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. 'Full content' hints that the response includes the complete article body rather than a snippet, but nothing is said about error behavior for invalid IDs, permissions, rate limits, or response format.

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

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

A single tight sentence that front-loads the verb and resource with zero filler. Nothing could be removed without losing 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?

For a one-parameter read tool with no output schema, the description is adequate but thin: it does not characterize the returned content shape beyond 'full content', nor does it cover failure modes. An agent can call it correctly, but with minimal supporting 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% for the single 'article_id' parameter, so the schema already documents it. The description's 'by ID' matches that semantic but adds no further meaning such as expected format or where to obtain the ID.

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

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

The description states a specific verb ('Get') and resource ('Help Center article') with a clear identifier qualifier ('by ID'), so the agent knows exactly what it retrieves. It does not explicitly contrast itself with the sibling 'search_articles', leaving the distinction (fetch-one-by-ID vs. query-many) to inference.

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

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

The phrase 'by ID' implies this is the tool to call when an article ID is already known, in contrast to 'search_articles' which would be used for discovery. However, no explicit when-to-use or when-not-to-use guidance is given, and no sibling is named.

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, and it does disclose the returned payload shape (comments and metadata), which is useful context beyond the schema. However, it says nothing about permission requirements, behavior for a nonexistent or inaccessible ticket, comment volume, or response format, so important behavioral traits remain undisclosed.

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

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

A single front-loaded sentence with no filler; the resource and the payload scope are both stated immediately. Nothing is redundant or padded.

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 two-parameter read tool with full schema coverage, the definition covers the essentials: what it returns and the identifying input. The remaining gap is the absence of any output schema or stated failure behavior, which is a minor omission for a tool of this complexity.

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

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

Schema description coverage is 100%, so both parameters (ticket_id, include_comments) are already fully documented in the schema, and the description adds no format, ID-type, or default-behavior detail beyond it. Baseline 3 applies when 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 states a specific verb (Get) and resource (a specific ticket by ID) plus the payload scope (all comments and metadata), which separates it from search_tickets without naming it. It is clear and unambiguous, but stops short of explicitly differentiating itself from its siblings.

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

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

Usage is implied rather than stated: 'by ID' signals a single-record fetch, which contrasts with the sibling search_* tools, but there is no explicit when-to-use guidance, no stated prerequisites, and no named alternative. An agent can infer the intent, but the definition does not help it choose.

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. 'Get' implies a read-only operation, but it never states pagination behavior, result ordering, or any cap on results even though paging parameters exist. For a list tool with zero annotation coverage this is a real 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?

A single short sentence that front-loads the verb and the filter with no filler. Nothing is wasted and nothing important is buried.

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 read-only list tool with a complete schema but no output schema and no annotations, the description is minimally adequate. It omits pagination/return-shape context that would help an agent call it correctly, but the schema covers the inputs.

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

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

Schema description coverage is 100%, so the tag, page, and per_page parameters are already fully documented including defaults. The description adds nothing beyond that, so the baseline 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?

The description states a specific verb+resource ('Get all tickets') and a filter ('with a specific tag'), so the operation is unambiguous. It does not, however, distinguish itself from the sibling search_tickets, leaving the agent to guess which of the two to prefer.

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 when-to-use guidance and no mention of the obvious alternative search_tickets. The agent gets no basis for choosing this tag-scoped lookup over the broader search sibling.

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 behavioral burden, and it does not say this is a read-only operation, or describe pagination behavior, result caps, or what a result contains. It only restates the search action, leaving the agent to infer everything about side effects and output shape.

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 one-line purpose is front-loaded before the bulleted examples, and every line earns its place. It is slightly padded by three examples that illustrate essentially the same plain-keyword pattern twice.

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 and no output schema, the description should do more work on behavior and result shape, and it should route between this and get_article. It is adequate for a simple paged search but leaves those gaps unfilled.

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, and the examples genuinely add value by demonstrating query syntax including the 'label:feature_name' operator, which is not expressed anywhere in the schema. Page/per_page defaults are already documented in the schema, so the description need not repeat them.

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

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

States a specific verb+resource: searching Zendesk Help Center articles, and clarifies the resource is the knowledge base. This clearly separates it from search_tickets, get_article, and get_tickets_by_tag, so an agent can pick it without opening a 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?

The examples imply how to phrase queries and even show a label: filter, which is useful, but there is no explicit when-to-use/when-not-to-use guidance. Nothing tells the agent when to prefer this over get_article for a known article, or how it relates to search_feature_feedback.

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 exist, so the description carries the full behavioral burden, and it mostly does not. It discloses that results span bug reports, feature requests, feedback, and support questions, but says nothing about result limits, pagination, sorting, or whether include_solved behaves differently for articles vs tickets.

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 core purpose is front-loaded in the first sentence, followed by a scannable bullet list of content types and a single concrete example. Slightly list-heavy but every line earns its place without redundancy.

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

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

All three parameters are documented in the schema and the description conveys scope and matching semantics. For a search tool with no annotations and no output schema, though, the absence of any return-volume, pagination, or ordering information leaves the agent under-informed about what to expect from a call.

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, but the worked example ('collections' will find all tickets and articles mentioning collections) adds genuine semantic meaning: it clarifies that feature_name is a keyword mention match, not an exact taxonomy lookup.

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

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

States a specific verb (Search) and resource (tickets and articles related to a feature), and frames itself as a convenience aggregate. It is distinguishable from siblings like search_tickets and search_articles because it spans both content types, though it never names those 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?

The framing as a 'convenience tool' and the enumeration of content types implies when it is appropriate (broad feature-oriented sweep rather than a targeted ticket/article lookup). However, it never states when to prefer search_tickets or search_articles instead, so routing guidance is only implied.

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 behavioral burden, yet it says nothing about result limits, ordering, rate limits, or what a returned ticket contains. The only behavioral crumbs (page defaults, per_page max 100) live in the schema, not the description.

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 one-line purpose is front-loaded and the syntax reference is organized as scannable examples plus a bullet list. It is a bit long, but each example demonstrates a distinct clause form rather than repeating.

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 query grammar is fully covered, which is the hard part, but with no output schema the description should say something about what comes back (fields, ordering, or result shape). Pagination exists in the schema but is never connected to result 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?

Schema coverage is 100%, so the baseline is 3, but the description substantially enriches the most important parameter by enumerating the supported query prefixes and comparator syntax with worked examples. It does not touch page/per_page, which the schema already documents.

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

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

States a specific verb and resource ('Search Zendesk support tickets') and adds the differentiating detail 'advanced query syntax'. It implicitly separates itself from article/feedback siblings by naming 'tickets', but never explicitly names an alternative, so it stops short of full sibling routing.

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?

Usage is implied by the query examples (filter by status, tag, priority, date, subject), but there is no explicit when-to-use or when-not-to-use guidance. Nothing tells the agent when to prefer get_ticket, get_tickets_by_tag, or search_feature_feedback over this tool.

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