Currency TWD

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

With no annotations, the description carries the behavioral burden and does disclose that task text is discarded and that the call returns setup artifacts. This indicates a non-executing, stateless lookup. It stops short of detailing network/cost side effects, but the pay-per-call phrase and output list provide adequate transparency for a simple index 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?

Three short sentences, front-loaded with the core purpose, then outputs, then an important behavioral note. No wasted words and no repetition of the schema.

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

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

The description names the tool's purpose and outputs, which is helpful given no output schema. However, with nine optional heterogeneous parameters and no guidance on which to provide (or whether a zero-argument call is intended), an agent has to infer the invocation. The sibling set is large, and the description doesn't explain how this tool relates to the other lookup/check tools.

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

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

Schema description coverage is 100%, so each of the nine parameters already has a description. The tool description adds no parameter-level meaning beyond the schema, so the baseline of 3 is appropriate; it neither clarifies how parameters map to the Monid lookup nor conflicts with 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 opens with a specific verb and resource ('Find a public pay-per-call tool gateway (Monid)') and enumerates concrete outputs ('CLI setup, how-it-works, skill file, and remote MCP hops'). This clearly identifies the tool's role and differentiates it from the sibling utilities, none of which mention a Monid gateway lookup.

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

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

It gives a clear context for use—looking up the Monid gateway and its setup artifacts—so an agent can decide when this is the relevant tool. It also states a constraint ('Task text discarded') that sets expectations, though it doesn't explicitly name alternatives or when-not conditions beyond that.

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

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

With annotations already indicating readOnlyHint=maybe and sideEffectsHint=likely, the description adds the key negative behavior 'No browser is launched' but leaves unclear whether a network request is made or what 'opened' implies (status code, DNS, 2xx check).

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

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

Two short sentences, purpose stated first and a key behavioral constraint second. No filler or repetition of schema details.

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

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

With seven parameters and no output schema, an agent cannot determine what the tool returns or how 'can be opened' is decided. The odd mix of params (city, json, path) is not explained, so the description feels incomplete for real use.

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 only 55%, so the description should compensate, but it adds no parameter-level guidance. It mentions 'URL' while the schema includes unrelated params like city, json, and path, leaving mapping 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?

States a specific verb ('Check') and a clear resource ('whether a URL can be opened'), and the second sentence ('No browser is launched') distinguishes it from sibling tools like playwright-url-ok that actually launch a browser.

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?

Implies a lightweight check without browser side effects, but never explicitly names alternatives or conditions for when to use it instead of normalize-url, fetch-status, or playwright-url-ok.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The only disclosure is 'Expression discarded,' a useful no-retention hint, but everything else — return behavior, side effects, how the evaluation result is surfaced — is omitted. The disclosure is also unanchored because no schema parameter accepts the expression that is supposedly 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?

Two sentences, no filler, and the operative phrase 'Evaluate a+b style arithmetic' is front-loaded. The length is proportionate to the minimal content it carries, making this the strongest dimension.

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 unannotated parameters, no output schema, and a large sibling family, a single sentence is grossly insufficient. The description never explains what the tool returns, how the nine parameters relate to the stated purpose, or when to prefer it over siblings. An agent has no basis to call this tool correctly.

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

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

Schema coverage is 100%, placing the baseline at 3, but the description adds no meaning to any of the nine parameters. Worse, its 'a+b style arithmetic' promise implies an expression parameter that does not exist, so cross-referencing description with schema actively confuses parameter selection. This justifies below-baseline scoring.

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 — 'Evaluate a+b style arithmetic' — which is clear in isolation. However, it is misleading in context: none of the nine schema parameters (ref, url, city, feed, host, json, path, query) can plausibly carry an arithmetic expression, so the stated purpose cannot be acted on. It also does nothing to distinguish this tool from its 26 siblings.

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

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

There is no when-to-use, when-not-to-use, or alternative guidance anywhere in the description. With 26 siblings such as normalize-url, validate-json, and web-fetch covering the schema's actual parameter domains, an agent gets no signal about when to pick calc-eval instead. This is a total absence of routing information.

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 transparency burden. It does disclose a meaningful privacy trait: 'Page content is not stored.' However, it does not mention network access, rate limits, or that the many non-URL input parameters are irrelevant, leaving some behavioral context unspecified.

