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

Annotations already mark this as non-read-only and non-idempotent, so the description doesn't need to restate that. It adds value by disclosing the default channels behavior and the upsert side effect, which are behavioral traits not covered by annotations. This is useful context that goes beyond the structured hints.

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 sentences with zero fluff. Each sentence conveys a distinct, high-value fact: creation, parameter exclusivity, default channels, and upsert behavior. The most important caveats are 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?

Given 19 parameters with full schema descriptions and an output schema present, the description covers the critical interactions (mutual exclusivity, default channels, upsert) that could otherwise trip up an agent. There is nothing essential missing 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?

Schema coverage is 100%, so each parameter is individually documented. The description adds the mutual exclusivity between timeout and schedule and the default value of channels, which are relationships not visible in the schema. That's meaningful added value beyond what the schema already provides.

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

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

The description opens with 'Creates a check', a specific verb and resource, and immediately distinguishes the create path from an upsert that may update an existing check. It clearly states what the tool does and hints at its relationship to update_check, so an agent can tell it apart without reading the schema.

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

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

It provides critical usage rules: pass either timeout or schedule (never both), and notes the default channels behavior (notify all integrations unless overridden). It doesn't explicitly say 'use this for new checks, use update_check for existing ones', but the upsert semantics imply that; the guidance is strong but not exhaustive on sibling selection.

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

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

The description goes beyond the annotations by describing the permanent nature of the deletion, the irrecoverable UUID, the impact on deployed scripts, and the two-step token process. This provides rich behavioral context that the annotations alone do not convey.

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 and well-structured, with the main operation stated first, followed by consequences and the two-step process. The warning about scripts breaking is somewhat tangential but adds useful context without making the description overly long.

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 output schema exists, the description does not need to explain return values. It adequately covers the operation, consequences, and the two-step procedure, making it complete for an agent to decide whether and how to call 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 schema already provides full descriptions for both parameters (check UUID and confirm_token), covering 100% of the parameters. The description adds a little context about the two-step process but does not significantly enhance the parameter understanding 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 that the tool deletes a check permanently, which is a specific verb and resource. It distinguishes itself from sibling tools like update_check, pause_check, and resume_check by explicitly focusing on deletion.

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 explains when to use the tool (to delete a check) and warns about the consequences (scripts breaking, permanent deletion). It also outlines the two-step confirmation process, which is essential usage guidance. It does not explicitly mention alternatives, but the purpose is clear enough.

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 this tool as read-only and idempotent, and the description aligns with those hints. It adds valuable behavioral context beyond the annotations by explaining what the tool actually reports and how the result affects the usability and identifier conventions of sibling tools.

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, dense sentence that front-loads the core purpose and then adds the most useful implications of the result. Every clause earns its place; there is no repetition, filler, or irrelevant detail.

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 configuration query tool with an output schema available, the description is fully complete. It tells an agent what the tool reports, why that matters, and how the result should shape subsequent tool selection and parameter formatting.

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, and the schema covers all of them trivially at 100%. With no parameters to document, the description's explanation of the output semantics is sufficient and adds meaning beyond the empty input 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 a specific verb ('Reports') and resource ('API key info'), and details exactly what is reported: configured instance, key validity, and key permissions. It also distinguishes this diagnostic tool from its data-manipulation siblings by explaining that its output governs how other tools can be used.

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 implies when to use this tool: before calling list_pings, get_ping_body, or list_integrations, and to determine the correct identifier format for checks. It provides strong contextual guidance, though it does not explicitly state a when-not-to-use condition or name an alternative diagnostic 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?

Annotations already cover readOnly, idempotent, and destructive hints. The description adds useful behavioral context: that it accepts a unique_key from read-only API keys, and that it returns all fields including specific ones. This goes beyond the annotations without contradicting them.

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 no fluff. The main action is front-loaded, and the unique_key nuance is placed second. Every word contributes to the tool's understanding.

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 single-fetch tool with an output schema and complete annotations, the description covers what the tool does, how it identifies the check, and the key return fields. Nothing essential for calling it correctly is missing.

