Falcon Structures

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

With no annotations, the description carries the full behavioral burden. It discloses that the tool is free and names the volatility data sources (Deribit DVOL), but it does not mention authentication needs, rate limits, caching, or error behavior. These gaps are meaningful but not severe for a simple read-only market data query.

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 a single efficient sentence with no wasted text. It front-loads the free-tier note and then lists the key data points and supported underlyings, making it easy to scan.

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 absence of an output schema and annotations, the description should do more to explain the return format, units, and response structure. It adequately describes what metrics are returned and for which assets, but leaves output shape and operational details unspecified.

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 must compensate for the single required parameter. It does so by explicitly stating the accepted values 'BTC, ETH or SOL', which clarifies the underlying enum and ties the parameter to the asset being queried.

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 clearly identifies the tool's output: live spot, Deribit implied volatility (DVOL), and 30-day realized volatility for BTC, ETH, or SOL. It lacks an explicit verb and does not distinguish this snapshot from siblings like price_note or preview_note, but the resource set is specific enough for an agent to understand the tool's function.

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?

There is no guidance on when to use this tool versus the sibling tools price_note or preview_note. The word 'Free' hints at a pricing tier but does not specify conditions, alternatives, or exclusions for invocation.

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

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

With no annotations, the description carries the full burden. It does disclose useful behavioral context: the quote is free and indicative, and coupon/participation is rounded to 0.5%. However, it does not clarify side effects, permissions, or whether the operation is strictly read-only.

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 a single compact sentence fragment that front-loads the quote type and then lists the returned computations. It is efficient and has no wasted words, though its terseness leaves some contextual gaps.

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?

The description gives a reasonable summary of outputs for a tool without an output schema, and the termSheet schema covers the only input. Still, for a structured-product pricing preview, it omits important context such as assumptions, limitations, or when to prefer this over price_note.

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 coverage is 100%, and the single termSheet parameter is thoroughly documented in the schema with a nested example. The description adds no parameter-level detail, which is acceptable given the high schema coverage, so the baseline 3 applies.

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 clearly states that this is a free indicative quote and lists the specific outputs: fair coupon/participation rounded to 0.5%, probabilities, and payoff diagram. This is more specific than restating the tool name, though it does not explicitly distinguish the tool from sibling price_note.

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?

There is no explicit guidance on when to use preview_note versus market_snapshot or price_note. The word 'Free' hints at a preview or indicative use case, but no alternatives or exclusions are stated.

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

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

With no annotations, the description carries the full burden and does well: it discloses Monte Carlo pricing on live Deribit implied vol, the output bundle, a free preview, and the $0.02 USDC x402 payment path. It still does not cover failure modes, rate limits, or exact preview behavior.

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 purpose and main outputs, and most sentences earn their place. The only clear waste is the repeated pricing statement: 'Free preview; full quote $0.02 USDC...' followed by 'Costs $0.02 USDC (x402).'

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 complex pricing tool with no output schema and a nested term-sheet parameter, the description lists the key return components and points to the term-sheet schema. It leaves some operational details sparse around the x402 payment and preview flow, but is broadly complete enough to call the 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 coverage is 100%, and the schema itself provides a detailed term-sheet example plus a reference to `/schema/term-sheet.json`, so the schema does the heavy lifting. The description adds product-type context but no additional parameter syntax or constraints beyond what the schema provides.

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 gives a precise verb+resource (structured-note pricing for crypto) and enumerates supported products, underlyings, and outputs. It does not explicitly name or distinguish itself from the sibling tools `preview_note` and `market_snapshot`, though the paid full-quote scope is clear.

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 tells the agent to send a JSON term sheet and mentions free preview versus full quote, implying when the tool is used. However, it does not explicitly name alternatives such as `preview_note` or state when to use this tool instead of a preview or market snapshot.

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