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

No annotations are provided, and the description carries full burden. It only states the action without disclosing side effects, required permissions, return behavior, or validation rules. This is a significant 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 brief, front-loaded with the purpose, and includes a structured Args list. Every part earns its place without unnecessary fluff.

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

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

The description covers the purpose and parameters adequately, but without an output schema, it does not mention what the tool returns (e.g., ticket ID) or any post-creation behavior. This leaves a completeness gap.

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

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

Schema description coverage is 0%, but the description fully compensates with an Args block that explains every parameter, including priority values. This adds clear meaning beyond the bare schema types.

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 'Create a new customer support ticket' with a specific verb and resource. It distinguishes from sibling tools (get_ticket, search_tickets, update_ticket) by focusing on creation.

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

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

The description clearly indicates its purpose, implying when to use it (creating tickets) versus alternatives (getting, searching, updating). It lacks explicit exclusions or when-not guidance, but the context is clear from the verb.

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?

Without annotations, the description carries full responsibility for behavioral disclosure. 'Retrieve' implies a read-only operation and no side effects, but it does not mention output format, error behavior, or permissions. Minimal behavioral context is provided beyond the tool 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 extremely concise, using two short sentences and a simple Args section. Every word adds value, and there is no filler 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?

Given the tool's simplicity (one parameter, no output schema, no annotations), the description is nearly complete. However, it lacks guidance on when to use this tool versus search_tickets and does not describe the return value, leaving minor gaps for the 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?

Schema description coverage is 0%, but the description only restates the parameter as 'Numeric ID of the support ticket,' which essentially repeats the schema's integer type and title. It adds little meaning beyond what the schema already provides and does not clarify constraints or format.

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 ('Retrieve') and the resource ('a customer support ticket') with a specific identifier (ticket ID). It is distinct from sibling tools that create, search, or update tickets, making the purpose immediately clear.

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 ticket ID' implies this tool is used when a specific ticket ID is known, but it does not explicitly mention alternatives like search_tickets for finding tickets without an ID. No exclusions or comparisons are provided, so usage guidance remains 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?

With no annotations provided, the description must fully disclose behavior. It only states 'Search' and lists filter options; it does not mention whether filters combine with AND/OR, what the default behavior is when no filters are given, whether results are paginated or ordered, or what the response structure looks like. The read-only nature is implied but not explicitly confirmed.

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

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

The description is concise and well-structured: a one-line purpose statement followed by a clean parameter list. Every sentence is informative, with no filler or redundant elaboration.

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 needs to explain return behavior and edge cases. It covers the core search functionality and all parameters, but omits details such as whether an empty filter list returns all tickets, how filters combine, response format (list vs objects), and any pagination/limits. These are notable gaps for autonomous execution.

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 0%, so the description compensates by fully documenting all four parameters in the Args section. It explains that keyword searches subject/description/customer name, customer_email matches exactly, and provides the accepted value sets for status and priority, adding significant meaning beyond the schema's bare type definitions.

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

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

The description opens with 'Search customer support tickets.', which clearly states the action (search) and resource (tickets). The subsequent list of search dimensions (keyword, customer_email, status, priority) further clarifies its scope and differentiates it from the sibling create/get/update tools.

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

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

The description explicitly says 'You can search using a keyword, customer email, ticket status, or ticket priority.', giving clear context for when this tool is appropriate. It does not, however, explicitly contrast with get_ticket for single-ticket retrieval or mention exclusions, but the intended use case is unambiguous.

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 discloses updatable fields and valid values for status and priority, but does not specify whether omitted fields remain unchanged (partial update), the return value, or required permissions. These are notable gaps 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 concise: a one-sentence purpose followed by an Args list. Each line provides necessary information without redundancy or fluff, and the structure is easy to scan.

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

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

For a 4-parameter mutation tool with no annotations and no output schema, the description is functional but incomplete. It lacks explicit statement about partial update behavior, error handling, or response contents. Sibling tools are not referenced. Overall adequate with clear 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?

Schema coverage is 0%, so the description must compensate. It documents all four parameters with meaningful semantics: ticket_id as the ID, status and priority with enumerated valid values, and description as the new text. This significantly exceeds the schema's simple string definitions.

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

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

The description states 'Update an existing customer support ticket' with a clear verb and resource, and the scope is specific to updating, making it distinct from sibling tools like create_ticket, get_ticket, and search_tickets.

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 when to use the tool—when an existing ticket needs modification—but doesn't explicitly mention when not to use it or name alternatives. The context is clear enough for a simple update tool, but it lacks explicit exclusions or alternative references.

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