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

Annotations already declare readOnlyHint=true and openWorldHint=false, establishing a safe, offline read. The description adds useful behavioral context by flagging that the results are a 'simulated backtest' rather than real returns, but gives no detail on computation cost, data freshness, or limitations of the simulation.

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?

Two dense sentences that front-load the returned metrics and follow with the mode enumeration; little waste. Slight redundancy ('conviction-conviction-weighted') but overall tight and well ordered.

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?

With no output schema, the burden of describing return values falls on the description, and it delivers by listing the metrics produced. Mode parameter meaning is covered; the only gap is period semantics and the absence of any when-to-use framing, which is minor for this read-only analytical tool.

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 only 33% (just influencerId: 'id from search'), so the description must compensate. It does meaningfully by expanding the opaque mode enum values into semantics (WLO = conviction-weighted, LS = long-short), which the schema only lists as bare codes. The period enum is left unexplained but its values (1W, 1M, YTD) are largely self-evident.

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?

States a specific verb+resource ('an influencer's simulated backtest from their public calls') and enumerates the exact output metrics (return, excess vs SPY, Sharpe, max drawdown, win rate, holdings). This is clearly distinguishable from siblings like rank_influencers, influencer, or stock_opinions without opening a schema.

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 never says when to use this tool versus alternatives such as rank_influencers or the base influencer tool, nor when to prefer one mode over another. The mode glosses describe what the modes are, not when to select them, so selection guidance is essentially absent.

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