Merlonix Monitoring

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

Annotations already indicate readOnlyHint=false, idempotentHint=true, and destructiveHint=false. The description adds valuable context by explaining the state change ('marks it as seen/being-handled') and emphasizing it does not resolve the alert. The write scope requirement is also disclosed, which aligns with readOnlyHint=false. No contradictions with annotations.

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

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

The description is exceptionally concise: two sentences that front-load the core purpose, then add key constraints (not resolving, optional note, scope requirement). Every sentence contributes meaningful information with no fluff.

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 acknowledgment tool, the description covers the essential context despite lacking an output schema. It states the input source, the effect, and the access requirement. It does not describe the response format, but the action is straightforward and annotations plus schema provide adequate 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 100% with clear descriptions for both parameters. The description repeats that alert_id comes from list_my_alerts and note is optional, but these details are already fully captured in the schema. Thus the description adds no significant semantic value beyond the schema, warranting the baseline score.

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

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

The description clearly states the action: 'Acknowledge one of YOUR alerts' with a specific resource (alert id). It distinguishes from the sibling tool 'resolve_alert' by explicitly noting 'without resolving it', making the purpose 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?

It provides explicit guidance on when to use the tool: when you want to mark an alert as seen/being-handled but not resolve it. It also specifies that the alert id comes from 'list_my_alerts' and requires write scope, effectively telling the agent the prerequisite context and excluding the resolve path.

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 annotation only declares readOnlyHint: true, but the description adds valuable behavioral context: it fetches specific files, returns a letter grade with findings, and explicitly states 'No browser rendering or LLM call — deterministic HTTP/parse.' This goes beyond the annotation and helps the agent understand exactly what the tool does and its limitations.

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-loads the core purpose, and packs essential details (exact resources fetched, output type, deterministic method) with no redundant words. Every sentence earns its place, making it 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 simple tool with one parameter, a read-only annotation, and no output schema, the description is complete. It covers what the tool does, how it works (HTTP/parse), what it returns, and its non-browser/non-LLM nature. There is no missing information that would hinder an agent from invoking 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?

The input schema fully documents the single parameter 'hostname' with description 'A public hostname, e.g. example.com' (100% coverage). The description adds no additional meaning about parameter formatting or constraints beyond what the schema already provides, so the baseline 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 clearly states the tool's purpose: 'Score how ready a website is for AI agents and answer engines.' It specifies the exact resources fetched (/llms.txt, /robots.txt, homepage) and the output (letter grade with per-signal findings). This distinguishes it from sibling tools like check_domain_health and check_mcp_health, which focus on different aspects.

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 clear context for when to use this tool—when assessing a website's AI readiness. It does not explicitly mention alternatives or exclusions, but the purpose is self-evident given the sibling tool names. The exclusion of browser rendering and LLM calls gives a hint about its appropriate use cases, but no direct comparison to alternatives is provided.

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

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

The annotation readOnlyHint=true already covers the safe-read nature. The description adds substantive behavioral context: 'Each leg fails soft and is reported independently,' which tells the agent that failures in one check won't prevent others from reporting. This goes beyond the annotation and helps set expectations without contradicting it.

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

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

Two tightly packed sentences with no filler. The opening 'Check the live SSL/TLS certificate...' immediately communicates the primary action and object, and the second sentence adds critical behavioral nuance without redundancy.

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

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

For a single-parameter tool with three independent checks and no output schema, the description is largely sufficient. It states the three legs and the soft-fail reporting, which implies a structured response. The only gap is the exact return format, but the description allows an agent to invoke correctly and infer result independence.

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%—the hostname parameter is described as 'A public hostname, e.g. example.com.' The description reinforces 'any public hostname' but doesn't add new details about format, normalization, or edge cases. The baseline of 3 is appropriate since the schema carries the meaning.

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 the specific verb 'Check' and clearly enumerates the three distinct checks: SSL/TLS certificate (validity, expiry, issuer), DNS records (A/AAAA/MX/NS), and RDAP expiry. This differentiates it from sibling health check tools like check_mcp_health and check_agent_readiness, making it unambiguous what the tool does.

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 states it works on 'any public hostname' and notes that each leg 'fails soft and is reported independently,' implying a diagnostic scenario where partial failures are tolerated. While it doesn't explicitly compare to alternatives, the scope and behavior clearly signal when to use this tool (domain health assessment) versus check_mcp_health or check_agent_readiness.

