verify_prep

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

No annotations are provided, so the description carries full burden. It transparently discloses read-only behavior ('只读, 零写库'), validation error codes (VALIDATION, NOT_FOUND), return status levels (PASS/PASS_WITH_WARNINGS/FAIL), course-level aggregation details, and the CLI equivalence. All key behaviors are covered.

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 dense but every sentence adds value. It is front-loaded with the primary use case, then systematically covers safety, parameters, output modes, and equivalence. No redundancy or filler.

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 absence of annotations and output schema, the description provides complete context: usage scenarios, parameter selection rules, error codes, compact vs verbose output shapes, and CLI correspondence. It fully compensates for missing structured metadata.

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 already describes all 3 parameters with 100% coverage, but the description adds critical semantics: the mutual exclusivity rule (both/neither → VALIDATION), the behavior for each value (single-lesson report vs course-level summary), and ordering by lessons.order. This goes well beyond the 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: a final verification step for lesson preparation ('备课收尾必调'), checking cross-item consistency across textbooks, flashcards, exercises, mind maps, and concepts. It distinguishes itself from sibling tools by being read-only and validation-focused, contrasting with the write-oriented siblings.

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?

Explicitly says when to use: before delivery ('交付前跑一遍'). It clarifies the lesson_id vs course_id selection rule and the distinction from write operations ('写入门禁看单发, 本工具看全家福'). This gives clear context and differentiates from alternatives.

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