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

The annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false. The description adds genuinely useful context beyond those: it discloses what is returned and that the result comes from a real algorithm engine rather than LLM generation, which the agent could not know otherwise. It still says nothing about where the user's own corpus comes from or what happens when no prior articles exist, so it is value-adding but not rich.

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 compact and front-loads the purpose in a bracketed label, followed by the trigger and the return value. It is terse rather than padded, though the parenthetical engine note slightly interrupts the flow.

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 two-parameter, non-destructive tool with a fully described schema, the description covers purpose, trigger, and return payload, which is enough to call it correctly. The residual gap is the provenance of the comparison corpus, which matters for interpreting results but is not required to invoke the tool.

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?

Schema description coverage is 100%, so both `text` and `top_n` are already documented in the schema, and the description adds no syntax, length limits, or default for `top_n`. Baseline 3 applies since the schema carries parameter meaning.

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 verb+resource: comparing a piece of text against the user's own previously written articles to measure textual overlap (查重), and states the return payload (overlap score plus similar literature). It is distinguishable from sibling literature tools like act_lit_search or act_lit_verify_citations, though it does not explicitly name them as alternatives.

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 gives an implied trigger — 'when the user asks whether this text overlaps with my own earlier articles' — which is a usable situation cue. However, it gives no explicit when-not guidance and does not route the agent to or away from the sibling literature-search/verification tools, leaving selection to inference.

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