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

No annotations are provided, so the description carries the full burden, and it delivers strong context: the probabilistic methodology (sampled price paths), the meaning of the p_up statistic, and the p10-p90 return band. The 'Price history only' statement further discloses that catalyst layers are excluded. It falls short of 5 only by omitting minor operational details such as the actual horizon length or sample count.

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 sentences, zero filler. The purpose is front-loaded, the definition of p_up and the return band follows immediately, and the differentiator closes the description. Every clause earns its place.

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 read-only forecast tool with 100% parameter coverage and no output schema, the description covers the essential return semantics (p_up plus p10-p90 band) and the ticker vs. full-board modes. The main gap is the vague 'over the horizon' — the horizon length is never specified — and no mention of what else the response might include, but nothing critical blocks correct invocation.

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% — both ticker ('omit for the full board') and limit ('max rows when no ticker is given') are fully documented in the schema. The description adds marginal context ('whole scored board' clarifies 'full board'), but per the baseline rule, high schema coverage means the schema carries the load, and the description's parametric contribution stays modest.

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 a specific verb+resource (get price forecast, as a probability) and defines the key output metric precisely: 'p_up is the share of sampled price paths closing higher over the horizon, with a p10-p90 return band.' It also differentiates from siblings by stating 'Price history only — independent of the catalyst signal layers,' which positions it against get_ticker_signal and get_thesis without ambiguity.

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 gives a clear usage boundary: this is the price-history-based forecast tool and is explicitly 'independent of the catalyst signal layers,' signaling when not to use it for signal-driven analysis. However, it does not name a specific sibling alternative (e.g., 'use get_ticker_signal for catalyst-based output'), so the when-to-use guidance relies on inference rather than explicit routing.

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