Bytes to KiB
Most tools have distinct outputs, but the URL/web-metadata cluster (citation, compatibility, domain-shape, normalize-url, status-catalog) overlaps conceptually and could confuse an agent choosing between request classification and URL parsing. The conversion, time, and JSON tools stand apart more clearly.
All tool names use lowercase kebab-case, which is readable, but they mix noun-only names (citation, timezone), noun-noun compounds (domain-shape, iana-zones), and verb-noun names (inspect-robots, normalize-url, validate-json). There is no consistent verb_noun or noun_verb pattern across the set.
Eleven tools is not objectively large, but for a server named 'Bytes to KiB' most of them are unrelated to the stated purpose. The count only makes sense if the server is reinterpreted as a general privacy-safe utility set, which the name does not convey.
The URL/time/JSON utilities cover basic cases, but the byte conversion is one-directional and lacks a KiB-to-Bytes counterpart. The web tools also omit natural companions like header inspection or DNS info, leaving the surface feeling like disconnected fragments rather than a coherent domain.
Bytes to KiB
| 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, the description carries the full burden of behavioral disclosure, but it only states a conversion label. It does not say whether the operation is read-only, what input is converted, whether any discarding or mutation happens, or what the output looks like.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The text is short but under-specified rather than appropriately concise. It lacks a full sentence, a functional verb, and any bridging context to the schema fields, so brevity here is a defect.
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 parameters, no annotations, no output schema, and an ambiguous description that mismatches its schema. There is not enough information for an agent to understand what this tool does, let alone invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although every parameter has a schema description (100% coverage), those descriptions are unrelated to the stated 'Bytes to KiB' purpose. The description adds no meaning about how url, host, json, or zone relate to a byte conversion, leaving the agent unable to pick the correct input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Bytes to KiB' is little more than a restatement of the tool name, with no verb, resource, or operational detail. It also misleads by implying a byte conversion while the input schema contains only url, host, json, and zone, with no bytes parameter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool or how it differs from the many siblings such as normalize-url, validate-json, or timezone. The description offers no context, no alternatives, and no exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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, the description carries the behavioral transparency burden. It does disclose a meaningful non-obvious behavior: page content is not stored. However, it does not explain redirects, failures, rate limits, or how the json and zone inputs behave, 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 fluff; the core operation is front-loaded and the second sentence adds a valuable privacy guarantee. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is incomplete relative to the tool's schema and sibling context. It explains only the URL-related behavior while the schema also accepts host, json, and zone, and no output schema or annotations fill in missing return/error semantics. An agent would not know how to correctly invoke the tool for the non-URL parameters or what happens if none are provided.
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 meaningful description, including that JSON text is discarded after the check. The description adds no extra parameter-level detail beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific operation: return host, scheme, and HTTP status for a URL, which distinguishes it from siblings like normalize-url and status-catalog. However, it ignores the substantial json, zone, and host parameters in the schema, so the stated purpose is only partially complete.
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 related siblings such as normalize-url, validate-json, or status-catalog. The privacy note about page content is not stored is useful but does not help an agent choose this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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 annotations are present, so the description carries the transparency burden. It reveals one meaningful behavioral trait: 'No identifiers are retained,' suggesting privacy-conscious handling. However, it does not state whether the tool is read-only, whether it makes network requests for URLs, or what side effects might occur, leaving transparency 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 appropriately sized at two short sentences, front-loading the main action and following with a relevant privacy guarantee. There is no filler, though the brevity contributes to some ambiguity in meaning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description must explain what the tool returns and how to interpret the classification, but it does not. It also fails to explain how the four heterogeneous optional parameters relate to the classification request or when this tool should be selected over its 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%, with each of the four parameters (url, host, json, zone) documented in the input schema. The description itself adds no parameter-level meaning, so it stays at the baseline of 3 rather than being penalized for missing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a verb ('Show') and names a resource ('how this request is classified'), but 'this request' and 'classified' are left undefined. The tool name 'compatibility' does not clarify what is being classified or what compatibility means, and no distinction from siblings like validate-json or citation is provided.
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 compatibility versus any of the ten sibling tools, and no conditions or prerequisites are mentioned. The description only implies a generic classification use case, which is not enough to guide tool selection.
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, the description carries the full burden. It openly describes the transformation and the absence of WHOIS/ownership data, which suggests a read-only utility. However, it does not explain how the tool handles the multiple accepted input parameters or what happens on invalid input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no filler. The key action is front-loaded, and the qualifying phrase adds useful scoping without bloating the description.
