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

Annotations already cover read-only and idempotent behavior, and the description adds valuable context by stating the tool is experimental until accrual gates pass and has no execution authority. It also discloses the weighted-by-depth computation logic and output components, going beyond the structured annotations.

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 dense sentence with no filler. Every clause adds either the computation method, the output components, or an operational caveat, and the title reinforces the purpose without redundancy.

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 zero-parameter diagnostic tool, the description covers purpose, computation logic, output concepts, and trust/safety status. Since no output schema exists, more detail about return shape or units would help, but the essential context for an agent to call and interpret the tool is present.

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 has zero parameters and the schema coverage is 100%, so there are no argument semantics the description needs to clarify. The description accurately focuses on the computation and output context instead.

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 produces a BTC/ETH consensus mark weighted by depth and names additional diagnostics such as blindness gap, concentration, and dislocated venues. This distinguishes it from sibling tools like venue_concentration or depth_episodes, though it lacks an explicit verb such as 'calculates' or 'returns.'

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?

Usage context is implied by the title 'Consensus price when venues disagree' and by the consensus-mark focus, but the description never explicitly says when to use this tool versus alternatives like venue_concentration or depth_episodes. No exclusions or routing guidance is provided.

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