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

Annotations already cover readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable context by flagging 'tradeability caveats' for the models, alerting the agent that some models may have limitations. This goes beyond the annotations and does not contradict them.

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 sentence that front-loads the main purpose and lists specific items. It is concise, with no filler, and every word contributes to the meaning. The caveat is integrated naturally without adding bulk.

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?

The description covers the main content: models, themes, and strategy types, and mentions tradeability caveats. It does not elaborate on what 'themes' includes, but given the tool has no parameters and no output schema, the description is reasonably complete for an agent to decide whether to call it. A more explicit explanation of 'themes' would improve completeness.

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 the schema provides no additional meaning. Per the rubric, a baseline of 4 is appropriate for zero-parameter tools. The description does not need to explain parameters that do not exist.

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 states a specific verb 'research' and a clear resource: backtest models and strategy types. It lists concrete examples (aib_sentiment, odiv, oboss; cross_exchange_arb, funding_rate, dex_replay) that distinguish it from siblings like list_backtest_surfaces, which focus on surfaces. No ambiguity remains about what the tool 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?

The description implies this tool is for retrieving backtest model and strategy-type information, but it does not explicitly state when to use it versus alternatives or provide exclusion conditions. For a simple info tool, this is acceptable, but it could have mentioned that it serves as an overview/reference for Backtest Labs capabilities.

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