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 states what the tool does but does not describe the return format, whether it is read-only, potential side effects, pagination, or how the analysis is performed. The description essentially restates the purpose without adding behavioral context beyond the name.

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

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

The description is a single, concise sentence that is appropriately front-loaded with the core purpose. It contains no redundant information or filler words, making it efficient and easy 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?

Given the tool has six parameters and no output schema, the description is incomplete. It does not explain what the analysis returns, how to interpret the results, or how the optional parameters affect the outcome. Context is minimal, and the description alone would be insufficient for an agent to know how to effectively use the tool's capabilities.

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 provides 100% description coverage for all six parameters, so the description does not need to compensate. However, the description itself adds no extra semantic detail beyond what the schema already provides. The phrase 'different timeframes' loosely maps to the 'timeframe' parameter, but the schema already explains this, so the description adds marginal 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 tool's function: analyzing trending topics and content patterns across timeframes. It uses a specific verb ('analyze') and resource ('trending topics and content patterns'). However, it does not explicitly distinguish itself from sibling tools like 'get_trending_subjects' or 'search_content', which are related but different in scope.

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

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

The description provides no explicit guidance on when to use this tool versus alternatives. It implies usage through its purpose but does not offer exclusions, prerequisites, or comparisons to sibling tools. There is no mention of scenarios where this tool would be preferred over 'get_trending_subjects' or a general content search.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It only says 'Build a structured search query' without specifying whether this is a pure computation, makes network calls, returns data, or has side effects. This lack of context is a significant gap for an agent.

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

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

The description is a single, front-loaded sentence of 11 words with no redundancy or filler. Every word contributes to the core meaning, making it appropriately concise for the information conveyed.

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 5 parameters including a nested dateRange object and no output schema, the one-sentence description is insufficient. It fails to describe what the resulting query looks like, how it integrates with other search tools, or any constraints on filters, leaving significant contextual gaps.

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

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

The input schema already provides exhaustive descriptions for all 5 parameters (100% coverage), so the baseline is 3. The description's mention of 'filters' adds no extra semantic value beyond the schema, and no additional formatting or relationship details are 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 action ('Build') and the resource ('a structured search query for AP content using filters'), making it evident this is a query constructor rather than a search executor. However, it does not explicitly differentiate itself from sibling tools like optimize_search_query or search_content, which slightly limits the 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?

The description provides no guidance on when to use this tool versus alternatives. There are no 'use when' statements, exclusions, or mentions of sibling tools, leaving usage entirely to inference.

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

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

No annotations are provided, so the description must carry the behavioral disclosure burden. It only states that it creates a monitor but does not mention side effects, validation behavior, permissions, or what happens on duplicate names. This is minimal and does not disclose useful behavioral details.

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, clear sentence with no unnecessary words. It is front-loaded with the main action. Slightly more context could be added, but as written it is appropriately concise.

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

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

Given the tool has 6 parameters and no output schema or annotations, the description is too minimal to be complete. It does not explain what a content monitor is, when alerts are triggered, or what state the system is in after creation. The schema covers data details, but the description omits broader context.

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 input schema fully documents each parameter. The description adds no parameter-specific information. Per the rubric, baseline 3 is appropriate when schema coverage is high and description doesn't compensate.

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 (create) and the resource (a content monitor), with a purpose ('for alerts'). It distinguishes the tool from siblings like update_monitor and delete_monitor by indicating this is the creation operation.

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. There is no mention of prerequisites, whether this is the only way to create a monitor, or any context like typical use cases. It is a bare action statement.

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

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

With no annotations, the description must disclose behavioral traits. It states the action and identifier but does not mention that deletion is irreversible, potential side effects, or any authorization requirements, leaving important safety implications untold.

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

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

The description is a single, front-loaded sentence with no redundant words. It immediately states the action and the key parameter, making it highly efficient.

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-parameter tool, the description covers the core purpose. However, without annotations or an output schema, it omits important context such as irreversibility and success/failure behavior, leaving modest gaps.

