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

Discloses real behavioral traits beyond the annotations: 'No duplicates are created', the automatic kind inference rule, and the entry-form rule (dictionary form in the entry, spoken form in example). It does not say what the call returns or whether existing entries are reported back, which the absence of an output schema makes more relevant.

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?

Front-loads the action and the item shape, and every sentence carries rule content. The single sentence-chain after the JSON example is dense and slightly hard to parse on a first read, but nothing is padding.

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 one-parameter mutation with no output schema, the description covers the field contract, dedup behavior and entry rules well. It stops short of the result shape (created vs skipped) and any permission/auth note, which would close the remaining gap.

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 coverage is 0% and the items array is untyped (additionalProperties: true), so the description carries the full contract: it enumerates term, meaning (with ui_lang sourcing), example, level (A1..C2) and kind (chunk|formulation), plus the fallback rule when kind is omitted. This is exactly the compensation a low-coverage schema requires.

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?

States a specific verb+resource ('Add words and phrases to the vocabulary and to cards') and explains the entry model in detail. It never names the near siblings add_chunk / add_cards, so an agent must still infer which tool to pick when a single chunk is the target.

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?

Gives implicit structural guidance (chunk vs formulation, the >5-word default rule, and a pointer to docs("vocab") for entry rules) but no explicit when-to-use / when-not-to-use guidance relative to add_chunk, add_cards or mark_known.

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