export_study_deck

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 key behavioral traits: it transforms questions into flashcards with specific formatting (front, back, tags), outputs as tab-separated CSV, and explicitly states 'No file is written to disk.' This covers output format and side effects, though it doesn't mention rate limits or authentication needs.

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. It front-loads the core purpose, then details the transformation process, output compatibility, and parameter usage. Every sentence adds value with no redundancy, making it efficient and 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 moderate complexity, no annotations, and an output schema present, the description is complete. It explains what the tool does, how it processes data, output format, parameter usage, and behavioral constraints. With an output schema handling return values, no additional explanation of outputs is needed.

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 input schema has 0% description coverage, so the description must compensate. It adds detailed meaning for the single parameter 'tag_filter': explains it's optional, provides an example ('machine-learning'), and clarifies that leaving it blank exports all questions. This fully documents the parameter beyond the bare schema.

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: 'Export your open questions as a portable study deck (tab-separated CSV).' It specifies the verb 'export' and the resource 'open questions,' and distinguishes it from siblings like 'export_captures' by focusing on study decks with flashcards from journal questions.

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 for when to use this tool: for exporting open questions as study decks, compatible with tools like Anki and Quizlet. It doesn't explicitly mention when not to use it or name alternatives, but the focus on flashcards from journal questions implies it's for study purposes rather than general data export.

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