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

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

Schema description coverage is 100%, so the schema already explains the parameter fully ('Check UUID, or the unique_key that a read-only API key returns instead'). The description repeats this without adding new semantic depth, 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 states a clear verb ('Fetches') and resource ('one check'), and specifies it returns all fields including description and keyword filters. This distinguishes it from list_checks (which fetches many) and other sibling tools, making its 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?

The description clearly implies usage for retrieving a single check by UUID or unique_key, and the contrast with list_checks is implicit. It doesn't explicitly name alternatives or exclusion criteria, but the context is clear enough for an agent to decide when to call 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?

Annotations already mark the operation as read-only, idempotent, and non-destructive. The description adds critical behavioral detail about the read-write API key requirement and the 401 failure mode, which goes beyond the annotations, even if the wording is convoluted.

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 overly verbose and repetitive, especially the two paragraphs about read-only keys and the confusing 'not what it sounds like' phrasing. The core purpose is stated early, but the redundant warnings could be condensed significantly.

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?

Covers auth requirements, parameter provenance, and failure modes, which is good. However, the confusingly worded second paragraph muddles the message about why read-only keys fail, making the context less clear than it could be.

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%, and the description adds useful guidance: 'n' is tied to list_pings output, and 'check' is explained as a UUID that read-only keys never see, with a pointer to list_checks. This enriches the raw schema definitions.

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?

Clearly states the tool returns the body POSTed with a ping, identifies it as the job output, and frames it as the fastest way to see why a check failed. This distinguishes it from siblings like list_pings or get_status.

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

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

Gives a concrete use case ('fastest way to see why a check failed') and explicitly warns that a read-write API key is required while read-only keys are refused. It points to get_api_key_info for checking key type, though it could more directly contrast with list_pings for retrieving ping numbers.

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 the tool as read-only, idempotent, and non-destructive, and the description aligns with these attributes. It adds the extra behavioral detail that no API key is needed, which is not covered by the annotations. This transparency helps the agent understand the tool's side-effect profile.

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 and well-structured, consisting of two sentences. The first sentence states the core function, and the second provides usage context. No unnecessary words or redundancy are present.

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 provides sufficient context for an agent to know when and why to call this tool, including the fact that it requires no API key and is ideal for initial troubleshooting. Since the output schema is defined separately, the description does not need to cover return values. It is complete for effective selection and 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 schema has no parameters (empty properties), so parameter coverage is trivially complete. With no parameters to describe, the description cannot add further semantic detail. The baseline of 3 is appropriate since there is nothing to explain 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 purpose: checking the reachability of the configured Healthchecks instance and its database. The verb 'checks' is specific and the resource is well-defined. It also implicitly differentiates itself from sibling tools that perform data operations rather than health 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 provides explicit guidance on when to use the tool: 'try first when something is not working'. It also notes that no API key is required, which helps an agent decide to use this tool as a preliminary diagnostic step before trying others that may need authentication.

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 provide readOnly, idempotent, and non-destructive hints, which cover the core behavioral expectations. The description adds no extra side-effect or rate-limit information but does not contradict the annotations, so a neutral score is appropriate.

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, concise, and directly to the point. It includes necessary detail about the two variants without any extraneous text or redundancy.

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

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

No output schema is provided, so the description must convey the expected return. It explains the two types of URLs and their semantics, which gives a solid understanding of the output. The exact structure (e.g., array of strings) is not specified, but it is reasonably implied.

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, and the schema coverage is therefore 100% (vacuously). With no parameters to document, the description does not need to add parameter-level detail, so the baseline score of 4 is given.

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 resource (status badge URLs) and the specific scope (one per tag plus project-wide). It also explains the distinction between plain and '3'-suffixed variants, which differentiates it from other list tools in the sibling set.

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 does not provide explicit guidance on when to use this tool versus alternatives, such as list_checks or list_pings. It describes what the tool does but not the conditions that would make it the preferred choice.

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

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds meaningful operational details such as project scoping, ordering, and omission of descriptions, which complement the annotations without contradiction.

