Consensus price when venues disagree

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

Annotations already declare readOnlyHint and idempotentHint, so the safety profile is covered. The description goes further by revealing the weighting methodology, the blindness gap concept, depth concentration metrics, dislocated venue names, and the experimental status with payload notification. This is valuable behavioral context beyond any structured field.

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 dense but every sentence earns its place: definition, formula, exclusions, key outputs, use cases, experimental caveat, and disclaimer. It front-loads the core meaning and then layers supporting details without repetition or 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?

Despite having no output schema, the description enumerates the key return elements: consensus mark, blindness gap, depth concentration, dislocated venues, and experimental payload flag. For a zero-parameter tool, this provides a complete picture of what to expect and how to interpret the result.

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, so there is no parameter ambiguity to resolve. The schema is empty with 100% coverage, so the description does not need to compensate for undocumented inputs. The baseline for zero-parameter tools is 4, and the description adds no conflicting or confusing parameter-related information.

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 verb and resource: computing a cross-venue consensus mark for BTC and ETH. It clearly distinguishes itself from a simple median or single-venue price by specifying the exact weighting formula and explicitly saying what it is NOT. This makes the tool's purpose unmistakable even among sibling tools.

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 gives concrete use cases: 'what is BTC/ETH actually worth right now', 'is an exchange dislocated', and 'before trusting any single venue's price'. It also warns that the tool is experimental until accrual gates pass. However, it does not explicitly name when to avoid this tool or point to a sibling alternative, though the use cases are clear enough.

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