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

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

The description is two short sentences with no filler. The main action and outputs are front-loaded, and the second sentence is a relevant caveat. Every word earns its place.

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

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

The description is adequate for a small metadata/status tool, and the schema compensates for parameter ambiguity. However, with nine optional parameters and no output schema, it would be clearer if the description explicitly stated that only the URL parameter is used and the others are ignored. This is a modest but real gap.

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

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

Schema description coverage is 100%, and each parameter already has a description, including the relevant 'url' field. The description adds the connection between URL input and the host/scheme/status output, but it does not meaningfully clarify parameter selection beyond what the schema already provides. 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 what the tool does: 'Return host, scheme, and HTTP status for a URL.' This is a specific action with concrete outputs and is not a tautology. It does not explicitly distinguish from sibling tools like fetch-status or normalize-url, but the stated purpose is understandable on its own.

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 'use this when' statement or named alternative tool. The caveat 'Page content is not stored' weakly implies this is for metadata/status rather than content retrieval, but the agent must infer routing from that. This is implied usage guidance, not clear exclusions or alternatives.

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

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

With no annotations provided, the description carries the full burden. It does disclose a meaningful behavioral trait: 'No identifiers are retained' indicates privacy and non-persistence. However, it does not clarify side effects, whether any external calls occur, or how the request is processed beyond classification.

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 main action is front-loaded and the privacy guarantee earns its place as a distinct, useful 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?

Despite the schema covering each parameter, the tool has 9 optional inputs and no output schema. The description does not explain what the classification output looks like, how the parameters relate to the classification, or what makes this tool useful in context. One vague sentence is insufficient for a multi-input classification tool.

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

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

Schema description coverage is 100%, so all parameters are already documented in the input schema. The description adds no parameter-specific meaning; it only adds a general privacy note. This matches the baseline for high schema coverage.

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

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

The description states an action ('Show how this request is classified') but leaves the classification concept undefined. It is not a tautology, but it does not clearly specify what the classification is, what inputs drive it, or how it differs from sibling classification tools like domain-shape or validate-json.

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

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

No guidance is given about when to use this tool versus the many sibling tools. The description does not mention alternative tools, prerequisites, or conditions that would 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?

There are no annotations, so the description carries the full burden of behavioral disclosure. It only reveals that the tool does not provide WHOIS or ownership data; it says nothing about return format, invalid-hostname handling, network access, normalization behavior, or side effects. This is too thin for a tool with no annotation safety net.

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

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

The description is a single, front-loaded sentence with an active verb and no filler. The WHOIS caveat earns its place by clarifying scope. It is easy to scan and appropriately sized for its core message.

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

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

Given nine optional parameters, no output schema, and no annotations, the description is not complete enough for reliable invocation. An agent cannot determine what the expected output looks like, which parameter is the true input for hostname splitting, or how non-host parameters should be treated. The scattered 'discarded' notes in the schema help somewhat but are not connected to the description.

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 a meaningful description. The tool description adds the 'hostname' framing that maps to the 'host' property, but it does not explain why the other eight parameters exist or whether they are ignored. It neither substantially compensates for nor worsens the schema information.

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: 'Split a hostname into labels'. It also draws a boundary by adding 'without WHOIS or ownership data', which helps separate it from domain-lookup tools. However, it does not reconcile this clear purpose with the schema's nine unrelated optional parameters, which creates some ambiguity.

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 use case is implied: use this tool when you have a hostname and need it split into labels. The 'without WHOIS or ownership data' caveat acts as a scope exclusion, but no alternative tool is named and there is no guidance about which of the nine optional parameters to provide. It is enough to infer basic usage, but not enough to disambiguate the broad 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?

Without annotations, the description still discloses the request method (HEAD), the target scope (public URL), and the output scope (status only), which conveys a non-destructive network request. It does not cover redirect/timeout/error behavior, but for a simple status-check tool the core behavior is 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?

One short, front-loaded sentence with no filler; the verb and object are immediately clear and 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 nine optional parameters and no output schema or annotations, a one-sentence URL-only description is inadequate. The agent cannot tell whether to pass url, json, city, or multiple fields, or what the returned 'status' represents across those modes.

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 only that the URL should be public, which is a minor clarification. It does not help disambiguate the nine optional parameters or their combination rules.