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 that this is a real live network operation (not simulated), performs a JSON-RPC handshake and tools/list, and is deterministic with no LLM. This adds behavioral context beyond the readOnlyHint annotation, including what the tool returns and that it makes an actual remote call.

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 three sentences, front-loaded with the core purpose, followed by specific output details and a concrete use case. No word wasted; each sentence earns its place. It is appropriately sized for a tool with one parameter.

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 what the tool does, what it returns (status, protocol version, server name/version, inventory, transport, latency), and its deterministic nature. Since there is no output schema, the description fully compensates by listing the return fields. For a single-parameter tool, this is complete.

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% with a clear parameter description for 'url'. The description simply restates 'by URL' without adding new constraints or format details. The schema already tells the agent the parameter is an endpoint URL, so the description adds marginal value beyond that.

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 specific verb+resource: health-check a live MCP server by URL. It details the exact operations (initialize handshake, tools/list) and distinguishes itself from sibling tools focused on agent readiness or domain health by targeting MCP protocol compliance specifically.

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 explicitly states when to use it: 'Use it to verify your own MCP server is alive and spec-compliant.' It does not name alternatives or exclusions, but the use case is clearly scoped. Sibling tools exist for other health checks, so this gives adequate guidance without listing when-not conditions.

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

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

Annotations already indicate this is a write operation (readOnlyHint=false) and non-destructive (destructiveHint=false). The description adds behavioral context beyond annotations by stating the write scope requirement, plan quota error condition, and that it returns the created asset. This helps the agent understand consequences and prerequisites, though it doesn't cover duplicate handling or exact error semantics.

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 three sentences, front-loaded with the main purpose, followed by required inputs, optional inputs, and caveats. Every sentence earns its place; there is no redundancy or fluff.

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 no output schema, the description mentions the return value ('Returns the created asset'), which is helpful. It covers required inputs, optional settings, authentication, and error conditions. Missing are details on duplicate handling or idempotency, but these are not critical for a create tool and annotations already address mutation behavior. Overall, it is complete enough for a tool of this complexity.

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

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

Schema description coverage is 100%, so the schema already documents all 7 parameters. The description adds a small amount of semantic value by mentioning 'optionally a label and which checks to enable', which aggregates the check-related booleans, but it does not provide details beyond what the schema already states. This matches the baseline of 3 for full 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 clearly states the tool's purpose: 'Start monitoring a new asset' in the user's Merlonix account. The verb 'start monitoring' is specific and the resource is a new asset (website/domain). It distinguishes itself from siblings like update_asset, delete_asset, and list_my_assets by focusing on creation.

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 concrete usage context: require hostname and asset_type, optionally a label and checks. It also gives important preconditions: 'Requires an API key with write scope' and 'Subject to your plan asset quota (a full or non-paying plan returns an error)'. While it doesn't explicitly mention alternatives, the context is clear enough for an AI agent to decide when to call 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?

Beyond the annotations (destructiveHint, readOnlyHint), the description adds critical behavioral details: the operation is irreversible, removes check history, and requires write-scope API key. This fully discloses the consequences and prerequisites.

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 deliver purpose, irreversibility, and auth requirement without padding. The essential action is front-loaded, making it easy to scan.

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 destructive, one-parameter tool with no output schema, the description covers what the tool does, how to get the id, the irreversible nature, and required permissions. It is complete for an agent to safely decide and invoke.

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 already provides a complete description for asset_id (type, source, UUID), and the description repeats the same source. With 100% schema coverage, the description adds no new parameter semantics beyond reinforcement, meriting the baseline of 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?

The description clearly states a specific verb ('STOP monitoring' and 'remove') applied to a specific resource ('one of YOUR assets'), and distinguishes itself from siblings like create_asset and update_asset. It also references list_my_assets as the source for the asset id, making the operation precise.

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?

Provides clear context: use when you want to stop monitoring an asset, and notes the need for an id from list_my_assets and an API key with write scope. It does not explicitly name alternative tools for non-destructive updates, but the 'STOP monitoring' phrasing implies when not to use it.

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

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

The readOnlyHint annotation already establishes the safe, non-destructive nature. The description adds meaningful context by stating it fetches the latest results for a single asset and requires an API key, which goes beyond the annotation.

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

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

The description is one sentence, directly states the action, scope, and prerequisite, with no redundant words.

