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walletap

@walletap/mcp-server

Official
by walletap

list_templates

Read-only

List pass templates owned by your account with cursor pagination. Get a paginated list with has_more, next_cursor, and total_count.

Instructions

List pass templates owned by this account, cursor-paginated. Returns { object: 'list', data, has_more, next_cursor, total_count }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (default 15, max 100).
startingAfterNoCursor — pass `next_cursor` from the previous response.
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description does not contradict it. The description adds valuable behavioral context beyond the annotation: it mentions cursor-pagination and the exact return object structure, which are not covered by annotations. It also specifies 'owned by this account,' clarifying scope. This is meaningful transparency for a read-only operation.

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

Conciseness5/5

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

The description is a single, well-structured sentence that front-loads the core action ('List pass templates') followed by scope, pagination, and return format. Every phrase earns its place: no filler, no repetition. It is concise yet informative, ideal for quick agent comprehension.

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

Completeness4/5

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

For a simple read-only list tool with two optional parameters, the description covers the essential operational context: scope, pagination behavior, and return shape. It does not explain error handling or security requirements, but those are likely implicit for an API tool and are not expected in a brief description. Given no output schema exists, providing the return structure explicitly increases completeness. The description is sufficient for an agent to call the tool correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so both parameters (limit and startingAfter) are fully documented in the schema. The description does not add any parameter-specific meaning beyond what the schema already provides, and it only references the return format, not the parameters. With high schema coverage, the baseline is 3, and the description adds no param semantics, so a 3 is appropriate.

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

Purpose5/5

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

The description states a specific verb (List) and resource (pass templates owned by this account), which clearly identifies the tool's function. It also mentions cursor-pagination, adding scope and pagination behavior. The purpose is unambiguous and distinguishes it from sibling tools like get_template (single retrieval) or list_passes (different resource).

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

Usage Guidelines3/5

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

The description implies usage (use this to list account-owned templates) but does not explicitly state when to use it over alternatives, nor does it mention exclusions or prerequisites. It does not reference sibling tools like get_template or create_template, so an agent lacking prior knowledge might not know when this is the appropriate choice. However, the purpose is clear enough that usage can be inferred.

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

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