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

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

The description states a specific action ('HEAD'), a resource ('a public URL'), and a narrow output ('status only'), so an agent can tell this apart from content-fetching tools like web-fetch. It is clear, though it does not name alternatives such as browser-url-ok and does not address the other eight schema inputs.

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 wording implies the tool is for cases where only an HTTP status is needed, but it gives no explicit when-to-use or when-not-to-use guidance and names no sibling alternatives. With nine optional parameters, it also does not say which parameter to supply for which intent.

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 one meaningful trait: the path is discarded. However, it does not describe the return value, validation behavior, or how other URL components are handled, leaving significant behavioral 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 two short sentences with no filler, and the main action is front-loaded. The path-discard note is a meaningful behavioral detail that earns its place.

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

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

The tool has 9 optional parameters, no required parameters, no output schema, and no annotations, so the description must compensate. It identifies the resource type and one discarded component, but it does not explain what a successful parse returns or which parameter should carry the Figma URL, leaving too much to inference.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds a useful hint that the relevant URL is a Figma file URL, narrowing the generic 'url' parameter. But it does not explicitly name which parameter to populate, and 'Path discarded' could be confused with the schema's 'path' property.

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

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

The description uses a specific verb and resource ('Parse a Figma file URL') that distinguishes this tool from siblings like github-repo-shape and jira-key-shape. It does not explicitly explain what the parse result means, and 'Path discarded' is terse, but the core intent is identifiable.

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 use when the agent has a Figma file URL, and the tool name reinforces that. It does not name alternative tools or state when not to use this tool, so the usage guidance is only implicit rather than explicit.

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

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

'No disk access' is a meaningful behavioral disclosure beyond any annotation: it tells the agent the check is purely syntactic and side-effect-free, so no filesystem permission or existence check is involved. It does not state the return format, but for a boolean-style checker this is a reasonable level of 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?

Two short sentences with no filler. The core action is front-loaded and the important side-effect constraint 'No disk access' 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 tool with nine optional parameters and no output schema, this description is too thin. It leaves the agent unsure whether the other schema fields are valid inputs, what the return value is, and when a path would be considered 'safe' from a shape standpoint.

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 nine parameters with 100% coverage, so the description adds little parameter-level meaning. It clarifies that 'path' is the focus, but does nothing to reconcile why the schema also accepts ref, url, city, feed, host, json, zone, and query.

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 clear verb and resource: it checks whether a file path looks safe, and adds the key constraint 'No disk access.' This distinguishes it from URL/title/query validators in the sibling list by narrowing the scope to file paths.

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 a file path needs a safety/shape check) but gives no explicit alternatives or exclusions, such as 'use normalize-url for URLs' or 'does not verify existence on disk.' The usage context is inferable but not 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 carries the full behavioral burden, yet it only names the external provider. It does not disclose that this is a network-backed lookup, what happens on failure, whether any state is retained, or what exact payload 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 a single nine-word phrase with no filler; it front-loads the output and the provider. It earns its place despite being terse.

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, this is incomplete: an agent does not know which parameter to pass, what the returned coordinates look like, or what error conditions exist. The presence of eight other optional parameters makes this ambiguity 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 coverage is 100%, so the baseline is 3 despite the description containing no parameter details. The description does not map 'place' to the city parameter, and the schema's unrelated optional fields (ref, json, feed, etc.) could confuse selection, but the city property is present and documented.

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 concrete outcome — latitude and longitude for a place — and names the data source (Open-Meteo). It lacks an explicit verb and does not contrast with sibling tools, but the intent is reasonably unambiguous.

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

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

No when-to-use or when-not-to-use guidance is provided, and no alternatives are named. 'For a place via Open-Meteo' weakly implies geocoding, but does not explain when this tool should be selected over weather-hint or other lookup 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 behavioral burden. It clearly indicates a pure parsing operation with no side effects, but it does not disclose how invalid or non-GitHub URLs are handled, nor what the exact return shape is.

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

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

The description is a single direct sentence with no filler. It front-loads the essential information and 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 parser, the description is minimally adequate: an agent can likely infer that `url` is the relevant input. However, with no output schema, no required parameters, and no error/edge-case behavior, the tool contract is incomplete.

