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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds valuable behavioral context: the output is an 'opaque PNG' (not interactive), it can use the SYNTH sample chain without user data, and it explicitly warns against starting a localhost dashboard. This goes beyond the annotations and helps the agent understand the tool's side effects and limitations.

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 three sentences, each earning its place: the first states the core function, the second explains data source options, and the third gives an explicit exclusion. It is front-loaded with the most important information and has no fluff.

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 the tool's complexity (10 parameters, 0 required) and the presence of an output schema, the description covers the key decision points: what the tool produces, when user data is needed, and what not to do. It doesn't explain the meaning of all parameters, but the output schema and parameter names provide some structure. The description is complete enough for an agent to invoke the tool correctly in most cases.

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 0%, so the description carries the burden for parameter semantics. The description mentions 'SYNTH sample chain' and 'user-supplied chain data', which maps to the 'symbol' and 'source_data'/'source_text' parameters, but it doesn't explain the meaning of 'rate', 'expiry', 'dividend_yield', 'rights_confirmed', or 'strategy' beyond what the schema provides. The description adds some context but doesn't fully compensate for the 0% coverage.

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 ('Show') and resource ('option-strategy payoff as an opaque PNG in the conversation'), which clearly identifies the tool's core function. It also distinguishes itself from a localhost dashboard by explicitly saying 'Do not start a localhost dashboard.' However, it doesn't explicitly name a sibling tool to differentiate from, though the mention of 'engine playbook' and 'SYNTH sample chain' hints at the context.

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 provides clear context on when to use the tool: it can build any structure from the engine playbook on the SYNTH sample chain, and a market ticker requires user-supplied chain data. It also gives an explicit exclusion: 'Do not start a localhost dashboard.' It doesn't explicitly name alternative sibling tools, but the guidance is sufficient for an agent to decide when this tool is appropriate.

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