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

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

The schema already documents monitor_id as 'Monitor ID or name' with 100% coverage. The description adds no further meaning beyond restating the identifier type, so it meets the baseline but does not exceed 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 uses the specific verb 'Delete' with the resource 'monitor', and clarifies that deletion can be done by ID or name. This clearly distinguishes it from sibling tools like get_monitor and update_monitor.

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

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

The intended use is implied by the action and resource: delete when a monitor should be removed. However, there is no explicit guidance about when not to use it or which alternative to choose, so the context is clear but not fully spelled out.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states 'Get account download history' without revealing any behavioral traits such as whether it returns a list, supports pagination, requires authentication, or what constitutes 'history'. This is minimal information beyond the tool's name.

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

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

The description is a single, front-loaded sentence with no unnecessary words. It gets straight to the point and is appropriately sized for the tool's straightforward name. There is no wasted content.

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 6 parameters, no output schema, and no annotations. The description is too under-specified to fully inform usage. It doesn't explain what fields are returned in the download history, how filters like min_date/max_date interplay, or the meaning of include/exclude. The schema covers parameters but not behavior or output, so the description should compensate; it doesn't.

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, each with a brief description (e.g., order, format, date filters). The tool description itself doesn't mention parameters, but since the schema already documents them, the baseline of 3 applies. No additional semantic value is provided by the description.

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

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

The description clearly states the tool's purpose: retrieving account download history. It uses a specific verb ('Get') and resource ('account download history'), which distinguishes it from sibling tools like get_account_info or get_account_plans. However, it relies heavily on the tool name and doesn't add additional scoping details, so it's not exceptionally informative.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, use cases, or exclusions. The agent receives no context about when to prefer this over other 'get' tools, making this a significant gap.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not state whether the operation is read-only, whether authentication is required, or what the response format looks like. The word 'get' implies a read operation, but that is an inference, not explicit disclosure.

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

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

The description is a single, concise sentence ('Get account information and available endpoints') that is front-loaded with the primary action. Every word contributes meaning, with no filler.

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

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

For a zero-parameter tool, the description is minimally sufficient, but it lacks elaboration on what specifically constitutes 'account information' or 'available endpoints'. Without an output schema or further details, the user is left to infer the exact return value and any implied 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?

The input schema is empty with zero parameters. Per the rubric, a baseline of 4 applies when no parameters exist, and the description does not need to provide additional 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's purpose: getting account information and available endpoints. The verb 'get' is specific, and the resource (account information) is identified, distinguishing it from sibling tools like get_account_plans and get_account_quotas that target narrower 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 no guidance on when to use this tool versus alternatives. There is no mention of context, exclusions, or when another tool would be more appropriate.

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

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

With no annotations, the description carries the full transparency burden. It does not disclose read-only behavior, required permissions, data scope, response format beyond the format parameter, or any side effects. The description is minimal and adds no extra 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 a single, clear sentence with no wasted words. It is appropriately concise for a tool with only optional parameters.

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

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

The tool has no output schema and annotations are absent, so the description must provide more context. It does not explain what 'plans and entitlements' includes, how results are structured, or any usage nuances. Minimal information for a potentially complex account-related 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 coverage is 100% (each parameter has a description), so the description does not need to explain parameters. It adds no additional meaning beyond the schema, matching the baseline for fully documented parameters.

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

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

The description uses a clear verb ('Get') and names a specific resource ('account plans and entitlements information'), which is reasonably distinct from siblings like get_account_info or get_account_quotas. However, it does not explicitly differentiate itself from those similar account-related 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?

No guidance is provided on when to use this tool versus alternatives such as get_account_info or get_account_quotas. The description only states what it does, not when it should be preferred, making it difficult for an agent to choose correctly.

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

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

No annotations are present, so the description must carry the burden of behavioral disclosure. It only states that the tool gets quotas/usage limits, but does not reveal response format, whether it is read-only (though 'get' implies it), or any other operational behavior. This is insufficient for a no-annotation tool.

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

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

The description is a single, front-loaded sentence that directly states the action and resource. It is concise and free of extraneous 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?

Given the simplicity of a zero-parameter tool, the description is minimally adequate, but it lacks details on the response structure (no output schema exists) and any usage context. It names quotas and usage limits but does not clarify how they are presented, making it a bare-bones pass.

