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

With no annotations, the description carries the full burden and does substantial work: it discloses the data source, the pricing model (Black-76 forward deltas from Deribit mark IVs), the interpolation convention (at each expiry's forward), the coverage gap (no DVOL for SOL), and the commercial behavior (costs $0.005 USDC per call, not charged on failure). It stops short of stating latency, freshness, or rate limits, which for a paid external-data fetch would be the remaining behavioral risks.

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?

Purpose and source are front-loaded in the opening clause, followed by the field enumeration and then short operational sentences on failure and cost. It is dense but every clause adds a distinct fact; the only mild bloat is the long output enumeration, which is justified by the absence of an output schema.

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?

There is no output schema, so the description compensates by enumerating the returned fields, and it also covers cost, charge-on-failure, and per-asset coverage limits. Given a two-parameter, no-annotation tool with a rich return payload, an agent has everything needed to decide to call it and interpret the result.

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% and both parameters (currency with its default and allowed values, maxExpiries with range 1-30 and default) are fully documented in the schema, so the baseline is 3. The description adds one useful semantic fact not in the schema — that SOL has no DVOL series — but says nothing extra about how maxExpiries ordering interacts with the returned term structure beyond what the schema already says.

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?

Names a specific instrument (option-implied volatility) and a specific source (Deribit public data) for a specific asset set (BTC, ETH, SOL), then enumerates exactly the quantities produced (term structure, 25-delta IV, risk reversal, butterfly, OI/volume ratios, DVOL). This is clearly distinguishable from siblings like crypto_price, perp_market_overview, open_interest_change or funding_rate_arbitrage because it is explicitly options-implied data rather than spot, perp or aggregate OI.

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?

Usage is only implied by the content: an agent can infer this is the tool for option skew/term-structure questions. There is no explicit when-to-use statement, no exclusions, and no named alternative for cases where spot or perp volatility is wanted instead. The failure condition ('Fails ... if Deribit's option data is unavailable') is a runtime caveat, not selection guidance.

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