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 GitHub-specific meaning to the `url` parameter and implies owner/repo as output, but it does not state that `url` is required or clarify the role of the many other accepted 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 action ('parse') and a specific resource ('owner and repo from a GitHub URL'). This clearly distinguishes it from sibling shape tools like domain-shape, figma-url-shape, or jira-key-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?

The description implies when to use the tool: when an agent has a GitHub URL and needs the owner and repo. However, it gives no explicit guidance about when not to use it or which sibling tools to prefer instead.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It does reveal that titles are discarded and that the count reflects the current front page, which is useful. However, it does not mention whether network access occurs, whether optional parameters are ignored, rate limits, or any error behavior.

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

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

The description is two short sentences with no filler. The core action is front-loaded, and the 'Titles discarded' clarification adds value without bloat.

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 count tool, the description is nearly sufficient: an agent knows what the tool does and that titles are not returned. However, the presence of nine unrelated optional parameters and the lack of output schema or annotations leave ambiguity about return shape and whether any parameter can affect 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?

Schema description coverage is 100%, so the baseline is 3. Each parameter has its own description, but the tool description adds no parameter-level meaning and does not explain why unrelated parameters like city, feed, or query appear in the schema. Since all parameters are optional, the agent can safely call with no arguments, but the disconnect between the description and schema remains unresolved.

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

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

The description names a specific verb ('Count') and a precise resource ('current Hacker News front-page stories'), and adds a clarifying detail that story titles are discarded. It does not explicitly differentiate from sibling tools like web-fetch or fetch-status, but the narrow resource and count-only intent make the purpose clear.

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

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

The description provides no guidance on when to use this tool versus alternatives, no exclusions, and no prerequisites. An agent can infer a use case from the purpose, but nothing tells it why this tool should be chosen over a general fetch or status-check 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?

With no annotations, the description carries the full burden of explaining behavioral traits. It does not state whether the tool is read-only, what the output format is, whether the parameters are ignored or used, or what 'clock calls' means. The description only names a category of data without disclosing 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 brief, but brevity crosses into under-specification. It is a noun phrase rather than a complete tool description, and it omits essential operational details. It is not a tautology, but it is too sparse to be genuinely useful.

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 and no annotations, so the description must explain the full context. It does not say what the returned data looks like, whether it is a list, how many items, where the names come from, or how the schema parameters relate to the tool. Given the unrelated parameters and sibling tools, the description is not complete enough for an agent to select and invoke the tool 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?

Although the input schema has 100% field-level description coverage, the description adds no meaning connecting any of the nine parameters to IANA timezone names. Several parameters are described as 'discarded' or unrelated, and the description does not clarify whether any parameter affects the result. This leaves an agent uncertain about how to invoke the tool.

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

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

The description identifies the subject matter ('Common IANA timezone names') and hints at a purpose ('for clock calls'), but it lacks a verb or explicit operation such as 'returns' or 'lists.' It does not clearly distinguish iana-zones from the sibling timezone or utc-time tools beyond the name itself.

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 phrase 'for clock calls' weakly implies a connection to time-related tools, but it does not say when this tool should be preferred over timezone or utc-time, nor does it mention any exclusions or alternate routes.

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. It does disclose that the fetch is public (no auth implied) and that only group counts are returned, but it does not mention network/error behavior, timeouts, or how missing/invalid robots.txt files 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?

One short sentence, front-loaded with the action and resource, with no filler. The 'group counts only' qualifier is efficient and useful.

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 network-fetch tool with 9 optional parameters, no annotations, and no output schema, this description is incomplete. It lacks a parameter mapping, output format details, and failure semantics, so an agent cannot reliably invoke it.

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

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

Although schema coverage is 100%, the property descriptions are generic and misaligned with the tool (e.g., 'url' is described as 'normalize or cite', and most fields are said to be discarded). The description never states which of the nine optional parameters should receive the robots.txt URL, leaving the mapping 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 names a specific verb ('Fetch'), a specific resource ('a public robots.txt'), and a precise output scope ('group counts only'). This is clear, but it does not explicitly distinguish itself from siblings like web-fetch or fetch-status, so it misses the top mark.

