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

With no annotations, the description carries the full burden and discloses key behaviors: it aggregates multiple sources, has a `degraded`/`missing_layers` contract (partial data possible), and has a cache TTL of 180s. It doesn't detail auth/rate limits, but for a read-only aggregation this is reasonable. The `missing_layers` contract and cache behavior add meaningful transparency beyond the schema.

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 sentences, dense with information: aggregation purpose, use-case trigger, efficiency benefit, error contract, and cache TTL. The most critical details are front-loaded (title/purpose first), and every sentence earns its place with no 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?

Given the tool's moderate complexity (2 params, no output schema), the description explains what data it aggregates, when to use it, what failure states to expect (`degraded`/`missing_layers`), and caching semantics. It doesn't describe the return structure, but the absence of an output schema and the explicit contract reference make this acceptable. A fuller description of the response format would earn a 5.

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 coverage is 50% (only `ticker` has a description, which is minimal). The description adds context for `cache_max_age_s` by mentioning 'Cache TTL 180s', hinting at cache-control semantics, but does not explicitly explain the parameter's purpose or effect. It partially compensates for the schema gap, but leaves interpretation to the agent.

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?

Description states exactly what the tool does: it aggregates smart-money data for one ticker by collapsing 7 specific data sources into a single call. The verb 'aggregates' plus the resource ('smart-money ... for one ticker') and the explicit list of underlying tools clearly distinguish it from individual data-source tools and sibling tools like ticker_full or ticker_transparency.

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?

Provides explicit guidance on when to use: 'Use when Brain's verdict needs positioning context' with concrete example questions. It also names the alternatives (the 7 individual tools) and highlights efficiency ('Saves 6 HTTP calls per verdict'), implying when to prefer the composite over individual calls. This covers when/when-not/alternatives well.

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