登记老师提供的实验输入

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

The description discloses key behaviors: per-file SHA-256 computation, writing to the evidence list, and the workspace constraint. Since annotations provide no hints (all false), this adds valuable context. However, it doesn't explain what happens on failure or whether re-registering overwrites entries, leaving some transparency gaps.

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 a single, information-dense sentence. It front-loads the primary action and includes necessary constraints without redundancy, earning its place fully.

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?

The presence of an output schema means return values need not be described. The description covers purpose, timing, hashing behavior, evidence writing, and workspace constraint. It lacks session_id semantics and error scenarios, but overall it provides sufficient context for an agent to select and invoke the tool safely.

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 schema description coverage at 0%, the description must compensate. It roughly maps guide_path, template_path, and data_paths to the guide, template, and data, but session_id is completely unexplained. The workspace constraint applies to all paths, adding some meaning, but session_id remains a gap and parameter details are shallow.

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: registering teacher-provided experiment inputs (data, guide, template) before screenshots, computing SHA-256 hashes, and writing them to the evidence list. The verb '登记' (register) combined with the explicit resource and action distinguishes it from sibling tools like register_output and finalize_evidence.

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?

It provides explicit temporal guidance ('在截图前' – before taking screenshots) and a hard precondition ('输入必须位于实验工作区内' – inputs must be inside the experiment workspace). It does not explicitly name alternatives, but the context of registering inputs vs. outputs is clear from the description and tool name.

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