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 on when to use this tool instead of alternatives such as web-fetch, fetch-status, or normalize-url. The word 'only' tells the agent what to expect from the result but not when to choose this tool over 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 provided, so the description carries the full behavioral disclosure burden. It discloses that the key is discarded, which is useful for privacy, but it does not state what the tool returns, whether the check is local, or any error behavior. This is only partial 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 very short, front-loads the action, and includes a useful privacy note without filler. It is concise, though the brevity leaves critical invocation details unstated.

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 annotations, and no output schema, the description is far too sparse to support correct use. It does not explain which parameter holds the Jira key, what a valid shape is, or what result the agent should expect. An agent cannot reliably invoke this tool correctly from the definition alone.

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

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

Schema coverage is 100%, so each of the nine string parameters has a description, giving a baseline of 3. However, none of the parameters—ref, url, city, feed, host, json, path, zone, query—obviously represents a Jira issue key, and the description does not map the key to any field. An agent cannot determine which parameter to populate for the stated 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: checking the shape of a Jira issue key, and adds a privacy-relevant note that the key is discarded. This makes the core function clear, though it does not explicitly differentiate itself from sibling shape-checkers like github-repo-shape or domain-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?

The only usage cue is the purpose statement itself; an agent can infer the tool is for validating whether something is a Jira issue key. However, there is no explicit guidance about when not to use it, what counts as a valid key shape, or which alternative validation tool to choose among the many 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?

The description discloses one meaningful behavioral trait: the response body is discarded, signaling a status-only operation. However, with no annotations, it does not state whether a real network request occurs, how redirects or errors are handled, or whether there are side effects, so it only partially carries the transparency burden.

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 wasted words. It is concise, though arguably too sparse for a nine-parameter tool; that sparsity is more appropriately 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?

Given nine optional parameters, no annotations, and no output schema, the description does not tell an agent which input to supply or what the returned HTTP status looks like. It needs at least a note that `url` is the relevant parameter and what a successful vs failed status means.

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 a baseline of 3 applies. The description adds only a narrow gloss—'public library docs'—to the `url` parameter, and says nothing about how the other eight optional parameters should be populated or 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 states a specific operation and resource: it returns the HTTP status of a public library docs URL and discards the body. It is clear but does not distinguish from sibling tools like fetch-status, browser-url-ok, or web-fetch, so it stops short of 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 when-to-use or when-not-to-use guidance, and no alternatives are named. The 'Body discarded' line weakly implies a status-only use case, but with many sibling URL tools, the agent is left to infer when to choose this one.

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

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

The phrase 'Values discarded' discloses that values are ignored and the operation has no value-dependent behavior. However, with no annotations to cover safety or side effects, the description still omits return format, error behavior on malformed JSON, and whether the count is recursive.

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 deliver the core operation and a behavioral caveat with no filler. The key information is front-loaded and each 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 simple counting tool, the description is nearly sufficient, but it omits whether the result is an integer count, whether nested keys are counted, and how errors like non-object input are handled. Given the absence of an output schema and annotations, some of that burden falls on the description.

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

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

The schema has 100% parameter descriptions, so the baseline is met, but the tool description itself does not explain which parameter to populate or that the whole input object is the thing being counted. The mix of unrelated parameters such as url, city, and host makes this ambiguity material.

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 clarifies that values are ignored. This distinguishes it from validation/shape tools, though it leaves ambiguous whether the count is top-level only and which input parameter carries the object.

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 siblings like validate-json or domain-shape. There are no conditions, exclusions, or named alternatives, so an agent must infer applicability from the name and brief 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 behavioral disclosure burden. It does usefully disclose that query and fragment are dropped, which is a real behavioral trait. However, it does not mention that other parameters appear to be irrelevant to URL normalization, whether the operation is purely local, or how invalid URLs 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 two sentences, front-loaded with the primary action, and contains no filler. Every word earns its place.

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

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

The tool has nine optional parameters and no output schema, so the description is less complete than it could be. It does not state that only 'url' is needed or that other parameters are ignored, though the schema-level descriptions partially compensate by marking several parameters as discarded. The description is adequate but leaves meaningful 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 coverage is 100%, so the baseline is 3. The description adds little beyond the schema: it mentions dropping query and fragment, which maps to one aspect of the 'url' parameter, but it does not clarify which of the nine parameters should actually be used or how the parameters relate to the output.

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 action: returning origin, host, and path for a URL, with query and fragment dropped. It is specific about the resource and transformation, though it does not explicitly differentiate it from URL-related siblings like domain-shape or browser-url-ok.

