Slug character check
Return host, scheme, and HTTP status for a URL. Page content is not stored.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. 'Page content is not stored' is a genuine behavioral disclosure, but it is the only one. The description omits whether the URL is fetched, what side effects occur, auth requirements, rate limits, or failure behavior — significant gaps for an unannotated tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with zero waste. The primary operation is front-loaded, followed by a single privacy-relevant qualifier. 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 4 parameters, none required, no output schema, and no annotations. The description explains only the URL-related behavior and never addresses the json and zone parameters, output format, possible return values, or error conditions. An agent would not know how to call this tool correctly for non-URL inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds nothing beyond the schema's parameter documentation. Notably, the description only mentions URL while the schema includes unrelated-looking parameters (json, zone); the description does not bridge how those fit 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 states a specific verb ('Return') and resource ('host, scheme, and HTTP status for a URL'), making the core function clear. It does not explicitly differentiate from sibling tools, which matters given the confusing sibling list, but the primary 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?
No guidance is given on when to use this tool versus alternatives, no usage context, and no exclusions. The single sentence does not address selection criteria or mention any sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Show how this request is classified. No identifiers are retained.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
"No identifiers are retained" contributes a privacy guarantee, but with no annotations the description carries the full burden of behavioral disclosure. It doesn't state whether the operation is read-only, what side effects (if any) exist, or what happens to the submitted data beyond retention.
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 wasted words. The purpose is front-loaded and the privacy note is a meaningful addition—both sentences earn their place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no usage guidance, an agent cannot infer what the classification result looks like or how the four heterogeneous optional parameters relate to one another. The description is too sparse for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents all four parameters (url, host, json, zone). The description adds no parameter-specific meaning, but the schema does the heavy lifting, earning the baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
"Show how this request is classified" names a verb and resource but the noun 'classified' is ambiguous—no indication of what categories, taxonomy, or criteria are used. It doesn't differentiate the tool from siblings like validate-json or normalize-url, so the exact purpose remains unclear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives, nor does it explain which of the four parameters should be supplied. No context, exclusions, or conditions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Split a hostname into labels without WHOIS or ownership data.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses only what the tool does not return (WHOIS/ownership data), but does not describe what the output looks like, how it processes the various input types, whether it performs any validation, or what side effects (if any) occur. Given the heterogeneous parameter list, this is a significant transparency 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 sentence with zero filler. Every word contributes a meaningful constraint: the action, the object, and the excluded data category. It is highly concise and 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?
For a tool with four optional parameters and no output schema, this description is incomplete. It does not tell an agent which parameter to provide, whether the parameters are mutually exclusive or combinable, or what the return value looks like. The schema covers parameter descriptions, but the overall invocation contract is underspecified.
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 any parameter-level meaning beyond the schema; it only mentions 'hostname' without explicitly mapping to the 'host' parameter or explaining how 'url', 'json', and 'zone' are handled. The schema itself already provides clear descriptions for each parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Split'), resource ('hostname'), and explicitly scopes the tool away from WHOIS/ownership data. This clearly distinguishes it from any sibling tools that would provide ownership information. However, the input schema lists four heterogeneous parameters (url, host, json, zone), and the description does not clarify how these relate to the stated purpose, creating some ambiguity about the tool's full scope.
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 explicit guidance on when to use this tool versus alternatives. The phrase 'without WHOIS or ownership data' implies a contrast, but no alternative tool is named and no condition is given. It also fails to explain whether to pass 'url' or 'host' or how 'json' and 'zone' fit into the intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Common IANA timezone names for clock calls.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
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 no side effects, inputs, output, or failure modes, leaving the agent with no behavioral information beyond a vague label.
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, but this is under-specification rather than effective concision. It provides no structured information or actionable guidance, so the brevity does not earn 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 and no annotations, the description is the only context, and it fails to explain what the tool returns, which parameters are relevant, or how it relates to sibling tools. The four optional and seemingly unrelated parameters are left completely 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 schema already documents all four parameters, setting a baseline of 3. The description adds no meaning about how zone, url, host, or json relate to the tool's purpose, but the schema covers the parameter names.
