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

With no annotations provided, the description carries the full burden. It does add useful behavioral context by stating the data comes from a 'paper trading bot', implying simulation and no real-world trades, and it lists the data categories returned. However, it does not explicitly say the tool is read-only, describe side effects, or disclose data freshness or ordering behavior. It is not misleading, but it is only partially transparent.

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 tight sentence that front-loads the core identity and then lists the main data categories. Every word contributes meaning, with no filler, repetition, or unnecessary detail. It is appropriately concise for the tool's simple parameter surface.

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?

There is no output schema, and the description only gives broad categories rather than the actual shape of returned data. An agent cannot tell what a 'signal' object contains, whether the results are ordered, or how 'strategy performance' is structured. The absence of usage guidance and return-format details makes this incomplete for a tool that must be invoked correctly without further schema support.

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 description coverage is 100%, so the parameters are already documented in the schema. The description adds minor semantic mapping by using 'strategy performance', 'active trades', and 'signal feed' to mirror the view enum values, but it does not add new parameter-level details. Baseline 3 is appropriate given high schema coverage.

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 identifies the resource: prediction market signals from a Polymarket paper trading bot. It lists the three content areas (strategy performance, active trades, signal feed), which maps to the view parameter. It does not use an explicit verb like 'retrieve' or 'list', but the noun phrase is unambiguous and mentions Polymarket, which helps distinguish it from other signal-related siblings.

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?

There is no guidance on when to use this tool versus alternatives such as wave_signal, get_prices, or other market-data tools. No conditions, exclusions, or recommended use cases are stated. The agent must infer usage solely from the data-source description, with no explicit routing.

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