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 there is no parameter schema to clarify. The description adds some context by naming what is returned, and the baseline for zero-parameter tools is 4, which is appropriate here.

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 'Get' and identifies the resource as 'account API quotas and usage limits', which clearly indicates what the tool does. It distinguishes from sibling account tools like get_account_info or get_account_plans by naming a distinct resource, but does not explicitly call out the differentiation.

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

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

The description provides no guidance on when to use this tool versus alternatives such as get_account_info or get_account_downloads. It only states the function without any context for selecting it over sibling tools.

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

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

No annotations are provided, so the description must convey behavioral traits. It vaguely mentions 'batch processing and error handling' but does not explain failure modes, partial results, missing-item behavior, or authentication needs. This is a significant gap for a bulk operation.

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, compact sentence that front-loads the core action. However, vague terms like 'efficiently' and 'error handling' add little specific value and could be replaced with more concrete details.

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

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

With no output schema and no annotations, the description is not complete for a tool of this complexity. It does not address expected return values, behavior on missing IDs (though parameter fail_on_missing hints at it), or any limits beyond the schema, leaving the agent under-informed.

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 provides 100% coverage with descriptions for all five parameters, so the description adds little beyond referencing IDs. The schema carries the semantic weight, making the value added by the description minimal.

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 multiple content items by IDs, which is a specific verb+resource+scope. It distinguishes itself from sibling tools like get_content_item by focusing on bulk retrieval.

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 retrieving multiple items by IDs, but it does not explicitly compare to alternatives like get_content_item or search_content, nor does it mention when not to use 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention pagination, response format, ordering, or any constraints on the feed. Merely stating 'get a feed' provides minimal insight into how the tool behaves beyond its basic read operation.

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

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

The description is a single concise sentence with no waste or redundant phrasing. It is front-loaded and easy to parse, earning a high score for efficiency, though the brevity limits its informative value.

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

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

Given the tool has 9 parameters, no output schema, and no annotations, the description is significantly under-specified. It fails to explain what 'AP content' means, how the feed is ordered or paginated, what fields are returned, or how the various filtering and inclusion parameters interact. The description is too sparse to provide a complete picture for an agent.

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% coverage, with each parameter including a description, so the schema does the heavy lifting. The tool description adds no parameter-specific semantics beyond what is already in the schema, which aligns with the baseline of 3 for high schema coverage.

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

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

Description states 'Get a feed of incoming AP content' with a specific verb and resource, clearly indicating a retrieval operation. However, it does not differentiate from sibling tools like search_content or get_content_bulk, which also retrieve content, so it lacks sibling distinction.

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 provided on when to use this tool versus the many alternative content retrieval tools. The single-sentence description offers no context about use cases, prerequisites, or exclusions, leaving the agent without direction for tool 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?

With no annotations provided, the description carries full burden for behavioral disclosure, but it only states the action without revealing any additional traits. It does not mention whether the operation is read-only, what happens on error, response format, or any rate limits. The 'get' verb implies read-only, but no further transparency is offered.

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

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

The description is a single concise sentence that is front-loaded with the core action and resource. It contains no fluff or redundant information, making it highly efficient.

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

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

Given the tool's simplicity (single required parameter) and full schema coverage, the description is minimally viable. However, it lacks any mention of optional response customization (like include/exclude fields) or return value details, and with no output schema, the agent might not know what to expect beyond 'the content item'. It is adequate but not 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 description coverage is 100%, so the baseline is 3 even though the description itself adds no parameter details. Each parameter has a description in the schema (e.g., item_id as 'The unique identifier for the content item'), so the description does not need to compensate.

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 'Get a specific content item by ID' clearly states the verb (get), resource (content item), and scope (specific by ID), distinguishing it from sibling tools like get_content_feed (feed) and search_content (search). The phrase 'specific' implies a single item, which differentiates it from bulk 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?

No guidance is given on when to use this tool versus alternatives. The description does not mention any exclusions, prerequisites, or comparisons to sibling tools. An agent would have to infer from the name and siblings that this is for fetching a single item by ID.