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

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

There is no guidance about when to use this tool versus alternatives, no exclusions, and no mention of the conditions under which an agent should choose normalize-url over sibling tools. Usage is only weakly implied by the 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 present, the description carries the full burden of behavioral disclosure. It reveals one trait—'No browser is launched'—but does not explain that several parameters are 'discarded after the shape check,' whether any network request occurs, or what 'can be opened' operationally means. This is insufficient transparency for a tool with multiple input types.

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

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

The description is a single concise sentence that is front-loaded with the primary action and includes a useful qualifier. It contains no waste. However, its brevity borders on under-specification, omitting important context about the schema's breadth.

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

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

The description covers only the URL aspect while the schema exposes seven parameters with varying purposes. There is no output schema and no annotations. An agent would be uncertain about what inputs to provide and what side effects occur. The tool appears more complex than the description acknowledges, leaving significant gaps.

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

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

All parameters have descriptive text in the input schema, so the baseline is 3. The tool description adds no additional parameter-level meaning beyond the schema. While some schema descriptions (e.g., 'City name for a public weather hint') seem inconsistent with the stated URL-check purpose, that inconsistency is not addressed by 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 a specific action and resource: 'Check whether a URL can be opened.' It also includes a distinguishing clause 'No browser is launched.' However, the input schema contains many parameters unrelated to a simple URL check (city, feed, json, path, ref), causing ambiguity about the tool's actual scope and purpose.

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

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

The description gives no explicit guidance on when to use this tool versus alternatives like browser-url-ok or web-fetch. The clause 'No browser is launched' implies a lightweight alternative, but the description does not state selection criteria, exclusions, or context where this tool should be preferred.

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

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

With no annotations, the description carries the transparency burden; 'Query discarded' is a useful disclosure that the input is not retained. But it does not state the return value, whether any network or side effects occur, or what happens if the query is empty.

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 efficient and front-loaded, but the definition is under-specified for a 9-parameter tool with no output schema. It sacrifices necessary invocation guidance for brevity.

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 mention of the return format or which parameter to pass among the nine optional fields. The description is not complete enough for an agent to confidently invoke this tool correctly, especially given the unrelated parameter descriptions.

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 little beyond referring to a 'search query.' The schema's `query` description ('Search text; discarded after the length check') actually provides the key semantics, though the description does not clarify why the other eight parameters are accepted.

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 begins with a specific verb and object: 'Count characters in a search query,' which states the core function clearly. However, it does not differentiate this from sibling count/shape tools or explain why the schema exposes nine unrelated optional parameters, so it stops short of full clarity.

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

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

No when-to-use guidance, conditions, or alternatives are provided. The description does not tell the agent that only the `query` parameter is relevant or that the other accepted parameters (url, json, path, etc.) should be ignored for 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 provided, so the description carries the full burden of disclosing behavior. It only describes a static catalog and gives no indication of side effects, network access, authentication needs, rate limits, or return behavior. This is insufficient for a tool with a mutable-looking input 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 very short and contains no wasted words, but it is under-specified rather than appropriately concise. It reads as a label rather than a functional description, which fails the purpose of a 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 no output schema, no annotations, nine optional parameters, and many siblings, the description leaves almost everything to inference. It does not explain what inputs are for, what the tool returns, or how the parameters relate to the catalog, making it inadequate for an agent to select and invoke correctly.

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

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

Schema description coverage is 100%, so the baseline is 3. The description adds no parameter-level meaning, but the schema itself documents each parameter. However, the parameter meanings (e.g., Git ref, city weather, JSON validation, timezone) do not obviously connect to the stated purpose of an HTTP status code catalog.

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

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

The description is a noun phrase, 'Short catalog of common HTTP status codes,' that essentially restates the tool name without specifying an action. It adds the domain 'HTTP status codes' but does not say whether the tool looks up, lists, or checks status codes, and it does not distinguish 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?

There is no guidance on when to use this tool versus alternatives. With many sibling tools such as fetch-status, browser-url-ok, and normalize-url, an agent is left guessing whether to call this for a lookup, a fetch, or something else.

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, but it only says 'Prompt discarded.' It does not say that all nine optional parameters are ignored, whether the output is static, or what the template contains; some schema descriptions even imply input is used.