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

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

For a simple read-only tool with one parameter and no output schema, the description covers what results are returned (SSL, DNS, uptime, heartbeat, port), the single-asset scope, the source of the asset id, and the authentication requirement. This is sufficient for an agent to 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?

The single parameter asset_id is fully documented in the schema with a clear description referencing list_my_assets and UUID format. The tool description repeats this information without adding new meaning, so the schema carries the weight.

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 retrieves the latest check results (SSL, DNS, uptime, heartbeat, port) for a single monitored asset by asset id. This distinguishes it from siblings like list_my_assets (listing assets) and check_domain_health (domain-specific checks).

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 specifies the prerequisite of having an asset_id from list_my_assets and notes the need for an API key. It does not explicitly exclude alternatives, but the single-asset scope makes the use case clear, providing adequate context for selection.

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

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: it returns both current status and 30-day history, and is scoped to one monitored vendor. This goes beyond the annotation without contradicting it.

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

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

Two sentences, both informative, with no wasted words. The purpose and usage pointer are front-loaded, making it easy to parse quickly.

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

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

For a simple read-only tool with one parameter and no output schema, the description covers the essentials: what is returned (status + history), scope (single vendor), and how to obtain valid slugs. Minor lack of return format details, but not essential for 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%, but the description adds value by providing an example slug ('cloudflare') and directing users to list_vendor_status for discovering valid values, which enhances the parameter meaning beyond the schema.

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

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

The description states a specific verb ('Get') and resource ('current status plus 30-day status history of one monitored vendor'). It also clearly distinguishes from sibling list_vendor_status by specifying a single vendor and giving an example slug.

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?

Explicitly directs the user to list_vendor_status to discover valid slugs, which establishes when to use this tool vs. the sibling listing tool. This is clear alternative guidance within 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?

The readOnlyHint annotation already signals safety, and the description adds the API key requirement, which is a behavioral prerequisite not present in annotations. It also discloses the output contains severity and lifecycle status, providing useful context beyond the structured data.

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 action and includes essential details (scope, examples, output fields, auth requirement). Every phrase earns its place with no redundant 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 zero-parameter, read-only list tool with no output schema, the description is sufficiently complete. It explains what alerts are included, gives examples, mentions severity and lifecycle status, and notes the API key requirement, covering all relevant aspects for an agent to 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?

There are no parameters in the input schema, so the baseline is 4. The description doesn't need to explain parameter semantics; the empty schema already makes it clear the tool takes no arguments.

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 ('List'), clearly defines the resource ('recent alerts'), and scopes it to 'YOUR monitored assets'. It distinguishes from sibling tools like acknowledge_alert and resolve_alert by indicating this is a read-only listing operation, not a mutation.

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 clearly indicates the tool's purpose and context ('recent alerts across YOUR monitored assets') without ambiguity. It doesn't explicitly state when not to use it or mention alternatives, but the sibling tool names and the readOnlyHint provide enough context for straightforward selection.

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

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

The readOnlyHint annotation already indicates a safe read operation. The description adds valuable behavioral context by specifying the API key required (Bearer mk_…), the exact return fields, and the account-scoped nature. This goes beyond the annotation, though it does not mention rate limits or pagination, which are minor for a simple list endpoint.

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 three sentences and every sentence earns its place. It front-loads the core action ('List the monitored assets'), then details the output fields, then the authentication prerequisite. There is no redundancy or fluff, making it highly efficient for an agent to parse.

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 zero-parameter list tool with no output schema, the description is fully complete. It defines the scope, the authentication requirement, and what the response will contain (asset id, hostname, type, monitoring status). Given the simplicity, there are no meaningful gaps that could cause an agent to misuse the tool.

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

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

The tool has zero parameters, so the baseline is 4 per the rubric. The description correctly notes there are no parameters to configure, and the schema confirms this with an empty properties object. No additional parameter explanation is needed.

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 lists monitored assets (websites/domains) in the user's Merlonix account. It mentions the return fields (id, hostname, type, monitoring status), distinguishing it from sibling tools like create_asset, delete_asset, update_asset, and list_my_alerts. The verb 'List' and resource 'monitored assets' are specific and unambiguous.

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

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

The description provides context about scope ('YOUR Merlonix account') and authentication requirements (API key), which helps the agent understand when to use this tool. However, it does not explicitly state when not to use it or name alternative tools, falling short of a full 5. Still, the read-only intent is clear and aligns with the readOnlyHint annotation.