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 the core purpose and suggests the output (labels), but with no annotations and no output schema, it leaves the relationship among the four optional parameters unclear. An agent can likely infer how to call it, but the missing parameter-selection guidance is a noticeable 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%, so the baseline is 3. The description adds no extra parameter-level meaning, and the schema already documents each parameter. It also does not clarify why parameters like json and zone are relevant to hostname splitting.
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 ('split') and resource ('hostname into labels'), and adds an explicit exclusion ('without WHOIS or ownership data') that sharpens the boundary. This clearly differentiates it from sibling tools like normalize-url, validate-json, and timezone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no explicit guidance about when to use this tool versus the sibling alternatives, nor any mention of what to use if WHOIS or ownership data is needed. The description implies a use case but does not state it as guidance.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure, but it is a noun phrase about content rather than behavior. It never states whether the tool returns a list, validates names, makes network calls, or is purely a read-only reference, so significant behavioral traits are undisclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and contains no filler, making it concise. But it is a sentence fragment that omits a verb and essential behavioral context, so the concision comes at the expense of clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, no annotations, and no explanation of return values or invocation shape. With four optional but seemingly unrelated parameters, an agent cannot reliably tell whether to call the tool with no arguments, a zone, or one of the other fields, so the definition is incomplete for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3; each parameter is individually described in the schema. However, the tool description adds no meaning for the url, host, and json parameters, and it does not explain why a timezone-name tool accepts parameters for URL normalization, hostnames, and JSON validation, which creates ambiguity about how to invoke it.
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 the resource ('common IANA timezone names') and a context ('for clock calls'), but it lacks a verb such as 'list' or 'return', so the actual action of the tool is left to inference. It is not a pure tautology because it specifies timezone names rather than generic zones, but it does not crisply state what an agent can expect the tool to do.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for clock calls' gives a weak usage context, implying the tool is relevant when timezone names are needed for clock-related operations. However, there is no explicit when-to-use or when-not-to-use guidance, and no alternative sibling tool is mentioned, leaving the agent to infer when iana-zones should be preferred over timezone or utc-time.
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?
With no annotations, the description carries the burden of behavioral disclosure. It does communicate that only group counts are returned, not the full robots.txt, which is useful. However, it does not mention behavior on missing/blocked robots.txt, error responses, or the meaning of 'groups', leaving important behavior implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short, front-loaded sentence with no filler. It conveys the core action and the limited return value efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four optional parameters, no output schema, no annotations, and a disconnected input schema, the description is too thin. It does not clarify the expected input for fetching a robots.txt, leaving an agent with ambiguous parameter choices and incomplete expectations about behavior.
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 descriptions cover 100% of parameters, they are generic and poorly tied to this tool: 'url' is described as 'HTTPS URL to normalize or cite', and 'json' and 'zone' are unrelated to fetching robots.txt. The description does not explain which parameter to use or how the parameters relate to the robots.txt fetch.
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 explicit action ('Fetch'), a concrete resource ('a public robots.txt'), and a precise output shape ('return group counts only'). It clearly distinguishes this tool from its siblings by naming the robots.txt inspection focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like domain-shape, normalize-url, or validate-json. The description gives no context, prerequisites, or exclusions to help an agent decide between tools.
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, the description must carry behavioral transparency. It usefully discloses that query and fragment are dropped, which is a meaningful transformation. However, it does not explain behavior for invalid URLs, non-HTTPS inputs, or whether the extra schema fields like host, json, and zone are ignored or validated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and front-loaded with the core purpose. The second sentence adds an important behavior (dropping query and fragment) without waste. However, the conciseness leaves the extra parameters unexplained.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and a schema containing four loosely related parameters, the description is not complete enough. It does not specify the return shape, how the non-URL parameters are handled, or what constraints apply, leaving significant gaps for an agent trying to call the tool reliably.
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%, but the description only addresses URL normalization while the schema exposes four unrelated parameters: url, host, json, and zone. The description does not clarify how host, json, and zone relate to the tool, and their schema descriptions ('Public hostname', 'JSON text to validate', 'IANA timezone name') seem disconnected from normalize-url. This creates ambiguity for the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb and resource: it normalizes a URL and returns origin, host, and path while dropping query and fragment. It is distinguishable from sibling tools like validate-json or timezone, though it does not explicitly contrast itself with a URL-related sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance about when to use this tool versus alternatives. It does not mention any conditions, exclusions, or related tools such as citation or domain-shape, leaving the agent to infer usage solely from the tool name.
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?