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

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions 'relevance scoring' which hints at output characteristics, but fails to detail any side effects, filters, defaults, or that the operation is read-only. The description is too sparse to adequately disclose behavioral traits beyond the core function.

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

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

The description is a single sentence that is front-loaded with the core purpose ('Get personalized content recommendations') and adds a distinguishing detail ('relevance scoring'). It is appropriately concise with zero 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 8 optional parameters, no output schema, and no annotations, the one-sentence description leaves significant gaps. It doesn't explain how recommendations are generated, what the response looks like, or how parameters like similarity_threshold and recency_preference affect behavior. This is inadequate for a complex tool, especially compared to the detailed 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 description coverage is 100%, with all 8 parameters well-documented in the schema. The description adds no additional parameter semantics beyond what the schema already provides. This meets the baseline of 3, as the schema does the heavy lifting.

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 personalized content recommendations with relevance scoring. This distinguishes it from sibling tools like search_content (query-based) and get_content_feed (feed-based). The verb 'Get' and specific resource 'personalized content recommendations' are concise 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 implies usage for obtaining personalized recommendations, but does not explicitly contrast with alternative tools (e.g., search_content vs. get_content_feed) or specify when this tool should be preferred. No exclusions or prerequisites are provided, so the guidance is inferred rather than explicit.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool retrieves content (a read operation), but does not mention potential rate limits, auth requirements, return format, or error handling. The behavior is adequately conveyed for a simple fetch but lacks depth.

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 directly states the tool's function without redundancy. It earns its place with 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?

The tool is simple with well-documented parameters and no output schema. The description covers the core use case (fetching content via href). It could mention return type or typical usage patterns, but for this complexity level it is reasonably 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 description coverage is 100%, so the schema fully documents each parameter. The description adds minimal value beyond the schema by contextualizing href as coming from 'previous search results', but it does not explain formats or additional nuances. Baseline 3 is appropriate.

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

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

The description clearly specifies the action ('Retrieve the full content'), the resource ('articles and media'), and the method ('fetching renditions using href URLs from previous search results'). This distinguishes it from sibling tools like get_content_item or search_content, which serve different purposes.

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 explicit usage context: it is meant to be used with href URLs obtained from previous search results. While it doesn't name alternative tools or exclusions, the 'from previous search results' phrase clearly signals the intended workflow after a search.

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

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

With no annotations, the description must convey behavioral traits itself. It identifies this as a read operation ('Get'), but does not disclose whether authentication is required, how results are paginated, what 'subscriptions' maps to, or any response-shaping constraints beyond the schema parameters.

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

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

The description is a single, front-loaded sentence with no filler. It is appropriately brief for a simple getter, though slightly more detail could be added without losing 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 no output schema and no annotations, so the description must compensate but does not mention return format, default behavior of the optional format parameter, or the shape of the result. The description is minimal and leaves the agent to infer common behavior for a listing 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 coverage is 100%, so the parameters are already documented with names and descriptions. The description adds no parameter-specific detail beyond the schema, but the baseline 3 applies because 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 a specific verb ('Get') and names the resource ('user's followed topics and subscriptions'), making the tool's function immediately clear. It is distinguishable from sibling tools like search_content or get_trending_subjects, though it does not explicitly contrast with 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?

No guidance is provided about when to choose this tool over alternatives, such as get_trending_subjects for trending topics or search_content for general content. The description implies a use case but offers no exclusions, prerequisites, or 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?

With no annotations, the description carries the full burden. It clearly indicates a read operation via 'Get' and the identification method, but it does not disclose behaviors such as error handling, return type, or authentication requirements. The description is acceptable for a simple getter, but lacks depth.

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

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

One concise sentence with no fluff; it gets straight to the point. It is appropriately front-loaded with the verb and resource.

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 is simple with one parameter and no output schema. The description states the core function but does not mention the return value or error behavior. Given the absence of an output schema, it could benefit from specifying that it returns the monitor details, but for a low-complexity get, it is minimally sufficient.