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

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

The description is compact and focused, using two sentences to cover purpose, scope, ordering, and a pointer to a related tool. No redundant or irrelevant information is included.

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 provides enough context about what is returned and how it differs from get_check. Since an output schema is present and the limit parameter is documented, the agent has sufficient information to invoke the tool correctly.

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

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

The input schema fully documents every parameter with descriptions and constraints, including the client-side status filter. The tool description itself does not add extra parameter context, but since schema coverage is 100%, 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?

Clearly states the tool lists checks in the current project and orders them newest state first. It also distinguishes itself from get_check by explicitly noting that descriptions are omitted.

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 useful direction by stating the project scope and pointing to get_check when descriptions are needed. It does not explicitly list all alternatives, but the key distinction from the most relevant sibling is present.

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, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond those: the instance retains only the current month and the two prior months, and either a UUID or unique_key may be used. This goes beyond what annotations provide.

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 no filler: the action is stated first, then scope/retention, then the accepted identifier format. 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?

Given the annotations, output schema, and fully described input schema, the description provides enough orientation for a simple read-only history tool. The retention limit and identifier flexibility are useful additions. It could be stronger with explicit sibling guidance, but nothing critical is missing.

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

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

Schema coverage is 100%, so every parameter already has a description. The tool description restates the UUID/unique_key identifier behavior but adds little beyond the schema. Baseline 3 is appropriate because the schema carries the parameter-documentation burden.

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

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

The description names a specific verb ('Lists') and a specific resource ('the up/down transitions of a check'), and clarifies that these are the history behind the current status. This clearly distinguishes it from siblings like list_pings or get_status even without naming them.

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

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

The intended use—viewing flip history for a check—is implied by the description, and the retention-window note ('current month and the two before it') gives practical context. However, it does not explicitly state when to choose this over list_pings or get_status, nor does it mention alternatives or exclusions.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description goes beyond these by disclosing that the endpoint nevertheless requires a read-write API key, that a read-only key causes a misleading 401 'wrong api key', and that the underlying check-addressing mechanism makes the tool unusable with a read-only key. This is valuable non-obvious behavioral context.

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 front-loaded with the primary purpose, but it becomes overly verbose in the final paragraphs, repeating the read-only key limitation more than necessary. While every sentence contributes useful information, the same guidance could be delivered in a more compact way.

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 listing tool, the description fully covers the key operational context: output purpose, API key requirements, failure modes, and how to verify key type. The presence of an output schema reduces the need to describe return shapes, and the auth caveat is explained thoroughly.

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. The description adds relevant context by stating what the returned UUIDs are for, which compensates for not having any parameter documentation to provide.

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

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

The description states the specific action ('Lists the notification integrations of the project') and the concrete purpose (providing UUIDs used by create_check and update_check). This clearly distinguishes it from the other listing tools such as list_checks and list_badges.

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 explicitly explains that integrations can only be created in the web UI, and gives clear guidance on read-only vs read-write API key behavior, including when to call get_api_key_info. It also explains why the tool cannot be used correctly with a read-only key, leaving little ambiguity about when it is usable.

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 goes far beyond the annotations by revealing plan-based caps (100/1000), absence of pagination, the misleading HTTP 401 'wrong api key' error, and the UUID vs unique_key mismatch with read-only keys. These are behavioral traits not visible in annotations or schema, and they materially affect whether and how the tool can be called.

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 front-loaded with the core behavior and caps, but the final paragraph repeats the read-only/UUID limitation already stated in the previous paragraph. The same point about 'read-only key cannot see a check UUID' appears twice, making it longer than necessary. Still, the structure flows from behavior to auth caveats to invocation details.