With no annotations, the description carries the full behavioral disclosure burden, but it only says the catalog is 'short'. It does not disclose whether the parameters are accepted, ignored, or required for filtering, nor what the output looks like or whether any input is discarded.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The text is extremely short, but this is under-specification rather than purposeful conciseness. It does not front-load any actionable guidance; the single sentence merely restates the tool's name in a noun phrase.
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 acceptably documented but unrelated optional parameters and no output schema, the description gives almost nothing an agent needs to select or call the tool correctly. It does not explain parameters, return value, read-only nature, or why url/json/zone/host appear in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, which normally earns a baseline of 3, but the parameter descriptions are unrelated to a catalog of HTTP status codes and no explanation connects them to the tool's purpose. The tool description adds no parameter-level meaning and leaves the mismatch unexplained.
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 phrase 'Short catalog of common HTTP status codes' identifies the resource and domain clearly, but it lacks an explicit action verb or indication of what the tool actually performs (returns a list, looks up a code, validates?). It also does not distinguish it from the sibling tools, though none obviously overlap.
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 optional parameters (url, host, json, zone) are not tied to the catalog purpose, so an agent cannot infer the intended invocation context or any exclusions.
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 implies a read-only operation by saying 'current time,' but it does not disclose the output format, whether the zone is validated, or that several input schema properties appear irrelevant to the stated behavior. The mismatch between the description and the schema's extra parameters creates ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one clean, front-loaded sentence with no filler or repetition. It communicates the core purpose immediately and earns every word.
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 parameters, zero required, no output schema, no annotations, and a sibling set that includes utc-time and iana-zones. The description does not explain which parameter to use, what the response looks like, or how this tool differs from siblings. The schema's unrelated parameters further increase the need for guidance that the description does not provide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents each parameter, including 'IANA timezone name' for zone. The description adds minimal semantic value by tying the tool's purpose to the zone parameter, but it does not clarify why url, host, and json are present or how they relate to the described behavior. The baseline of 3 is appropriate given the 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 a specific, meaningful behavior: returning the current time for a named IANA timezone. It clearly identifies the verb and resource, and while it does not explicitly name sibling tools, the phrase 'named IANA timezone' differentiates it from generic UTC time or zone-listing tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to prefer this tool over utc-time or iana-zones, nor does it explain that the 'zone' parameter should be supplied. With no required parameters and an input schema containing unrelated fields like url, host, and json, the agent is left without direction on how to invoke this tool correctly.
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, the description carries the full burden of behavioral disclosure, but it only states the output. It does not explain whether the four input parameters are ignored, optional, or required, nor does it specify the return format (e.g., ISO-8601 vs Unix epoch). The unrelated parameter names further obscure actual behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief and front-loaded, which is superficially concise. However, it is under-specified for a tool with four optional parameters; a single clause is not enough to convey the role of those parameters or any output details. This is under-specification rather than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has four optional parameters, no output schema, and no annotations, yet the description is only a bare output claim. It fails to state what arguments a caller should pass, whether the parameters affect the result, or what the response contains. An agent cannot reliably invoke this tool based on the provided definition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3, but the parameter descriptions (url, host, json, zone) appear to belong to other tools and do not fit a UTC timestamp utility. The tool description adds no parameter clarification and does not warn that these parameters may be irrelevant, leaving agents with misleading semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the current UTC timestamp, a distinct resource with a specific verb. It avoids tautology and is distinguishable from siblings like timezone or iana-zones by name. However, the presence of unrelated parameters (url, host, json, zone) muddies the tool's scope and prevents a perfect score.
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, iana-zones, or normalize-url. The intended use is only implied by the name and one-line description; no exclusions, prerequisites, or alternative routing are provided.
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 behavioral transparency burden. It does disclose that the body is discarded, which is useful, but it does not say what the tool returns, whether it makes network calls, or how the unrelated parameters are handled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences, front-loaded with the action and then the key side effect. 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 too thin for the full context. There is no output schema, so the return value is unspecified. Additionally, the input schema includes url, host, and zone parameters that are not mentioned in the description, leaving ambiguity about whether they are relevant or ignored.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds only the synonym 'body' for the JSON text and reinforces the discard behavior, providing minimal additional semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check whether a body is valid JSON') and a key trait ('The body is discarded'). It distinguishes validate-json from the other sibling tools in purpose, though it does not explicitly name which parameter is the 'body'.
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, and no exclusions or conditions. Usage context is only implied by the tool name and the phrase 'Check whether a body is valid JSON'.
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.
bytes-kibcitationcompatibilitydomain-shapeiana-zonesinspect-robotsnormalize-urlstatus-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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