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 ('Common IANA timezone names for clock calls') with no verb, so it never states what operation the tool performs. 'Common' and 'for clock calls' add small scoping hints, but the function remains ambiguous and close to a restatement of the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus siblings like timezone or validate-json. The only hint is 'for clock calls,' which is too weak to route an agent reliably.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a public robots.txt and return group counts only.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
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 says 'return group counts only', which partially clarifies output, but it does not disclose network behavior, error conditions, rate limits, or whether the fetched content is cached. For a fetch operation, that leaves notable behavioral gaps; an agent might reasonably expect more detail about what 'inspect' implies (e.g., does it block on network? can it fail?).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core operation and output scope efficiently. There is no wasted wording, though it could have added a brief parenthetical about which parameter to use without becoming bloated.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, no output schema, and four optional-looking parameters, the description leaves an agent guessing about the actual calling pattern. The tool fetches a robots.txt but also offers parameters like json, zone, and url that are described as unrelated actions ('normalize or cite', 'validate', 'IANA timezone name'). That mismatch is confusing and makes the description incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter has some textual description in the schema. However, the tool description says 'return group counts only', which does not explain how any of the four parameters relate to the operation. The schema descriptions themselves are minimal (e.g., 'HTTPS URL to normalize or cite', 'Public hostname'), and the description does not compensate by clarifying which parameter is actually required or how they interact. Baseline 3 applies because coverage is high, but no added semantics are given 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?
States a specific verb ('Fetch') and resource ('public robots.txt') and scopes the behavior to 'group counts only'. The name 'inspect-robots' matches the description well. It does not explicitly distinguish from siblings (citation, which suggests related tools), but the resource and output scope are clear on their 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?
No guidance is given about when to use this tool versus alternatives. The sibling list includes citation, but the description does not say when to prefer this over citation or any other tool. An agent must infer usage context from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return origin, host, and path for a URL. Query and fragment are dropped.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully carries the behavioral burden and explicitly discloses that query and fragment are dropped—a non-obvious behavioral trait. It also defines the output components (origin, host, path). It does not mention edge cases such as invalid URLs or handling of missing inputs, but the core transformation 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?
The entire description is a single focused sentence that front-loads the primary function and immediately discloses the key transformation. Every word earns its place; there is no repetition or filler.
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 appropriately explains the return values (origin, host, path) and the components that are dropped. It does not cover error behavior, the fact that all parameters are optional, or the roles of the non-URL parameters, but for a simple transformation tool this is a minor 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 descriptions cover 100% of parameters, so the baseline is 3. The description adds no parameter-level meaning and does not clarify why 'host', 'json', and 'zone' are inputs to a URL normalization tool. The schema descriptions themselves are present but seem mismatched with the tool purpose, and the description does not resolve this confusion.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific action ('Return origin, host, and path') and resource ('a URL'), clearly distinguishing it from URL validation or other operations. It also specifies that query and fragment are dropped, which further clarifies the behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives, and no exclusions or related tools are mentioned. The description only states what the tool does, leaving the agent to infer appropriate usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Slug character check
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations at all, the description carries the full burden of behavioral disclosure, but it only names a 'check'. It says nothing about side effects, accepted slug rules, error behavior, output format, or why parameters such as zone and json are involved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The text is only three words, but this is under-specification rather than effective conciseness. It lacks a complete, front-loaded explanation that would help an agent act on it.
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 four optional heterogeneous parameters, no output schema, no annotations, and a vague sibling context, the description is far too weak. An agent cannot determine what input to provide, what the tool returns, or how it relates to URL normalization, JSON validation, or timezone handling.
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 all 4 parameters with descriptions, giving 100% schema coverage, so the baseline of 3 applies. The description adds no parameter-level meaning, but the schema itself documents each parameter adequately for basic understanding.
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?
Description 'Slug character check' is a bare noun phrase that essentially restates the tool name without stating an action, object, or result. It fails to explain what is checked or returned and does not distinguish the tool from siblings like validate-json 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?
No guidance is given about when to use slug-ok versus any sibling tool. The heterogeneous parameters (url, host, json, zone) only deepen the ambiguity, and the description provides no conditions, exclusions, or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Short catalog of common HTTP status codes.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of disclosing behavior. It only describes the catalog as 'short' and does not state whether the tool is read-only, whether it uses any of the inputs, what side effects exist, or what the output looks like. This is far too little behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, but this is under-specification rather than effective conciseness. One short noun phrase is not enough for a tool with four optional parameters and no output schema, and the sentence does not earn its place because it fails to communicate the tool's actual 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?
Given the tool has no output schema, no annotations, and four optional parameters that appear to belong to other tools (normalize-url, validate-json, timezone, citation), the description is severely incomplete. An agent cannot determine what inputs to pass, what the tool returns, or why this tool exists alongside the siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and each parameter has its own text, so the baseline is 3. However, the description adds no meaning to the parameters and fails to connect url, host, json, or zone to HTTP status codes, leaving the parameter semantics confusing despite the 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 'Short catalog of common HTTP status codes' is a noun phrase that essentially restates the tool name rather than stating an operation or behavior. It does not explain what the tool does with an input or what a caller receives, and it is disconnected from the four unrelated 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 this tool versus any sibling. The sibling names (normalize-url, validate-json, timezone, citation, etc.) suggest related web utilities, but the description never tells an agent when status-catalog is the right choice or when it is not.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Current time in a named IANA timezone.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
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 conveys that the tool returns the current time, but it does not disclose output format, error behavior, or the fact that url/host/json parameters appear irrelevant to the tool's purpose, which can mislead an agent.