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 the main action front-loaded and no filler. Slightly ambiguous phrasing ('Prompt discarded') prevents a 5, but it is appropriately concise.

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

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

For a tool with no annotations, no output schema, nine optional parameters, and 28 siblings, this description is too thin: it omits when to use it, what the three-step template looks like, whether arguments are accepted or ignored, and the return format.

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

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

Schema description coverage is 100%, so each parameter is individually documented and the baseline is 3. The tool description adds no parameter-level meaning and fails to clarify whether any parameter affects the returned template, leaving the nine optional fields disconnected from the tool's 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 concrete deliverable ('three-step thinking template') with a clear verb ('Return'), so an agent knows what the tool produces. It does not differentiate from any sibling tools or explain what the template is for, so it misses the top 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?

No guidance is given on when to use this tool versus the many sibling utilities, and no alternatives or exclusions are mentioned. 'Prompt discarded' hints that the tool is independent of input, but it does not state a use case.

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

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

No annotations are provided, so the description must fully disclose behavior. It states an output but does not explain how the tool actually behaves with the given parameters, nor does it disclose that none of the parameters appear timezone-related. An agent cannot infer what to expect or what side effects might occur.

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 padding and the core idea is front-loaded. It loses points only because its brevity omits necessary invocation context.

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

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

With 9 parameters, no output schema, and no annotations, a one-sentence description is inadequate. The agent lacks essential information: which parameter carries the timezone, what the return format is, and how this tool is meant to be combined with sibling tools. The mismatch between purpose and schema further reduces completeness.

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

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

Schema coverage is high, but the description adds no meaning that maps the 'named IANA timezone' to any actual parameter. The visible parameters (ref, url, city, feed, host, json, path) are irrelevant to timezone lookup, so an agent cannot determine which parameter to set. The description fails to 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 identifies the result ('current time') and the resource ('named IANA timezone'), and it is differentiated from sibling tools like 'iana-zones' (list zones) and 'utc-time' (UTC time). However, it uses a noun phrase rather than an explicit verb and does not address the evident mismatch with the input 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?

There is no guidance on when to use this tool versus alternatives, such as 'utc-time' for UTC or 'iana-zones' for zone names. The description does not mention any conditions, exclusions, or preferred use cases.

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 states the output. It fails to disclose that the parameters appear to be discarded or ignored, that the operation has no side effects, or what format the timestamp is returned in.

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 fact, making it economical. However, the single noun phrase is closer to under-specification than to an appropriately sized description, since it omits all behavioral and invocation information.

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

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

For a tool with no annotations, no output schema, and seven optional parameters that are opaque relative to the stated purpose, one clause leaves too much unknown. An agent cannot tell whether to pass parameters, what timestamp format to expect, or how this differs from sibling timezone tools.

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

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

The input schema already provides substantive descriptions for every parameter, such as 'JSON text to validate; discarded after the check', so schema coverage is high and the baseline applies. The description adds nothing about the parameters and does not reconcile them with the UTC-time purpose, but it does not need to restate 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 identifies the tool's output as the current UTC timestamp, which is a clear and specific resource and aligns with the tool name. It lacks a verb and does not distinguish itself from sibling tools like timezone or iana-zones, so it does not 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?

The description gives no guidance on when to use this tool versus alternatives such as timezone or iana-zones. It also does not explain whether the seven listed input parameters should be supplied, leaving invocation context entirely to inference.

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

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

With no annotations, the description carries the disclosure burden. It does add a useful behavioral trait ('The body is discarded'), indicating no retention. However, it does not describe the return value, error behavior, or whether the check is purely syntactic, 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?

Two short sentences, front-loaded with the action and followed by the key side-effect note. 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?

This is a 9-parameter, 0-required tool with no output schema and no annotations. The description does not clarify the relationship between the many 'discarded' params and the body being validated, nor state what the caller should expect back. An agent can invoke it only by assuming `json` is the relevant parameter.

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 covers 100% of parameters with descriptions, so the baseline is 3. The description itself adds no parameter-level meaning; it does not even identify which parameter is the 'body' (presumably `json`). It neither helps nor hurts 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 uses a specific verb ('Check whether') and resource ('a body is valid JSON'), making the core function unmistakable. It also states the body is discarded, which separates this from tools that consume or store the body. The name alone is reinforced, not merely restated.

