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

Annotations already declare readOnlyHint=false, destructiveHint=false, and openWorldHint=false, so the safety profile is largely covered. The description adds that it RETURNS a five-dimension score plus revision advice, which is useful because there is no output schema, but it says nothing about depth, cost/latency, or whether the pasted text is stored. Note the readOnlyHint=false is odd for a pure text-analysis tool, though the description does not actively contradict it.

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 pipe-delimited, front-loaded structure makes the trigger easy to scan, and the RETURNS segment earns its place. The eight-item multilingual ALIASES block is keyword stuffing that consumes a large share of the description without adding invocation guidance.

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?

For a one-parameter tool with no output schema and simple annotations, the description covers trigger and output shape, which is the minimum viable set. It stops short of clarifying scope relative to the many overlapping review siblings or the input assumptions (language, length, discipline) that would let an agent choose confidently.

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?

There is a single parameter with 100% schema description coverage, and the schema already states the ≥100-character minimum, so baseline 3 applies. The description adds no additional meaning about the input beyond what the schema provides.

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 names a specific resource (proposal / grant / protocol) and a specific output set ('scoring, weaknesses and revision advice'), so an agent can tell what it does. The opening segment 'Proposal / grant review / 标书评审' is only a restatement of the title, and nothing distinguishes it from closely related siblings such as deep_peer_review, pre_submission_review, paper_six_agent_review, or nsfc_grant_analysis.

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?

'USE WHEN: the user pastes a proposal or protocol and wants scoring, weaknesses and revision advice' gives a concrete trigger condition tied to user intent and input form. However, it never states when NOT to use it or names the obvious alternative siblings, so routing in a crowded review-tool cluster still requires inference.

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