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

Beyond the readOnlyHint and openWorldHint annotations, the description reveals substantial behavioral detail: the report includes N, a Wilson 95% confidence interval, minimum-sample guards, a first-half/second-half stability split, per-year counts, and a disclaimer. It also clarifies that results are historical conditional frequencies, not predictions. This is precisely the kind of context agents need to interpret outputs correctly.

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 dense but purposeful: it opens with the core result, then lists the honesty-envelope components in a compact sequence, then adds the crucial historical-not-predictive qualifier. No sentence is wasted, though the length is on the high side; a slightly tighter grouping of output components would make it ideal.

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 present, the description carries the burden of explaining what the tool returns, and it does so thoroughly: the probability estimate, confidence interval, sample-size guards, stability split, yearly counts, value distribution, disclaimer, and a clear caveat about historical frequency. Together with the schema's fully documented parameters, an agent has enough information to select and invoke the tool correctly.

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 schema already documents all three parameters, including the detailed context-parameter instructions. The description adds only light semantic help by mentioning that preset ids come from edge_presets and symbols from edge_symbols, which the schema also already states. This matches the baseline 3 for fully schema-documented parameters.

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 pair ('precomputed session-statistics result') and defines the exact semantic content: P(outcome | conditions) for a preset on a hosted symbol. It also distinguishes the tool from siblings by tying it to edge_presets and edge_symbols, making it clear this is the report lookup tool rather than a journal, library, propfirm, or tracker tool.

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 clearly situates the tool as a historical-frequency source and explicitly warns 'not predictions,' which helps an agent avoid misusing it for forecasting. It also tells the agent where to get required inputs ('Preset ids come from edge_presets; symbols from edge_symbols'). However, it does not explicitly state when to prefer this tool over sibling analytics tools, such as trackers_query or propfirms_simulate, so it stops short of a full when/when-not guide.

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