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

Annotations already establish read-only, idempotent, non-destructive behavior; the description adds domain behavior by stating which forensic signals it computes and what question it answers. It does not discuss data freshness, sourcing, or limits, preventing a 5.

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?

Two sentences, front-loaded with the forensic signals and ending with the decision it supports. There is no 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?

An output schema exists and annotations cover the safety profile, so return values and read-only semantics need not be in prose. However, for a tool with two undocumented inputs, the description is not complete enough to tell an agent how to configure `risk` and `limit`.

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 0%, and the description never explains the `risk` or `limit` parameters. The phrase 'risk flags' refers to an output metric, not the input filter, so the description does not compensate for the undocumented 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 names a specific domain and concrete outputs (reviewer concentration, ghost-reviewer ratio, burst detection, risk flags) and frames the purpose as distinguishing earned from manufactured reputation. It does not explicitly distinguish itself from nearby tools such as get_trust_forensics or get_solana_trust_summary, so it is clear but not fully differentiated.

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 a clear use case: checking whether a Solana agent's reputation is earned or manufactured. It lacks when-not guidance and does not name alternatives among the many trust/reputation siblings, so it provides context but no exclusions.

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