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by com.brainonbnb
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pancakeswap_range_plan

Read-only

For a liquidity provider who has picked a PancakeSwap V3 pool and now has to pick a PRICE RANGE - the decision concentrated liquidity actually forces, and the one every interface answers with a preset. This does not model and does not forecast. It replays: the V3 Swap event carries the liquidity that was active when each trade went through, so a position of a stated size is walked through the swaps that really happened in a live window and asked, at each one, whether it was in range and what share of the active liquidity it was. Returns per candidate width the fees it would have collected, how much of the window it stayed in range, and how many times the price walked out. Impermanent loss is not in it, and it is worst exactly where the fees are best. The window is about an hour and travels with the answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
quoteNoThe other side of the pair, optional: BNB, USDT, USDC, USD1 or BUSD, or its address. Without it the quote with the deepest V3 pool is used, so pass it whenever a pair was named (CAKE/BNB)
addressYesA BSC token address, or a PancakeSwap V3 pool address to pin the pool
capitalUsdNoSize of the position in dollars, optional - defaults to 1000

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / quote
      Added value: +{
+  "description": "The other side of the pair, optional: BNB, USDT, USDC, USD1 or BUSD, or its address. Without it the quote with the deepest V3 pool is used, so pass it whenever a pair was named (CAKE/BNB)",
+  "type": "string"
+}
  2. Added

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already mark this read-only and non-destructive; the description goes further by explaining the replay mechanism, explicit exclusions (no modeling, no forecasting, no impermanent loss), the live window of about an hour, and the caveat that it is worst exactly where fees are best. This is substantial behavioral disclosure beyond the 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 compact but somewhat ornate, especially the opening clause about concentrated liquidity forcing the decision. Most sentences add a distinct, useful point, and the key outputs and caveats are front-loaded enough for an agent to grasp quickly.

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?

There is no output schema, but the description enumerates the main returned values: fees collected, time in range, and number of walk-outs. It also covers limitations and temporal scope, giving an agent enough context to understand the result shape, though exact output formatting is not specified.

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%, so the schema already documents all three parameters. The description provides conceptual mapping such as 'position of a stated size' to capitalUsd, but it does not add meaningful parameter semantics beyond what the schema fields already describe.

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

Purpose4/5

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

The description clearly explains an analytical function: it replays historical V3 Swap events through a position of a given size and reports fees and in-range behavior per candidate price range. It is detailed enough to distinguish it from route/fee-tier siblings, though it never explicitly names an alternative tool.

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?

It gives a clear context for when to use the tool: a liquidity provider has already chosen a PancakeSwap V3 pool and now needs to choose a price range. It does not explicitly compare against siblings or state when not to use it, but the intended decision scenario is well-defined.

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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