flashcards_create

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

With no annotations provided, the description carries the full burden. It discloses the user approval requirement via the confirm parameter, which is a key behavioral trait. However, it doesn't cover other aspects like what happens during generation (e.g., creation of new resources, potential side effects, or response format), leaving gaps in transparency.

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 appropriately sized with a brief overview and parameter explanations. However, it's not optimally front-loaded; the key requirement 'Requires confirm=True after user approval' is in the first sentence, but the parameter details follow in a separate 'Args:' section, which slightly reduces clarity. Every sentence adds value, but the structure could be more streamlined.

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 moderate complexity (4 parameters, 1 required), no annotations, and an output schema present, the description is fairly complete. It covers the purpose, usage context, and parameter semantics adequately. The output schema handles return values, so the description doesn't need to explain them. However, it could benefit from more behavioral details like error handling or generation specifics.

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 must compensate. It adds meaningful semantics for all four parameters: notebook_id as 'Notebook UUID', source_ids as 'Source IDs (default: all)', difficulty with values 'easy|medium|hard', and confirm as 'Must be True after user approval'. This significantly enhances understanding beyond the bare schema, though it could provide more detail on format or constraints.

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 verb 'Generate' and resource 'flashcards', making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'quiz_create' or 'mind_map_create' that might also generate educational content, so it doesn't reach the highest score.

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 provides clear context with 'Requires confirm=True after user approval', indicating when to use this tool (after user approval). However, it doesn't specify when NOT to use it or mention alternatives among the sibling tools, preventing a perfect score.

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