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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 forty minutes and travels with the answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesA BSC token address, or a PancakeSwap V3 pool address to pin the pool
capitalUsdNoSize of the position in dollars, optional - defaults to 1000

TDQS

A3.9/5.0
Behavior5/5

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

The description goes well beyond the readOnlyHint/destructiveHint annotations. It discloses the replay methodology, the use of actual V3 Swap events, the live forty-minute window, the per-width outputs, the absence of impermanent loss modeling, and the trade-off warning that IL is worst where fees are best. This gives the agent meaningful behavioral expectations without contradicting 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.

Conciseness3/5

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

The description is longer and more narrative than necessary for a two-parameter tool. The first sentence contains useful context but is padded with phrases like 'the decision concentrated liquidity actually forces.' Still, each sentence contributes substantive information about behavior, outputs, limitations, and the time window, so it is not wasteful enough to warrant a 2.

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

Completeness3/5

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

With no output schema, the description does a decent job conveying what the tool returns: fees per candidate width, in-range duration, and exit count. However, it never explains how candidate widths are specified or what exact set of widths is considered, which is a meaningful gap for an agent trying to interpret or request results. The temporal window and lack of IL modeling are covered, but the overall contract remains somewhat underspecified.

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?

The input schema already covers both parameters at 100%, so the baseline is 3. The description adds some context by tying 'stated size' to capitalUsd and mentioning pool/token address pining, but it does not explain parameter formats or defaults beyond what the schema states. The phrase 'per candidate width' introduces a concept not reflected in the schema, which slightly reduces clarity.

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 states this tool helps a liquidity provider choose a PRICE RANGE for a PancakeSwap V3 pool by replaying real swaps and computing fees, in-range time, and exits. It distinguishes itself from modeling/forecasting tools by explicitly saying 'This does not model and does not forecast,' though it does not name a specific sibling alternative.

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 opening sentence gives a clear use case: a liquidity provider who has already picked a pool and now needs to decide on a price range. It also implicitly says when not to use it for forecasting or impermanent loss analysis. It does not explicitly compare to alternatives like pancakeswap_fee_tiers or pancakeswap_best_route, but the situational framing is reasonably clear.

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

A3.7/5.0
Disambiguation3/5

Several tools operate on overlapping data: bobai_burned, bobai_activity, and bobai_smart_money all report burn-related metrics, while bobai_token_info, bobai_circulating_supply, and bobai_burned overlap on supply numbers. The long descriptions mitigate this, but the purpose boundaries are less crisp than ideal. The BSC pool tools are more easily told apart.

Naming Consistency3/5

Most token tools use a consistent bobai_* snake_case prefix, but the set mixes conventions: bnb_agent_*, bsc_pool_scan, find_agents_on_bnb_chain, and pancakeswap_fee_tiers break the pattern. The names are still readable and mostly noun-oriented. There is no chaotic mixing of camelCase or vague verbs, but the pattern is not uniform.

Tool Count3/5

19 tools sits in the borderline heavy range for a token research server. Many are focused data views, but some could be consolidated, such as bobai_token_info with circulating supply/burned, or the informational guide/links/tokenomics cluster. Each tool has a defensible role, but the overall surface feels padded.

Completeness4/5

Core workflows are well covered: price, liquidity, DEX parameters, purchase guidance, burns, wallet balances, and BNB agent discovery. Missing historical price/volume, holder distributions, or detailed per-agent profiles, but these are minor gaps rather than dead ends. The server gives an agent what it needs to understand and interact with $BOBAI.

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