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 fully documents the single parameter with a description ('Monitor ID or name'). The tool description adds no additional semantic detail beyond what the schema 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 uses the specific verb 'Get' and resource 'monitor', and clarifies identification by ID or name. It clearly differentiates from list_monitors (which lists all) and implicitly from status/history siblings, though it does not explicitly name alternatives.

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 provided on when to use this tool versus siblings like get_monitor_status or list_monitors. The usage context is limited to the basic operation with no exclusions or alternatives.

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

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

No annotations are provided, so the description carries the full burden. It only says 'Get monitor activity history' without disclosing pagination, filtering behavior, output structure, or any side effects. For a read tool, the lack of detail about what 'activity' entails is a significant gap.

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

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

The description is a single brief sentence with no redundancy, but it is under-specified. It is concise but not appropriately sized given the tool's complexity, as it omits needed details without being efficient in conveying 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 7 parameters and no output schema, the description should explain what 'activity history' returns, how filters interact, and what the response format is. The minimal description leaves too much unspecified for a tool with 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%, and all parameters have descriptions, so the schema alone documents parameter meanings. The description adds no additional semantic context beyond what the schema already 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 'Get monitor activity history' identifies the resource (monitor) and action (get history), but 'activity history' is vague and does not specify what constitutes activity or the time scope. It distinguishes from get_monitor_status (status vs. history) but not strongly.

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 provided on when to use this tool versus alternatives like get_monitor_status or list_monitors. There is no mention of exclusions, preferences, or conditions that make this tool the right 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?

With no annotations, the description carries the full burden. It only says 'Get monitor status and recent alerts' without disclosing what status means, the time window for alerts, or any other behavioral nuances. There is no contradiction, but the description is minimal.

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

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

The description is a single, front-loaded sentence with no filler. It communicates the core purpose efficiently, though it lacks depth.

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 3 parameters, no annotations, and no output schema, the description does not explain return values or how to interpret 'status' and 'alerts'. This is inadequate for a monitor-related API 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% (all three parameters have descriptions). The tool description adds no parameter-level detail beyond what the schema 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 a specific action ('Get') on a specific resource ('monitor status and recent alerts'). It is distinct from sibling tools like get_monitor_history, though it could explicitly contrast with 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?

No guidance is provided on when to use this tool versus alternatives. Sibling tools such as get_monitor_history or list_monitors exist, but the description does not mention them or exclusion criteria.

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

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

With no annotations, the description carries the full burden. It only states the basic purpose without disclosing pagination, return format, side effects, authentication, or deduplication behavior. The schema provides parameter details, but behavioral expectations are still unclear.

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 immediately states the purpose. It is front-loaded with the verb and resource, with no unnecessary words 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?

With no annotations, no output schema, and 7 parameters, the description is too minimal. It doesn't explain response structure or behavioral nuances such as consumer_id deduplication or pagination, leaving the agent to infer these from parameter names alone.

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

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

All 7 parameters have schema descriptions, providing 100% coverage. The description adds no additional parameter meaning beyond the schema, but the baseline of 3 is appropriate since the schema handles parameter semantics adequately.

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

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

The description clearly identifies the action (Get), the resource (AP content items), and the specific context (OnDemand queue). It distinguishes this tool from sibling content tools like get_content_feed or search_content by focusing on the OnDemand queue.

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

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

The description implies the tool is for retrieving OnDemand queue items, but it provides no explicit guidance on when to use it versus alternatives like search_content or get_content_feed. No exclusions or alternative tool names are mentioned.

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

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

With no annotations provided, the description carries full responsibility for disclosing behavior. It only says 'Get', which implies read-only, but gives no details on response format, pagination, authentication, or side effects. This is minimal disclosure beyond the tool's name.

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

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

The description is a single, concise sentence that is front-loaded with the key information. 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?

While the schema covers parameters well, the description does not mention response behavior or the advanced filtering/pagination capabilities (include/exclude/page_size). With no output schema, the description should provide some context on return values, but it is still adequate for a simple get-by-ID 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 input schema already provides 100% description coverage for all four parameters (rss_id, exclude, include, page_size). The description adds no additional parameter semantics beyond the ID, so the baseline of 3 applies.

