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

With no annotations, the description carries the burden well: it discloses the $0.007 cost, the paused-engine condition, and that every response includes engine_status and engine_paused_since. It does not cover latency, pagination, or data freshness beyond the pause flag, but the critical behavioral caveat is explicit.

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?

Three sentences, each carrying useful information, with the cost and historical-record caveat front-loaded. The leading price tag is useful for a paid tool but slightly delays the purpose statement.

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 historical-data tool with no output schema, the description explains the key return contents and includes the essential engine-status caveat. It is sufficient for correct invocation, though it could say more about response shape or granularity.

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?

This tool takes zero parameters, so the baseline is 4; there is nothing for the description to clarify beyond what the empty schema already conveys.

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 the specific resource and its contents: win rates by regime and pair, discretionary vs grid performance, and lessons from the evolution engine. It also distinguishes itself from live-signal siblings by stating it is the historical record of past trading, so an agent can tell it apart from regime or apex_pulse style 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?

It clearly frames when this is appropriate: historical analysis while engines are paused, not live activity. It does not explicitly name an alternative live tool for current-state questions, but the paused-engine warning gives a strong contextual signal for choosing between historical and live sources.

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