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EchoLedger

by io.github.icmoore

AnalyzeStableswapLP

Analyze a 2-asset Curve-style Stableswap LP position's PnL using the amplified-invariant IL formula where small depegs can produce surprisingly large IL at high A. Values are in peg-numeraire (tokens valued 1:1); fee income is not attributed in v1 (pool-global only); positions whose implied alpha is in the unreachable regime return None on il_percentage, net_pnl, and real_apr.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rpc_urlYesAn Ethereum (or L2) JSON-RPC URL used to read live pool state. Required; supplied by you per call (BYO-RPC) and may carry your provider key. The endpoint stores and logs nothing — the URL is never persisted or written to logs.
chain_idNoOptional guard. If supplied and the RPC reports a different chain id, the call is rejected. Defaults to 1 (Ethereum mainnet) conceptually; omit to skip the check.
pool_typeYesWhich protocol the pool at pool_address belongs to. This tool accepts only stableswap (2-asset plain Curve pool).
lp_init_amtYesLP tokens held by this position, in human units.
block_numberNoOptional block number to pin the read to a historical block. Omit to read the latest block.
pool_addressYesOn-chain address of the pool/pair to analyze (Uniswap V2/V3 pair, Balancer weighted pool, or Curve stableswap pool). Required. Lowercase, uppercase, or checksum casing all work.
entry_amountsYesPer-token entry amounts in pool insertion order. Exactly 2 entries (2-asset pools only in v1).
holding_period_daysNoOptional holding period in days. If supplied, real_apr is annualized from net_pnl.

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does well: it discloses valuation units (peg-numeraire), exclusions (fee income not attributed), and edge-case behavior (returns None for unreachable alpha regime). It also warns about high A's effect on IL, providing substantial behavioral context.

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?

Two sentences pack purpose, scope, and three caveats without redundancy. Every clause adds value, and the key purpose is front-loaded, making it appropriately sized and well-structured.

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?

For a complex analysis tool with no output schema, the description covers important output fields (il_percentage, net_pnl, real_apr) in edge cases and explains valuation/fee assumptions. It doesn't enumerate all potential outputs, but given the schema richness and sibling context, it is reasonably complete.

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 description coverage is 100%, so parameters are already well-documented. The description adds no direct parameter semantics beyond mentioning the formula and None cases, which aligns with the baseline 3 for high coverage.

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 analyzes a 2-asset Curve-style Stableswap LP position's PnL using a specific formula (amplified-invariant IL). This distinguishes it from siblings like AnalyzeBalancerLP and SimulateStableswapMove by specifying the pool type and analytical method.

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 implies usage for stableswap LP analysis and scopes to 2-asset Curve-style pools, but does not explicitly name alternatives or exclusions. The schema's pool_type constraint reinforces the scope, yet the description lacks direct alternative guidance.

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

A4.2/5.0
Disambiguation4/5

Tools are mostly distinct by protocol and action, but AnalyzePosition and the protocol-specific Analyze*LP tools overlap in purpose, as do SimulatePriceMove and Simulate*Move. Descriptions clearly differentiate them, so an agent can select correctly with careful reading, but the generic versus specific split introduces some ambiguity.

Naming Consistency5/5

All tool names follow a consistent VerbNoun pattern (Analyze, Assess, Build, Calculate, Check, Detect, Simulate) with no mixing of conventions. The naming is uniform and predictable across the entire set.

Tool Count5/5

11 tools is well within the ideal range for a specialized LP analysis server. Each tool covers a distinct function across protocols, and none feel redundant or superfluous. The count is well-scoped for the server's purpose.

Completeness4/5

The tool set covers the full lifecycle of LP analysis: position PnL analysis, price simulations, depeg risk, slippage, pool health, rug detection, and state serialization. Minor gaps exist, such as fee attribution for Balancer and Curve pools and a generic simulate tool for all protocols, but these are protocol limitations or acceptable omissions.

Resources