Crypto Data & Market Analysis Agent

get_implied_volatility

Read-onlyIdempotent

How far the market EXPECTS price to move, priced off options (the DVOL index). Every other derivatives tool here describes how the market is POSITIONED; this one prices how expensive protection is. Returns the current 30-day implied volatility, annualized, in PERCENT (34.95 means 34.95%), together with its min, median, max and PERCENTILE over the window — an IV of 35% says nothing alone, but at the 5th percentile of the last month it says optionality is cheap and the market is complacent. Also returns the derived expected move (plus or minus percent over 1, 7 and 30 days), which scales with the square root of time, not linearly: dividing annualized IV by 365 instead of by the root understates a one-day move roughly nineteenfold. Distinct from the VIX reported by get_macro_rates, which is US equity volatility, not crypto. Published for BTC and ETH only; any other coin comes back under "unavailable" rather than failing the request.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`coins`	No	Coins, e.g. ["BTC","ETH"]. Defaults to both. Only BTC and ETH have a published index.
`windowDays`	No	How many days the percentile distribution covers. Defaults to 30, maximum 365.

Output Schema

TableJSON Schema

Name	Required	Description
`coins`	Yes
`windowDays`	Yes
`unavailable`	Yes	Requested coins with no published volatility index. Never silently dropped.

TDQS

A4.7/5.0

Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true. The description adds significant behavioral context: return format (annualized IV in PERCENT, plus min/median/max/percentile), interpretation guidance (IV alone is meaningless without percentile), derivation of expected moves with time scaling warning, and error behavior for unsupported coins. No contradictions with annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured: core purpose first, then differentiation from siblings, then detailed output explanation with interpretation, and finally an important mathematical warning about time scaling. Every sentence adds value without redundancy. It is informative yet concisely worded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, presence of an output schema, and rich annotations, the description is remarkably complete. It covers purpose, usage context, output interpretation, edge cases (unavailable coins), and a subtle mathematical pitfall. The agent has enough context to correctly invoke and interpret the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with both parameters already described in the input schema (coins: defaults, only BTC/ETH supported; windowDays: default 30, max 365). The description repeats these details but adds no new parameter semantics beyond what the schema already provides. Baseline of 3 is appropriate because the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns options-implied volatility (DVOL index) for BTC/ETH, with a specific verb and resource. It distinguishes itself from sibling tools by noting that other derivatives tools describe positioning, while this one prices protection cost. Also explicitly distinguishes from get_macro_rates (US equity volatility).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit guidance on when to use this tool: to assess how expensive protection is (implied volatility), contrasting with positioning tools. It explicitly names the sibling get_macro_rates as an alternative for US equity volatility. It limits usage to BTC and ETH and explains behavior for other coins.

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

All Crypto Data & Market Analysis Agent tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.4/5.0

Disambiguation5/5

Each tool targets a distinct data domain—network health, market prices, news, DeFi, derivatives per-venue vs aggregate, economic calendar, ETH address, whale flows, execution cost, sentiment, implied volatility, macro rates, market brief, dominance, history, and traditional market quotes. The only similar pair (get_derivatives vs get_derivatives_aggregate) is clearly differentiated by level of detail, so there is no real ambiguity.

Naming Consistency5/5

All tools follow the get_<domain> pattern with descriptive noun phrases (e.g., get_btc_network, get_eth_whale_flows, get_market_brief). No mixed verb styles or casing conventions appear, making the naming fully predictable and consistent.

Tool Count4/5

At 17 tools, the surface is slightly above the ideal 3-15 range, but the breadth of the domain—spot, derivatives, on-chain, macro, sentiment, and execution—justifies each tool. It's borderline but each tool earns its place in a comprehensive market analysis agent.

Completeness5/5

The toolset covers nearly every major facet of crypto market analysis: prices, history, dominance, derivatives, on-chain activity, DeFi, macro, economic calendar, sentiment, implied volatility, execution cost, and a composite brief. Minor gaps like historical OHLCV or multi-chain on-chain analytics are not critical given the agent's stated focus.

Resources

Need Help?