LiquidVision — Crypto Derivatives Data

get_precedents

Read-onlyIdempotent

[measured] When did the market look like this before, and what did price do next? Scans our hourly archive for hours whose positioning resembled now (OI change 24h within 3 pp, funding APR within 15 points and same sign, long share within 5 pp, liquidation volume within x2.5), one per day, and returns the 24h and 72h price outcome of those look-alikes: count, share that went up, median and quartiles, worst and best, next to the unconditional base rate over the same archive. verdict says whether the sample is big enough to mean anything. Frequencies from our archive (since 2026-09), NOT a forecast. Metered: free key (100/day), Pro/Bot, or x402.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_precedents"
  }
}

Input Schema

Name	Required	Description	Default
`coin`	No	Base asset, e.g. BTC, ETH, SOL (no USDT suffix).	BTC
`api_key`	No	LiquidVision API key (lv_...). Omit when the key is sent as the X-API-Key header on the connection.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 6, 2026

addedInput schema / properties / api_key / description

Added value: +"LiquidVision API key (lv_...). Omit when the key is sent as the X-API-Key header on the connection."

addedInput schema / properties / coin / description

Added value: +"Base asset, e.g. BTC, ETH, SOL (no USDT suffix)."

AddedNov 3, 2026

TDQS

A4.4/5.0

Behavior5/5

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

Goes well past the annotations by disclosing the exact matching tolerances (OI change within 3 pp, funding within 15 points and same sign, long share within 5 pp, liquidation volume within x2.5), the one-per-day deduplication rule, and the sample-size 'verdict' field. It also discloses metering/pricing tiers and archive start date, which the readOnlyHint/idempotentHint annotations cannot convey.

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?

Front-loaded with the core question, then mechanism, then output shape, then caveats and metering — a sensible ordering. The long parenthetical tolerance list is dense but each clause is informative; only minor tightening is possible.

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?

With no output schema, the description must carry the return shape, and it does: count, share that went up, median and quartiles, worst and best, plus the unconditional base rate and the 'verdict' sample-size flag. It also covers archive provenance and billing, leaving nothing essential unstated for a read-only analytical 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% and both parameters (coin, api_key) are already fully described there, so the description carries no burden for parameter meaning. The tolerance thresholds in the description describe matching logic, not parameter semantics, so the baseline 3 applies.

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?

Opens with a concrete question the tool answers, then states the specific mechanism: scanning an hourly archive for hours with similar positioning and returning 24h/72h outcomes. That is far more specific than sibling names like get_positioning_regime or get_market_brief, so an agent can distinguish it without opening the schema.

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 framing ('When did the market look like this before, and what did price do next?') makes the use case clear, and 'NOT a forecast' sets an important boundary on interpretation. It stops short of naming an alternative sibling or an explicit when-not-to-use condition, so it earns a 4 rather than 5.

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

All LiquidVision — Crypto Derivatives Data tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?