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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the description only needs to add behavioral context. It does so by specifying the markdown return content and the absence of workflow instructions, plus alias-resolution and variant-addendum behavior. This adds useful context without contradicting annotations.

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 front-loaded with the core purpose and the critical 'does NOT return workflow' boundary before any supporting lists. The type list, alias mapping, and variant note are compact and each line provides decision-relevant information, so the length is justified.

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?

There is no output schema, so the description compensates by naming the returned markdown sections and by pointing to the sibling tool for workflow needs. Combined with the schema's coverage of 'context' and 'variant', an agent has enough information to invoke the tool correctly.

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?

Although the schema has 100% coverage, the description carries the real semantic weight: it lists all seven canonical types, the full alias mapping table, and the conditional rule that 'variant' only applies when type is 'quiz' and omitting it means a standard scored quiz. This is substantial added meaning beyond the schema fields.

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 a specific verb and resource ('Retrieve craft knowledge for building a specific form type') and names the exact knowledge areas returned. It also distinguishes itself from clipform_get_workflow by explicitly saying what it does not return, so an agent can tell it apart from its key sibling.

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 gives an explicit exclusion and routing direction: 'Does NOT return a step-by-step build workflow - use clipform_get_workflow for that.' It also enumerates supported types, alias mappings, and the variant condition, giving the agent concrete rules for when and how to call this tool.

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