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

With no annotations provided, the description carries the burden of behavioral disclosure. It covers the read-only nature ('Public read'), empty aggregate return (`total: 0` and `signal: none`), and the derivation rules for `signal`. It could be more explicit about the response shape (e.g., whether a `score` field is always present), but covers key behaviors well.

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 tightly structured in three short segments: purpose, empty aggregate edge case, and signal derivation logic. Every sentence adds value with no filler or repetition. It's front-loaded with the core purpose.

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 simple one-parameter read tool with no output schema, the description explains the main return value (`total` and `signal`) and the signal derivation thresholds. It doesn't explicitly describe the full response structure (e.g., whether a `score` field is present), but it's reasonably complete for the tool's simplicity.

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?

The schema already provides 100% coverage of the `node` parameter with a clear description ('ip, domain, asn, or entity slug.'). The tool description doesn't add further parameter-specific semantics beyond contextualizing node as the subject of the outcome aggregate, so baseline 3 is appropriate.

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: 'Public read of the crowd-sourced outcome aggregate for a node — how callers reported their real-world results after acting on its verdict.' It uses a specific verb ('read') and resource (outcome aggregate), and explicitly distinguishes it from a trust verdict, differentiating it from sibling tools like explain_verdict or verdict_lookup.

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 provides context about when to use it: it's an advisory signal on real-world outcomes, not a trust verdict. It also explains empty aggregate behavior. However, it doesn't explicitly name alternative tools or say 'use this instead of X', so it stops short of full usage guidance.

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