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list_templates

Lists available prompt and code templates, with optional filtering by category to locate the right template for your AI development workflow.

Instructions

Lists available prompt and code templates

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoFilter by template category (optional)
Behavior2/5

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

With no annotations provided, the description carries the burden of behavioral disclosure, but it only states the basic action. It does not mention that this is a read-only operation, what the output format is (e.g., names, metadata, content), or any potential side effects. The description adds no safety or behavior context beyond the literal meaning of 'lists'.

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

Conciseness4/5

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

The description is a single concise sentence that is easy to parse and front-loads the key verb and object. It is appropriately brief for a simple tool, though the word 'available' adds little value. It does not waste words, but could have used the spare word budget to clarify the full category set.

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

Completeness2/5

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

The tool has only one optional parameter and no output schema, so the description should compensate by explaining what is returned (e.g., template names, metadata, contents) and explicitly covering all categories from the enum. It fails to mention 'architecture' and 'review' categories and gives no indication of output structure or how to proceed after listing. This is a simple tool, but the description leaves important gaps, especially given no annotations.

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% for the single parameter 'category', including an enum, so the schema already fully documents the parameter. The tool description adds no additional semantic value over the schema; it merely mentions 'prompt and code' while ignoring the other enum values, which is slightly inconsistent. Baseline 3 is appropriate 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.

Purpose4/5

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

The description clearly identifies the action ('Lists') and the resource ('available prompt and code templates'). However, it fails to mention the 'architecture' and 'review' categories present in the schema, making the scope incomplete and slightly misleading. It distinguishes from siblings like list_patterns and list_learnings by focusing on templates, but could be more explicit.

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

Usage Guidelines2/5

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

No guidance is provided about when to use this tool versus alternatives such as render_template or list_patterns. The description only states what it does, leaving the agent to infer usage context. There is no mention of prerequisites, exclusions, or sibling alternatives.

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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