whale-data

Squeeze Score (crowding)

squeeze_score

Read-onlyIdempotent

Fused 0-100 crowding read per pair (funding + long/short accounts + taker imbalance + OI trend) with the overexposed side. Descriptive, not a trade signal. Needs a paid developer plan. Descriptive market data only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`coin`	No	Alias for pair.
`pair`	No	Trading pair, for example ETH/USD. A bare symbol like ETH is read as ETH/USD. Defaults to BTC/USD when omitted. A developer plan is needed for any pair here: without one the call is refused before the pair is even read.

Output Schema

TableJSON Schema

Name	Required	Description
`note`	No	One line saying what the numbers cover, or why there are none. Read it before reporting any zero as a market reading.
`pair`	No	The pair this crowding read describes.
`available`	No	False when this lane could not answer: a producer is dark, the pair sits outside this plan, or the argument named something we do not carry. Absent or true means the numbers are a real reading, not a guess.
`updated_at`	No	When the read was computed.
`access_note`	No	What this connection could not return and what lifts it. Always pass this on to the user: it is the only place that information appears.
`by_exchange`	No	The same read broken out per exchange.
`crowded_side`	No	Which side is overexposed, long or short.
`squeeze_score`	No	Crowding from 0 to 100. Descriptive, not a trade signal.
`long_short_ratio`	No	Long accounts against short accounts.
`taker_buy_sell_ratio`	No	Aggressive buying against aggressive selling.

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds that the tool 'fuses' multiple data sources and reports the overexposed side, and it reiterates the descriptive nature. It also flags the paid plan requirement, which is a behavioral prerequisite. No contradiction 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.

Conciseness4/5

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

The description is short and front-loaded with the primary purpose, followed by caveats. However, 'Descriptive' appears twice ('Descriptive, not a trade signal' and 'Descriptive market data only'), creating slight redundancy. Otherwise it is efficient.

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 and the presence of an output schema, the description covers the key inputs (per pair), the composite nature of the score, and the access prerequisite. It does not need to detail return values since an output schema exists. This is complete for its purpose.

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 detailed descriptions for both coin and pair, including default behavior and developer plan requirement. The main description only mentions 'per pair' and the plan requirement, adding little beyond the schema. A baseline score of 3 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 a fused 0-100 crowding score per pair, listing contributing factors (funding, long/short accounts, taker imbalance, OI trend) and the overexposed side. It also clarifies that it is descriptive, which distinguishes it from signal-oriented tools. This is specific and unambiguous.

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 explicitly says 'not a trade signal' and 'Descriptive market data only', indicating when not to use it for trading decisions. It also notes the paid developer plan prerequisite. However, it does not name alternative tools for comparison, so usage context is clear but lacks explicit exclusions beyond the trading disclaimer.

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

A3.6/5.0

Disambiguation3/5

Many tools share the same broad purpose domains, such as market_digest vs market_overview vs market_snapshot and whale_context vs whale_profile vs whale_flow, making selection genuinely ambiguous for an agent. The long descriptions help separate them, but the sheer number of overlapping 'one-call' market and whale views still invites misselection, and whale_tape is a direct duplicate alias.

Naming Consistency4/5

Names are consistently snake_case and mostly follow a clear domain-prefix pattern: market_*, whale_*, hl_*, defi_*. Minor deviations like liquidations vs market_liquidations, liq_zones, my_access, and the deprecated whale_tape keep it from a perfect score, but the overall convention is predictable and readable.

Tool Count2/5

With 30 tools, the server exceeds the reasonable upper bound and feels heavy even for a broad data domain. Many tools could be consolidated—for instance, several one-call market summary tools and multiple whale-flow variants—without losing capability.

Completeness4/5

The tool set covers an impressively wide range of whale and market data: news, liquidations, funding, DEX activity, Hyperliquid wallets, market scans, history, and plan access. There are minor gaps such as no general price/OHLC history or per-wallet trade history beyond swaps and fills, but agents can work around these using the existing surface.

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