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 obvious use case—any time a body's JSON validity needs confirmation—but it gives no when-to-use guidance versus alternatives and names no sibling tools. For a simple validator, this is adequate but not explicit.

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

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

There are no annotations, so the description carries the burden of behavioral disclosure. It usefully reveals an external API dependency via Open-Meteo and the time-sensitive nature of 'current' temperature, but it does not explicitly state that the call is read-only, side-effect-free, or how failures or rate limits behave.

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

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

The description is a single concise sentence that front-loads the core behavior and data source. It contains no wasted words and is appropriately minimal for a simple lookup 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 essential action and source are present, but there is no output schema and no annotations, and the description does not state return format, units, or how the eight non-city parameters relate to the tool's purpose. The schema descriptions mitigate some ambiguity, but the definition is not fully self-sufficient for a 9-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?

Schema description coverage is 100%, and each parameter already has a description including note about values being discarded, so the baseline is 3. The tool description itself adds no parameter-level meaning beyond identifying 'city' as the relevant input, and the presence of eight other unrelated parameters still creates ambiguity about which arguments matter.

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

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

The description clearly identifies the tool as returning current temperature for a city and names Open-Meteo as the source. This is specific enough to distinguish it from the generic validation siblings, though it does not explicitly contrast with related tools like geo-hint. The many unrelated optional schema parameters slightly undercut the clarity.

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

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

The description provides a clear usage context: use this tool when a current city temperature is needed. It does not mention alternatives, exclusions, or that only the city parameter should be supplied while the other parameters appear to be ignored, so it stops short of full routing guidance.

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

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

With no annotations available, the description carries the behavioral disclosure burden. It does meaningfully disclose that the body is discarded and that the URL must be public, which is useful. However, it does not mention redirects, error behavior, authentication requirements, rate limits, or whether only HTTP status and content-type are ever 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 key behavior and its most important limitation are front-loaded, making the description easy to parse and act on.

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

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

The description is too thin for the surrounding context: a large unfocused input schema, no output schema, no annotations, and several sibling tools that appear to overlap in purpose. It does not explain which parameters matter, what the response looks like, or how this tool relates to fetch-status and other URL-focused tools.

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

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

The input schema contains dozens of generic properties, and the description does not map 'public URL' to a specific parameter such as 'url' or 'host'. The schema descriptions are broad and even misaligned—'url' says 'normalize or cite' rather than fetch—so the agent receives little help selecting the correct argument. The description adds almost no parameter-level clarity.

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

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

The description is specific: it says the tool returns HTTP status and content type for a public URL, and adds that the body is discarded. This clearly identifies the verb and resource. However, it does not explicitly distinguish itself from similarly named siblings like fetch-status, so it misses the top level of differentiation.

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

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

There is no guidance about when to use web-fetch instead of fetch-status, browser-url-ok, playwright-url-ok, or normalize-url. The description implies a use case, but does not state exclusions, prerequisites, or alternatives. The agent must infer the right context from the name and brief behavior summary.

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

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

With no annotations provided, the description carries the full burden. It only discloses that the title is discarded after the call, but does not clarify whether this is a network operation, what it returns, or how it handles redirects or case variants. Some behavior is disclosed, but far too little.

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, well-structured sentence that front-loads the primary purpose and adds only one relevant behavioral note. There is no wasted wording.

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 actionable: it lacks an output schema, annotations, a parameter mapping, or any indication of the expected return value. The mismatch between the described title-checking behavior and the schema properties leaves an agent without enough information to select and invoke this 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 description repeatedly refers to a 'title', but the input schema has no 'title' property—only ref, url, city, feed, host, json, and path. The description fails to map the core concept to any actual schema parameter, so an agent cannot determine what value to pass. The schema descriptions for the existing parameters are irrelevant to the stated 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 clearly states a specific verb ('Check'), resource ('Wikipedia title'), and predicate ('exists'), which distinguishes this tool from sibling URL, path, host, and JSON validation tools. The added note that the title is discarded reinforces its stateless purpose.

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

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

The intended use is implied: call this when an agent needs to verify whether a Wikipedia title exists. However, it does not explicitly state when not to use it or mention alternative tools such as url-ok or browser-url-ok.

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