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

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

Description states 'Get a specific RSS feed by ID', which clearly identifies the action (get), resource (specific RSS feed), and the key identifier (ID). This distinguishes it from the sibling tool get_rss_feeds (plural), which presumably lists all feeds.

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 is used when you have a specific RSS feed ID to retrieve, but it does not explicitly state when to use this tool over alternatives like get_rss_feeds or provide any exclusions or prerequisites.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Get list of available RSS feeds', which implies a read operation but does not disclose return format, pagination, authentication needs, or whether all feeds or only user-accessible feeds are returned. The description adds minimal insight beyond the tool's name and title.

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, tightly worded sentence: 'Get list of available RSS feeds'. Every word contributes to the meaning, and there is no redundancy or filler. It is appropriately sized for a zero-parameter tool.

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

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

Given zero parameters, no output schema, and no annotations, the description gives a basic understanding of the tool's purpose. However, it leaves ambiguity about the response structure and does not clarify the relationship with the sibling tool 'get_rss_feed'. A sentence or two about what the list contains or when to prefer this over the singular variant would make it more 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?

The input schema has zero parameters, so the baseline is 4. The description correctly does not attempt to document parameters, and no parameter details are needed. The absence of parameters is fully captured by the schema, so the description needs no further elaboration.

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

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

The description clearly states the tool's function: 'Get list of available RSS feeds' with a specific verb 'Get' and resource 'RSS feeds'. It implicitly distinguishes from the sibling tool 'get_rss_feed' (singular) by using 'list' and 'feeds', though it does not explicitly name the alternative.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'get_rss_feed' (singular). There is no mention of context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone.

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

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

With no annotations, the description should carry the full behavioral burden. It conveys 'quick' and 'without full content analysis' but omits return format, data source, pagination, or permission requirements, making it insufficient for a tool with zero structural safety 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?

The single-sentence description is extremely concise and free of fluff, but it may be under-specified; still, 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?

The tool has four optional parameters and no output schema. The description leaves the output format undefined and does not clarify the differences with analyze_content_trends, so agents may struggle to set correct expectations.

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 all four parameters with descriptions, enum, and defaults. The description adds no extra parameter semantics or usage examples, so baseline 3 is warranted.

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

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

The description identifies the tool as discovering trending subjects and hints at a lightweight scope ('without full content analysis'), but 'subjects' remains ambiguous and no direct comparison to sibling tools like analyze_content_trends is made.

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 implies a use case (rapid topic insights) and contrasts with full content analysis, but it doesn't explicitly state when to choose this over analyze_content_trends or search_content, nor does it mention any 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?

With no annotations, the description carries the burden. 'List' implies a read-only operation with no side effects, which is disclosed. However, it does not mention potential pagination, ordering, or what data each monitor contains. This is minimal but adequate for a zero-parameter read tool.

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

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

The description is a single concise sentence, 'List all existing monitors', which is front-loaded and contains no filler. Every word adds value beyond the title.

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 low complexity (no parameters, no output schema, no annotations), the description is mostly complete. It clearly states what the tool does. It could mention that no filtering is possible or how results are presented, but for a trivial list tool, this is not a critical 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?

The tool has zero parameters and schema coverage is 100% (empty). There is no parameter information needed, so the description does not need to compensate. The baseline for zero parameters is 4, and the description adds no unnecessary detail.

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 'List all existing monitors' uses a specific verb (list) and resource (monitors), and the qualifier 'all existing' clearly distinguishes it from sibling tools like get_monitor (which targets a single monitor). It fully clarifies the tool's scope.

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

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

The description implies usage (when you want all monitors) but does not explicitly contrast with alternatives like get_monitor or mention any exclusions. For a simple list tool, this is acceptable but not informative beyond the obvious.

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

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not state whether this is a read-only operation, what the output looks like, or any side effects. The description only says it converts queries, which is insufficient for an agent to anticipate 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 a single, concise sentence with no wasted words. However, the phrase 'intelligent suggestions' is vague and could be more precise, so it is not a perfect score.