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

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

For a tool with this complexity, the description covers the essential invocation conditions, failure modes, plan limits, pagination absence, and recommended preflight via get_api_key_info. Since an output schema exists, return-value documentation is not needed. Nothing critical is missing for an agent to decide whether and how to call this 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. The schema already documents the check UUID, the read-only key limitation, the type enum, and the limit default and bounds. The description adds operational context like plan caps and the unique_key issue, but these are more behavioral than parameter-specific, so the schema remains the primary source for parameter 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 opens with a specific verb and resource: 'Lists recent pings of a check, newest first.' This clearly identifies the tool's function and separates it from sibling tools like get_ping_body or list_flips. No ambiguity about 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 gives actionable guidance: it explains that a read-only key cannot be used, recommends calling get_api_key_info to verify key type, and clarifies that the endpoint is unreachable with a read-only key. It does not explicitly compare to sibling tools for listing pings, but the usage preconditions and fallback actions are clear.

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 (readOnlyHint=false, destructiveHint=false, idempotentHint=true), the description adds concrete behavioral details: it stops expecting pings, stops alerting, and the caveat that a stopped job goes unnoticed while paused. This goes beyond the basic annotation info.

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 contains some meta-commentary like 'so this is not asked about' and 'It does mean...' which adds slight verbosity without improving clarity. It could be more streamlined while retaining the useful caveat.

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 that an output schema exists and the description focuses on the action's effect (pausing, stopping alerts, preserving data), it is sufficiently complete for an agent to invoke the tool. It does not describe return values, but that is covered by the output 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?

The schema already covers the 'check' parameter with a UUID pattern and description, and the description adds extra context about read-only API keys and how to obtain the UUID via list_checks. This exceeds the baseline for fully documented 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 purpose: 'Pauses a check: it stops expecting pings and stops alerting.' It also distinguishes it from the sibling tool 'resume_check', making the function 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 indirectly signals when to use the tool by contrasting with resume_check and noting that 'nothing is lost in between'. However, it does not explicitly state a selection criterion against other tools like get_check or list_checks, so only a minor deduction.

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 the failure condition (HTTP 409 if the check is not paused) and the state change (back to 'new'), which are key behavioral aspects. It aligns with the annotations (idempotent, non-destructive) and does not contradict them, providing a transparent picture of the tool's effects.

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

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

The description is a single, concise sentence that conveys the action, the resulting state, and a key failure condition without unnecessary words. It is well-structured and immediately digestible.

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 behavior but does not mention the return value or output format (despite the context indicating an output schema exists). An agent would not know what to expect in the response (e.g., the updated check object or just a status code), leaving a minor gap in 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?

The schema fully covers the single 'check' parameter with a description and pattern. The description in the tool does not add extra semantic detail beyond what's already in the schema, so it meets the baseline for high schema coverage but provides no additional 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 verb 'resumes' and the resource 'paused check', specifying the transition to the 'new' state. It differentiates from sibling tools like pause_check and update_check by focusing on the specific resume action.

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 explicit guidance is given on when to use this tool versus alternatives (e.g., when to resume instead of update or pause). The description only states what it does, not the conditions under which it should be chosen, leaving the agent to infer from the tool name and context.

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 explains key behavioral aspects not covered by annotations: that unspecified fields remain unchanged, that channels replaces the integration list, and that schedule takes precedence over timeout. It also mentions the requirement for a UUID and the limitation of read-only keys, adding transparency beyond the basic 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 a single, well-structured sentence that packs essential information without verbosity. It front-loads the core purpose and then provides critical exceptions and requirements, making it efficient and clear.

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 complexity of 19 parameters, the description covers the most important contextual points: the partial update behavior, the two notable exceptions, the need for a UUID, and the restriction on read-only keys. With an output schema present, it appropriately omits return value details, making the description comprehensive.

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 covers 100% of parameters with individual descriptions, so the baseline is 3. The description adds unique cross-parameter semantics, such as the general rule about unspecified fields and the specific exceptions for channels and schedule, which are not captured in any single parameter 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 that the tool updates a check, and it distinguishes itself from sibling tools like create_check, pause_check, and delete_check. It also notes the need for a UUID, which is unique to update operations.

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

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

The description implies usage for modifying existing checks and provides important context about partial updates and exceptions (channels replacement, schedule switching). It doesn't explicitly say 'use this when you need to modify a check' but that is strongly implied. It also mentions that read-only API keys cannot be used, which is useful guidance.

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