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

Annotations are all false (not read-only, not destructive), so the description carries the disclosure burden and adds real value beyond them: the cost behavior ('for free (no credits)'), deduplication behavior ('Repeated fronts are dropped and reported as skipped'), and the card-orientation/swapping rule when the learning language is ambiguous. It does not fully cover side effects such as whether an existing deck with the same name is overwritten, which keeps it from a 5.

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 purpose and cost are front-loaded in the first sentence, and every subsequent sentence contributes distinct information: usage context, card orientation, dedup behavior, and sibling routing. It is slightly long at six sentences, with minor redundancy between 'user provided or that you wrote together' and the word-list/table examples, but no wasted sentences.

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?

For a 6-parameter mutation tool with no output schema, the description covers the essentials: purpose, cost, input formats, card directionality, dedup behavior, and alternative tools. The main gap is that it doesn't describe the response format beyond 'reported as skipped' — with no output schema, some return-value guidance would fully close the loop.

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 83% (above the 80% baseline of 3), and the parameter descriptions already document that front is in learningLanguage and back is the translation. The description adds meaning beyond the schema by explaining how to resolve ambiguity ('ask when that is unclear, and swap each pair so the front is in learningLanguage'), which clarifies the relationship between the language parameters and the cards array.

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 first sentence states a specific verb and resource ('Saves flashcards ... as a deck in the user's NextLang account') and adds the cost qualifier 'for free (no credits)'. It also differentiates from siblings by explicitly naming generate_deck and get_deck_file as the alternatives for other situations.

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 gives explicit when-to-use guidance: 'Use it to turn a word list, a table or an export the user pasted into a deck.' It also states exclusions and routing: 'For an .apkg (Anki) or .mochi (Mochi) file, call get_deck_file next; for Quizlet and Brainscape, give the deck link' and 'use generate_deck instead' for topic-written cards. Nothing is left to inference.

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