates it from browser-based siblings like browser-url-ok. However, it does not specify how the check is performed (HTTP status, DNS, renderability), so it stops short of a fully precise definition.

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 'No browser is launched' clause implies this is for quick reachability checks when browser rendering is not required, but it never names alternatives such as browser-url-ok or fetch-status, nor gives explicit when-to-use/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?

With no annotations, the description carries the full burden of behavioral disclosure. It discloses that the query is not retained, which is useful, but it does not explain what is returned (e.g., a number), how multiple parameters are handled, or whether any input is normalized or validated. The behavioral picture is extremely incomplete.

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

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

The description is short and front-loaded, with both sentences contributing meaning: the operation and the non-retention side effect. It is appropriately concise, though the missing parameter mapping makes the overall structure feel incomplete.

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

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

For a tool with seven input parameters, no annotations, and no output schema, this description is far too sparse. It does not state the return format, identify the relevant parameter, or explain error behavior. An agent would need significant tool-level context beyond the description to call this correctly.

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

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

The input schema individually describes seven parameters, so schema coverage is high, but the description fails to connect any of them to the concept of a 'search query.' Without that mapping, an agent cannot know which string to pass for character counting, undermining the value of the parameter descriptions.

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 verb and object: 'Count characters in a search query.' However, it never specifies which input parameter represents the search query, and the schema contains seven unrelated string parameters (ref, url, city, feed, host, json, path). The purpose is clear at a high level but ambiguous in terms of how to invoke the 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?

There is no guidance on when to use this tool versus alternatives, no mention of prerequisites, and no indication of which schema property to populate. The only behavioral hint, 'Query discarded,' does not help an agent decide when to select 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?

The description implies a read-only catalog but does not explain outputs, side effects, or whether inputs are actually used. With no annotations provided, the description carries the full transparency 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 a single short sentence with no redundant wording or filler. It is maximally concise for the information it conveys.

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 does not explain how the nine optional parameters relate to the tool, what the output format is, or what 'catalog' means in practice. Given no output schema and irrelevant-looking parameters, meaningful context 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 every parameter has a schema description, the parameters (ref, url, city, feed, host, json, path, zone, query) appear unrelated to an HTTP status code catalog. The description adds no clarifying meaning to these inputs.

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 as a short catalog of common HTTP status codes, so the basic resource is clear. However, it lacks an explicit action verb like 'returns' or 'lists,' and does not distinguish this from sibling 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?

No guidance is provided about when to use this tool versus alternatives such as fetch-status or web-fetch. The description gives no conditions, examples, or exclusions.

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

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

It discloses one meaningful behavioral trait: 'Prompt discarded,' which tells the agent the prompt is not used. However, with no annotations and seven optional parameters, the description does not clarify whether the parameters affect the output or are ignored, nor what the returned template actually contains. Some behavioral transparency is present, but the description carries more of the burden than it should.

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 purpose is front-loaded, and 'Prompt discarded' is a compact, valuable addition. Every word earns its place.

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

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

For a tool with a 7-parameter schema and no output schema, the description is too thin. It does not explain the return value's structure, whether parameters should be populated at all, or how the template might vary. The schema descriptions help, but the overall definition still leaves an agent uncertain about 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?

All seven parameters have individual schema descriptions explaining their intended use and discard behavior, so schema coverage is essentially complete. The tool description itself adds no parameter-level meaning, so the baseline score of 3 applies.

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

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

The first sentence names a specific verb and resource: 'Return a three-step thinking template.' It is not a tautology and clearly states the core action. However, it doesn't explicitly distinguish itself from sibling tools, though no sibling appears to offer this same template behavior.

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

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

There is no guidance on when to use this tool versus alternatives, and no mention of prerequisites or typical invocation context. The phrase 'Prompt discarded' hints that the tool ignores prompt content, but it never says when choosing 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?

No annotations are present, so the description carries the full burden of behavioral disclosure. It only states the output and does not mention input validation, return format, or what happens when no valid timezone is provided. The schema's unrelated parameters make the actual behavior even less 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, front-loaded sentence with no filler. It is concise but slightly under-sized for the schema complexity, since it omits the critical 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?

For a tool with seven unrelated optional-looking parameters and no output schema or annotations, a one-line description is thoroughly inadequate. An agent cannot infer which parameter to supply or what response 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?

The description's 'named IANA timezone' maps to no property in the schema; the seven listed params (ref, url, city, feed, host, json, path) are individually described but have no connection to the tool's purpose. The description sets expectations that the schema contradicts, so an agent cannot determine 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 tool's goal: return the current time for a named IANA timezone, which distinguishes it from siblings like utc-time and iana-zones. However, it lacks an explicit verb and, more importantly, does not align with the input schema, which contains no timezone parameter.

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: use this when you need current time in a specific IANA timezone. There are no explicit when/when-not statements, alternatives, or prerequisites, and the schema mismatch means the guidance is not actionable.

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, but it only states the output. It does not mention that the nine optional parameters are effectively irrelevant or discarded, that no input is needed, that the operation has no side effects, or what timestamp format will be 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 very short and front-loaded, with no filler. However, it is under-specified for a tool that has nine optional parameters and surprising discard-behavior, so the brevity sacrifices important context that the agent would need.

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 not complete given the tool's actual complexity: it fails to explain that all parameters are optional/ignored, when to choose this tool over siblings, or what format the timestamp takes. Since there is no output schema, the description should have provided more return-value details.