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 wasted words. It is concise, though arguably too terse for a tool with a mismatched four-parameter schema.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four optional parameters, no output schema, and no annotations, so the description must compensate. It does not specify which parameter to pass, what output shape to expect, or how the current time is formatted, leaving an agent with significant 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?
Although schema coverage is 100%, most parameters (url, host, json) have descriptions that point to unrelated behaviors like normalization, citation, and validation. The description mentions 'named IANA timezone' and the zone parameter is described as 'IANA timezone name', but the description fails to clarify that zone is the only meaningful parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb+resource: returning the current time for a named IANA timezone. It is clear on its own, though it does not distinguish this tool from 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 guidance on when to use this tool or how it relates to sibling tools. The description also fails to indicate that the 'zone' parameter is the relevant one, especially given that the schema exposes unrelated parameters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Current UTC timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears the full burden of behavioral disclosure, but it reveals nothing beyond the tool name: no timestamp format (ISO 8601 vs epoch), precision, or latency characteristics. The tool appears to be a harmless read, but the description adds no behavioral context at all.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded at five words with zero filler. It earns its place but is so terse that it sacrifices useful substance; still, for conciseness alone it is well-formed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no annotations and no output schema, and its four parameters are left unexplained in relation to its purpose. An agent cannot tell why url/host/json are accepted, whether they affect the result, or what the return value looks like. The description is incomplete for reliably 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?
Schema description coverage is 100%, so the baseline is 3 even with no parameter details in the description. However, the four parameters (url, host, json, zone) seem largely unrelated to fetching a UTC timestamp, and the description provides zero guidance on how they relate, leaving an agent to guess whether passing 'zone' alters 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, 'Current UTC timestamp,' names a specific behavior with a subject and resource: it returns the current UTC time. It clearly identifies the UTC scope, which partially distinguishes it from the sibling 'timezone' tool, though it does not explicitly differentiate 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?
No guidance is given on when to use this tool versus alternatives such as 'timezone'. There is no mention of use cases, exclusions, or conditions that would route an agent to this tool over its siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check whether a body is valid JSON. The body is discarded.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | HTTPS URL to normalize or cite | |
| host | No | Public hostname | |
| json | No | JSON text to validate; discarded after the check | |
| zone | No | IANA timezone name |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It does disclose the notable behavior that the body is discarded, implying a non-persistent operation. However, it does not mention what happens on invalid JSON, response format, or any side effects beyond discarding, so the disclosure is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with no waste. The core action is front-loaded, and every sentence earns its place by adding either the operation or the discard 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?
Given 4 parameters, all optional, no output schema, and no annotations, the description is too sparse. It does not indicate which parameter is the JSON body, does not describe the return value, and leaves the role of url/host/zone unexplained. An agent would need to infer too much 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?
Schema description coverage is 100%, so the baseline is 3 even without additional parameter info in the description. The description's reference to 'body' maps loosely to the 'json' parameter, but it does not clarify which of the four parameters is relevant or how the unrelated url/host/zone fields should be treated. No meaningful new semantics are added beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: checking whether a body is valid JSON. The verb 'check' and the resource 'valid JSON' make the purpose specific, and the name validate-json reinforces it. However, 'body' is ambiguous and the description does not explicitly differentiate from siblings, though siblings appear unrelated.
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, nor any conditions or exclusions. It simply states what the tool does without situating it among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
citationcompatibilitydomain-shapeiana-zonesinspect-robotsnormalize-urlslug-okstatus-catalogtimezoneutc-timevalidate-jsonClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such as io.github.acme/server also needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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Converts text titles into URL-safe slugs and flags duplicates. x402 payment required (testnet USDC).
Add one secure layer between your agents and this server.
Several tools have overlapping concerns: citation, normalize-url, and domain-shape all analyze URLs/hostnames, while timezone, utc-time, and iana-zones all relate to time. The purpose of compatibility is vague and could be confused with the URL inspection tools. Only a few tools like slug-ok and validate-json are clearly distinct.
All names use lowercase hyphenation, which is consistent, but the pattern is mixed: some are verb phrases (normalize-url, inspect-robots, validate-json), while others are bare nouns (citation, compatibility, timezone). There is no unified verb_noun convention, though the names remain readable.
Eleven tools is not an unreasonable count by itself, but the tool set is unfocused for a server named 'Slug character check.' Most tools address unrelated concerns such as time, URLs, HTTP status, and JSON, making the collection feel padded rather than purpose-built.
The server lacks a coherent domain: slug checking has only one thin tool, URL utilities have no encoding/decoding or query-param handling, and time utilities lack conversions or formatting options. For any single stated purpose, the surface has significant gaps and no end-to-end workflow.