get_event_reaction

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

Annotations already provide readOnlyHint, openWorldHint, and idempotentHint, lowering the burden. The description adds meaningful behavioral context beyond annotations: it clarifies that results are measurements, not causal proof, and that ratios are expressed as fractions (0.12 means 12%). This helps the agent interpret results 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 front-loaded with the core action and output, then a usage cue, then a critical interpretation caveat and unit convention. Every sentence earns its place, and there is no repetitive or filler content despite covering a fairly rich tool.

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?

Given there is no output schema, the description does a good job enumerating the computed values and their units, so an agent knows what to expect. It also clarifies the non-causal interpretation. Minor gaps like handling of missing sessions or non-trading event dates are not addressed, but the core calling context is complete.

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 four parameters and their meanings. The description reinforces the default windows (1st, 5th, 20th session) and the benchmark concept, but it does not add parameter-specific semantics that are not already present in the input schema.

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 opens with a specific verb and resource: 'Measure how an asset's price moved after a dated event.' It enumerates the exact outputs (returns at 1st/5th/20th session, benchmark return, excess, drift), which clearly differentiates it from siblings like get_price_summary and compare_assets.

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 explicitly says 'Use it for "how did the market react to X" questions,' giving clear context for when to invoke it. It also adds a useful exclusion by stating it measures but does not prove causation Temp, though it does not name alternative tools or when-not conditions explicitly.

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