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 absence of an output schema, the lack of annotations, and the presence of a nested object parameter, the description is incomplete. It does not explain the return value, how 'optimized' is determined, or the format of the suggestions, leaving important gaps 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 description coverage is 100% for all parameters, so the description does not need to elaborate. Baseline of 3 is appropriate; the description adds no additional meaning beyond the schema but does not need to.

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

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

The description clearly states the tool's function: converting natural language queries into optimized AP search syntax with suggestions. However, it does not differentiate from the sibling tool 'build_search_query', which may perform a similar conversion, so it loses a point for lacking sibling differentiation.

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

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

There is no guidance on when to use this tool versus alternatives like 'search_content' or 'build_search_query'. No prerequisites, exclusions, or specific use cases are mentioned, leaving the agent to infer usage from the description alone.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. 'Search for AP content using flexible query parameters' only implies a read operation; it does not mention pagination, response format, rate limits, or potential side effects. This is insufficient for an unannotated tool.

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

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

The description is a single, front-loaded sentence with no wasted words. It is concise, though somewhat sparse for a tool with many parameters and no annotations.

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

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

Given the tool has 9 parameters, no annotations, no output schema, and multiple sibling search tools, the one-line description is too generic. It does not explain what queries are supported, what results look like, or how it differs from search_content_all or build_search_query. The overall context is incomplete.

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

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

The input schema already provides descriptions for all 9 parameters, achieving 100% coverage. The description adds no extra parameter meaning beyond the generic 'flexible query parameters,' which is vague. Baseline 3 is appropriate since the schema does the heavy lifting.

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 searches for AP content with a specific verb and resource. However, it does not differentiate from sibling search tools like search_content_all or build_search_query, so it loses a point for lack of sibling distinction.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or contexts where a sibling tool might be preferred. This is a clear gap given the number of related search tools.

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

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

With no annotations, the description must disclose behavioral traits. It mentions automatic pagination and efficiency, but it is misleading by saying 'all matching results' when the max_results parameter defaults to 500, potentially capping results. It omits other behaviors like rate limits, output format, and whether the operation is read-only.

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, focused sentence that front-loads the verb and resource, with no redundancy. It is concise and readable, earning its place.

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

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

The tool has 11 parameters and no output schema or annotations. The description is too brief to provide complete context, missing key behaviors like the default result cap, deduplication feature, and output structure. It only covers the basic search purpose.

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

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

Schema coverage is 100%, so the baseline is 3. The description doesn't add specific parameter semantics beyond the concept of pagination and retrieving all results, which are already reflected in parameters like page_size and max_results.

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 searches AP content, with the specific behavior of automatic pagination to retrieve all matching results. However, it doesn't explicitly differentiate from the sibling 'search_content' tool, though the 'all' scope implies it is the comprehensive version.

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

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

The description implies the use case for retrieving all matching results, but it doesn't explicitly state when to use this versus search_content or other alternatives, nor does it provide any exclusions or prerequisites.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. The description merely restates the action and gives no information about side effects (e.g., whether existing values are overwritten), authentication requirements, rate limits, or what happens on failure. This is a critical gap for a mutation tool.

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

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

The description is a single sentence with no wordiness. It conveys the basic purpose efficiently, but it is so terse that it doesn't add meaningful context beyond the tool name. This is concise but under-specified; a 4 is appropriate because there is no fluff, yet it could be improved with brief behavioral notes.

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 7 parameters, no output schema, and no annotations, the description is extremely sparse. It doesn't explain update semantics (partial vs full replacement), required fields, or what a successful update returns. The schema documents parameters but not the operation's overall behavior, leaving an agent under-informed. A score of 2 reflects this significant 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?

The input schema contains detailed descriptions for all 7 parameters (e.g., name pattern, notify array structure, conditions criteria). Since the description adds no parameter-level detail, the schema is the sole source; according to the rubric, this is a baseline 3 because the schema covers parameter semantics comprehensively.

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') and the target resource ('an existing monitor'). It distinguishes from sibling tools like create_monitor, get_monitor, and delete_monitor by using the 'update' verb. However, it provides no additional scope or detail about what updating entails.

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 create_monitor or get_monitor. No context about prerequisites, partial vs full updates, or exclusions is provided. The agent must infer usage purely from the tool name and schema.

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