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

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

The annotations already declare readOnlyHint=true, and the description's 'List' verb is consistent. It adds useful context about the plan names and monitoring limits, but it does not disclose other behaviors such as return format, auth requirements, or potential variations. This is adequate for a simple read-only list, but not rich.

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 that immediately identifies the tool's purpose and enumerates the plan categories. No wasted words.

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 zero parameters, no output schema, and a simple read-only listing, the description provides all necessary context for an agent to select and invoke the tool. It names the plans and the included attribute (monitoring limits), making it complete for its simple scope.

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 tool has zero parameters, so the description carries no parameter burden. Baseline for 0 params is 4, and the description does not need to explain any parameter 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 lists Merlonix subscription plans and pricing, and it enumerates the specific plan names (Starter, Team, Agency, Compliance) and mentions monitoring limits. This specificity distinguishes it from sibling listing tools like list_my_alerts and list_my_assets.

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 this tool is for retrieving plan/pricing information, but it does not explicitly state when to use it relative to alternatives or include exclusions. Since there are no other plan-related tools among siblings, the context is reasonably clear, but the lack of explicit guidance holds it back from a 4.

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

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

Annotations already declare readOnlyHint=true, covering safety. The description adds scope (every Merlonix-monitored vendor) and output details (slug, status, 24h count), but does not discuss pagination, rate limits, or limitations. This adds some context but not rich behavioral 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 concise sentences with no redundancy. The verb 'List' leads, examples clarify vendor types, and return fields are specified. 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, no-parameter, read-only list tool, the description is largely complete: it states the purpose, scope, and return structure. The only minor gap is lack of explicit guidance on when to use this over the similar sibling get_vendor_status, but that is not essential for understanding the tool's operation.

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 tool has zero parameters, so the input schema provides no information. The description clarifies the tool's output and scope, but parameter semantics are inherently not applicable; the baseline for zero parameters is 4.

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 lists operational status and recent incidents for all monitored third-party vendors, with explicit output fields (slug, current status, 24h incident count). The word 'every' distinguishes it from the sibling 'get_vendor_status', which likely targets a single vendor.

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 for a bulk overview of all vendors but does not explicitly mention when to use this tool versus get_vendor_status or other list tools. No exclusions or alternatives are named, leaving usage only implicit.

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 idempotent and non-destructive behavior, the description adds context about closing the alert, the optional resolution and note, and the write-scope requirement. It doesn't contradict annotations.

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

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

Two sentences with the main action first, no fluff. Every word contributes: the verb, resource, ID source, optional parameters, and prerequisite.

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 mutation with 3 params, the description covers purpose, source of the ID, optionality, and auth scope. No output schema exists, so return details are not required. It is sufficiently complete for an agent to 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 covers all parameters (100%), but the description adds meaning by pointing alert_id to list_my_alerts and explaining the optional resolution enum and note. It goes beyond a bare schema listing.

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 resolves/closes an alert by ID, with a specific verb ('Resolve') and resource ('your alerts'). It differentiates from sibling tools like acknowledge_alert and list_my_alerts by indicating a closure action on existing alerts.

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 clear context: to close one of your alerts obtained from list_my_alerts, and it mentions the requirement of write scope. It doesn't explicitly exclude alternatives, but the intent is clear, and the write-scope note gives practical 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?

Annotations indicate readOnlyHint=false, idempotentHint=true, destructiveHint=false. The description adds that an API key with write scope is required and that the updated asset is returned. It does not contradict annotations and provides useful context beyond the structured fields.

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 action and purpose. It contains no redundant words and stays within a compact length.

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 tool's purpose, required authentication (write scope), and return value. Combined with the rich schema and annotations, it provides enough context for an AI agent to use it correctly. It could mention error cases, but that is not necessary given the structured data.

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 baseline is 3. The description adds meaning by explaining that 'relabel' corresponds to the label parameter and 'toggle which checks run' maps to the boolean parameters. It also clarifies that asset_id comes from list_my_assets, adding practical guidance 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 action: 'Update one of YOUR monitored assets by its asset id'. It specifies the resource (monitored assets) and the operations (relabel or toggle checks). This distinguishes it from sibling tools like create_asset, delete_asset, and list_my_assets.

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 tells the user to get the asset id from list_my_assets, which is a clear prerequisite. It implies the use case of modifying an existing asset, though it doesn't explicitly contrast with create or delete tools. The context from sibling names and the description makes the intended usage clear.

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