Crypto Data & Market Analysis Agent

get_macro_rates

Read-onlyIdempotent

Live US macro data with the derived signals, not just the raw levels: Fed funds rate, 2Y and 10Y Treasury yields plus the 2s10s YIELD CURVE SPREAD (with its direction — steepening or flattening — and an inverted flag), CPI inflation year-over-year, the broad trade-weighted dollar index (a different index from the ICE dollar index, so read its direction rather than comparing its level), VIX and M2 money supply. Every series carries its previous reading, so direction is available without a second call. The curve slope, not the level of any single yield, is the liquidity and cycle signal: inversion has preceded every US recession, and re-steepening out of an inversion usually marks the start of easing — the moment that matters for risk assets. VIX explains crypto drawdowns that have no crypto-native cause.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`m2`	No
`vix`	No
`ust2y`	No
`cpiYoY`	No
`ust10y`	No
`fedFunds`	No
`dollarIndex`	No
`yieldCurve2s10s`	No	10Y minus 2Y. Inversion has preceded every recent US recession.

TDQS

A4.2/5.0

Behavior4/5

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

Annotations declare readOnly, idempotent, etc., which covers safety. The description adds that every series carries previous reading for direction, and explains the significance of the curve slope and VIX, but doesn't detail computational methods or potential side effects (none expected). No contradiction.

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

Conciseness3/5

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

The description is quite verbose and repetitive (e.g., the 'curve slope' and 'VIX' explanations are repeated). Could be condensed significantly. The structure is a single block, but the redundancy hurts conciseness.

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

Completeness4/5

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

Given the tool's simplicity (no params), the description covers the main outputs and their significance. It explains the derived signals and why they matter, which is sufficient for context. Slight redundancy, but complete.

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

Parameters4/5

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

No parameters exist, so the description's lack of param details is acceptable. But since there are no params, the baseline of 4 is appropriate.

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 the tool provides live US macro data and derived signals (e.g., Fed funds rate, Treasury yields, 2s10s spread, CPI, dollar index, VIX, M2), distinguishing it from other market tools. It is specific and action-oriented.

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

Usage Guidelines4/5

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

The description explains that the tool includes derived signals (spread, inverted flag, direction) and clarifies that it differs from the ICE dollar index, implying when to use it (for macro context). However, it does not explicitly state when not to use other tools, though the contrast with sibling tools is implicit.

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

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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

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