Summarise stored data

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

Beyond the readOnlyHint annotation, the description discloses important behavioral details: counts come from a capped read, and the reply lists exactly what it cannot see. It also mentions that enabling transcript stats parses transcripts and can be slow on big meetings, adding performance 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 concise, two sentences, and front-loads the primary purpose. It avoids unnecessary detail while covering the core functionality, limits, and output nature efficiently.

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 simplicity (3 optional parameters, no output schema), the description sufficiently explains what the tool does, what inputs affect the outcome, and what the reply will contain, including the caveat about the capped read. It is complete enough for an agent to decide when and how to call it.

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 schema descriptions for notes_limit and include_transcript_stats are meaningful, explaining their effect on the results and performance. The main description adds context about the capped read. Although transcriptions_limit lacks an explicit schema description, its purpose is inferable from the overall context of the tool and its similarity to notes_limit.

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 summarises stored data in the OpenWhispr app, enumerating the types (notes, folders, transcriptions, dictionary words) and the dimensions (type, folder, month) along with word/character/audio totals. It distinguishes itself from sibling tools like list_notes and list_folders by focusing on aggregate counts rather than individual items.

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 implies the tool is for obtaining summary statistics, and the sibling tools list individual entities, so the intended use is inferable. However, it does not explicitly name alternatives or provide explicit 'use this when' or 'use that when' guidance, leaving the choice to the reader.

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