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BitCLI — Crypto Futures & Order Flow

by io.bitcli.mcp
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get_market_snapshot

BEHAVIOR & SIDE EFFECTS: Safe, idempotent, read-only operation. Zero side effects. Fetches a pre-computed market-wide anomaly snapshot directly from in-memory Redis cache (data latency <1s). Rate limits: Public Alpha tier (unrestricted).

WHEN TO USE: Use this as the FIRST exploratory step in your workflow to scan all 1,650+ perpetual contracts simultaneously and identify top statistical outliers (whale volume, funding extremes, volatility).

WHEN NOT TO USE: Do not use this tool to analyze a single specific coin in depth or fetch indicator history (use get_ta_consensus instead).

FAILURE MODES: If the market is completely flat or cache is refreshing, returns a valid array of top coins by 24h volume. Output length is strictly bounded by the limit parameter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of coins to return (allowed range: 1 to 20, default: 10).
sort_byYesAnomaly screening criteria: 'rvol_5m' (Whale volume bursts vs SMA20), 'funding_rate' (Carry cost & squeeze traps), 'oi_change_1h' (Aggressive leverage buildup), 'natr_1h' (Normalized ATR volatility).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / properties / limit / description
      Previous value: -"Maximum number of coins to return (1-20)."New value: +"Maximum number of coins to return (allowed range: 1 to 20, default: 10)."
    • changedInput schema / properties / sort_by / description
      Previous value: -"Anomaly sorting metric: 'rvol_5m' (Whale volume spikes), 'funding_rate' (Carry squeezes), 'oi_change_1h' (Leverage inflow), 'natr_1h' (Volatility)."New value: +"Anomaly screening criteria: 'rvol_5m' (Whale volume bursts vs SMA20), 'funding_rate' (Carry cost & squeeze traps), 'oi_change_1h' (Aggressive leverage buildup), 'natr_1h' (Normalized ATR volatility)."
  2. Changed2 schema fields changed
    • changedInput schema / properties / sort_by / description
      Previous value: -"Market anomaly filter metric."New value: +"Anomaly sorting metric: 'rvol_5m' (Whale volume spikes), 'funding_rate' (Carry squeezes), 'oi_change_1h' (Leverage inflow), 'natr_1h' (Volatility)."
    • changedInput schema / properties / sort_by / enum
      Previous value: -[
-  "funding_rate",
-  "rvol_5m",
-  "oi_change_1h",
-  "natr_1h"
-]New value: +[
+  "rvol_5m",
+  "funding_rate",
+  "oi_change_1h",
+  "natr_1h"
+]
  3. First observed

TDQS

A4.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does well: read-only, idempotent, zero side effects, <1s cache latency, unrestricted rate limit, and a documented degenerate-case return. However, it omits how fresh the snapshot can be relative to the cache refresh cycle and what the item-level fields look like, so it stops short of full disclosure.

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?

Labeled sections (behavior, when to use, when not to use, failure modes) make it scannable and front-load the safety profile. Every line contributes a decision-relevant fact; nothing is redundant padding.

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?

With no output schema, the description compensates by stating the return is an array of top coins by 24h volume with length bounded by `limit`, plus the flat-market edge case. Item-level field contents are the only meaningful gap for a two-parameter screening tool.

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?

Schema coverage is 100%, so the baseline is 3; the description adds the non-obvious consequence that output length is strictly bounded by `limit`, tying the parameter to result shape rather than just restating its range. The enum semantics remain fully in the schema, so it does not need to repeat them.

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?

States a specific verb and resource (fetches a pre-computed market-wide anomaly snapshot) with concrete scope: all 1,650+ perpetual contracts screened simultaneously from a Redis cache. It is clearly distinguishable from get_ta_consensus, which is named as the single-coin/indicator-history alternative.

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?

Explicitly instructs to use this as the FIRST exploratory step for scanning the whole market, and names the exclusion case (single-coin deep analysis or indicator history) with the sibling tool to use instead. Both the when and the when-not are stated outright.

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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