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

No annotations are provided, so the description carries the full burden of disclosing behavior. It explains the clustering semantics (shared funding source), but does not state whether the tool is read-only, what exact output is returned, or any limitations such as data coverage, latency, or failure modes.

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 with no filler. It front-loads the main action and result, then appends the purpose, which is exactly appropriate for a simple one-parameter tool.

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 low-complexity tool with one parameter and no output schema, the description is largely sufficient: it defines the input, the cluster concept, and the intended use. The only gap is that the exact return shape and edge-case behavior are not described, though the description does indicate the result is a set of addresses.

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%, and the schema already documents the parameter as a 0x-prefixed funder address. The description reinforces the role of the parameter but does not add meaning beyond the schema's own parameter description.

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 states a specific verb ('detect') and a concrete resource: the set of addresses funded by a given funder address, framed as shared-funding-source clustering. It also names the purpose (Sybil/entity identification), which clearly distinguishes it from siblings like query_alerts or get_label.

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?

The description implies a use case through '用于女巫/实体识别' (for Sybil/entity identification), giving some contextual guidance. However, it provides no explicit comparison with alternatives, no when-not-to-use conditions, and no exclusions.

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