get_deck_stats

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool returns a dictionary with specific counts (new_count, learn_count, review_count), which adds value beyond the input schema. However, it lacks details on error handling (e.g., if deck doesn't exist), performance (e.g., speed, rate limits), or side effects (e.g., read-only nature implied but not stated). The description doesn't contradict annotations, but it's incomplete for a tool with no annotation coverage.

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 well-structured and appropriately sized, with a clear purpose statement followed by Args and Returns sections. Every sentence earns its place by providing essential information without redundancy. It's front-loaded with the main function and efficiently details inputs and outputs, making it easy to parse.

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 low complexity (1 parameter, no nested objects) and the presence of an output schema (implied by 'Returns' details), the description is mostly complete. It covers purpose, parameter semantics, and return values adequately. However, with no annotations, it could benefit from more behavioral context (e.g., read-only confirmation, error cases). The output schema reduces the need for detailed return explanations, but gaps in usage guidelines and transparency slightly limit completeness.

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?

The description adds meaningful context for the single parameter 'deck_name' by specifying it as 'Name of the deck to get stats for', which clarifies its purpose beyond the schema's basic type and default. With 0% schema description coverage and only one parameter, this compensation is effective, though it could note the default value 'Default' from the schema. The baseline would be 3 for high schema coverage, but here the description enhances understanding significantly.

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 tool's purpose with a specific verb ('Get statistics') and resource ('for a deck'), including the key metric 'due cards count'. It distinguishes itself from siblings like 'list_decks' or 'search_cards' by focusing on statistical data rather than listing or searching. However, it doesn't explicitly differentiate from all siblings, such as how it relates to 'anki_connection_status' in terms of data retrieval.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., deck must exist), compare to siblings like 'list_decks' for deck existence checks, or specify contexts (e.g., for review planning vs. general stats). Usage is implied only by the purpose, with no explicit when/when-not statements.

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