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

No annotations are provided, so the description carries the full behavioral burden. It discloses the output dimensions (provider, chain, symbol breakdowns) which is genuinely useful given there is no output schema, but says nothing about auth requirements, rate limits, or the precise shape of the response. Read-only nature is only implied by 'Identify'/'Returns'.

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?

Four compact clauses: definition, parenthetical disambiguation of the risk concept, return scope, and routing to the alternative. Front-loaded with the core purpose and no filler sentences.

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?

With no output schema and no annotations, the description supplies the essential missing context: what is returned and when to call it versus get_metrics. It stops short of describing the concrete response fields or ordering, but nothing critical for correct invocation is absent.

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 tool takes zero parameters, so the baseline is 4. The description correctly implies there is nothing to configure and adds no misleading parameter hints.

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?

States a specific verb+resource ('Identify oracle coverage gaps and single-provider-risk symbols'), defines the key concept inline (assets served by only one oracle = concentration risk), and tells the agent what it returns (breakdowns by provider, chain, symbol). It explicitly contrasts itself with get_metrics, so an agent can pick it without opening sibling schemas.

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?

Gives an explicit use condition ('Use this when assessing where coverage is thin') and names the alternative with its selecting condition ('For ecosystem scale plus top reputable providers, use get_metrics instead'). This is the when/when-not/alternative pattern in full.

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