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 each parameter in detail. The description adds no parameter semantics and does not clarify why unrelated parameters such as ref, url, city, and json appear in the schema. The baseline of 3 applies because the schema carries the semantic load.

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

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

The description 'Current UTC timestamp' clearly states what the tool produces: a current UTC timestamp. It is not a vague restatement, but it lacks an explicit verb and does not contrast with sibling tools such as timezone, so it does not fully differentiate.

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 about when to use utc-time versus alternatives like timezone or other sibling tools. There are no usage conditions, exclusions, or alternative references, leaving the agent to infer appropriate selection.

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

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

The description discloses only that the body is discarded. With no annotations present, it fails to state whether the tool returns a boolean, raises an error on invalid JSON, or how strict the validation is. This leaves a significant behavioral 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?

Two short sentences, front-loaded with the purpose and a clear behavioral note about discarding. There is no wasted text.

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 incomplete: it omits return format, invalid-JSON behavior, and which parameter is the 'body'. The presence of several unrelated parameters adds confusion that the description does not resolve.

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

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

All seven parameters have schema descriptions, so schema coverage is high and the description adds little per-parameter meaning. The description does not clarify that 'json' is the only relevant parameter and that the other fields are accepted but ignored, which would be valuable given the large schema.

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

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

The description states a specific action, 'Check whether a body is valid JSON', with a clear resource. It is not a tautology and naturally distinguishes this tool from the sibling shape-validation tools because it is the only JSON-specific validator.

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

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

No guidance is given about when to use this tool versus any alternative, nor are there exclusions or warnings. An agent is not told, for example, to use this before parsing JSON or to prefer another tool for non-JSON validation.

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 only mentions the data source and result, with no disclosure of caching, failure behavior, rate limits, data freshness, or whether this is a read-only operation.

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

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

The description is a single concise sentence with no filler. Its brevity is a strength, though it sacrifices useful contextual detail that would earn 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?

The tool has a large, seemingly unrelated input schema and no output schema or annotations. The description is too minimal to account for why many parameters exist, how the city parameter should be formatted, or what the agent should expect in response.

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 detailed descriptions for all parameters, including that most are discarded. The description adds little beyond this, but it does confirm that 'city' is the meaningful parameter for a weather hint. With high schema coverage, baseline 3 is appropriate.

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

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

The description clearly states a specific verb and resource: returning current temperature for a city via Open-Meteo. It differentiates this tool from geo-hint and lib-docs-hint, though it doesn't explicitly name sibling alternatives.

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

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

No guidance is given about when to use this tool versus alternatives, what inputs are required, or what qualifies as a valid city. The description implies a simple lookup but leaves all selection and invocation decisions to the agent.

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

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

With no annotations, the description carries the burden and does disclose one useful behavioral trait: the response body is discarded rather than returned. However, it leaves out redirects, timeouts, error behavior, and the network/privacy implications of fetching an arbitrary public URL, so the transparency 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 compact and front-loaded: the main outcome appears first, and 'Body discarded' is a useful one-line qualifier. It is efficient, though perhaps too terse given the schema's complexity.

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 several closely related siblings, yet the description only covers the high-level URL case. It does not explain what happens with the other parameters, what the return shape is, or when a sibling tool would be more appropriate, leaving important context 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 has 100% description coverage for all 9 optional parameters, so the baseline is 3. The tool-level description adds only the URL/body framing and does not explain how the many optional 'discarded' parameters interact or which one should be provided for which task.

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 returns HTTP status and content type for a public URL and that the body is discarded. This is a specific operation with clear scope, though it does not differentiate itself from similar siblings like fetch-status or browser-url-ok, and it ignores most of the 9 input parameters.

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 web-fetch versus sibling tools such as fetch-status, normalize-url, or browser-url-ok. The only contextual hint is 'public URL', which implies not for authenticated/private resources, but there are no explicit exclusions or alternative routing.

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 offers a single behavioral note—'Title discarded after the call'—which suggests the input is not persisted. But this note refers to a 'title' that is absent from the schema, and nothing is disclosed about read-only status, network dependency, error behavior, or return format. With no annotations present, the description carries the full burden and fails to cover these essentials.

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 front-loads the main purpose effectively. However, the second sentence about the title being discarded is confusing and redundant given the schema mismatch, so not every sentence 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 validation tool with seven generic parameters, no annotations, and no output schema, this description is critically incomplete. An agent cannot determine which parameter carries the Wikipedia title, what response to expect, or when this tool is appropriate, making successful invocation nearly impossible without external knowledge.

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%—every parameter has a description—so the baseline is 3, but the tool description actively misleads by referring to a 'title' parameter that does not exist in the schema. It provides no mapping from the stated purpose to any of the seven actual parameters, undermining the agent's ability to construct a correct 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 concrete action and resource: 'Check whether a Wikipedia title exists.' However, the input schema contains no 'title' parameter—instead there are unrelated fields like 'ref', 'url', and 'city'—so the core purpose does not map cleanly onto the tool's actual inputs. It also does not differentiate this from the many sibling '-ok' validation tools.

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

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

No guidance is given about when to reach for this tool versus alternatives like browser-url-ok, file-path-ok, or web-fetch. There are no context conditions, exclusions, or mentions of a sibling tool for different input types.

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