query_errorbook

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

Goes well beyond the readOnly/idempotent annotations: no re-OCR, a 12000-byte cap on the JSON summary set that forces continued paging via next_offset even when results are fewer than limit, and the instruction to refresh the first page after mutations during paging. It also warns that summaries may contain hints that must not be shown before independent answering.

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?

Purpose and matching rules are front-loaded, and nearly every clause adds distinct information (byte cap, pagination, verdict-vs-status distinction). It is dense and semicolon-heavy, but not padded.

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?

Even though an output schema exists, the description usefully documents pagination via next_offset and the byte cap that governs return size, plus the important semantic gap between agent_verdict and review_status. An agent has everything needed to call and page this tool correctly.

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?

With 0% schema description coverage the description carries the load and does so well: it explains search matching rules, each filter dimension (review_status, agent_verdict, subject, document_id, knowledge_point), intersection semantics, and null/default meaning. It leaves limit/offset semantics only implicit through the pagination discussion.

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?

Opens with a specific verb+resource ('查当前错题文本') and immediately defines the matching semantics (case-insensitive literal substring, no internal field names/IDs/old history, no wildcard or Anki syntax). This clearly separates it from siblings like export_errorbook and read_review_queue, which serve different purposes.

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 actionable when-to-use guidance: filters intersect, omission means 'all', and practice selection should explicitly pass review_status=include since excluded items are included by default. It does not name a sibling alternative for the export/history cases, so it stops short of a full routing rule.

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