R_net LP risk evaluator for DeFAI agents. IL + Breakeven Corridor O(1). L402 Lightning paywall.
Scored across 1 tool
With only a single tool, there is no possibility of confusion between tool purposes. The tool has a clear, specific function.
The single tool name 'evaluate_pool' follows a verb_noun pattern that is consistent and descriptive. There are no other names to compare against.
One tool is on the borderline of being too few for a typical server. It feels thin for a decision engine, which might be expected to provide multiple related operations.
The tool surface is severely limited, providing only a single evaluation operation. Obvious supporting functionalities such as data retrieval, comparison, or scenario analysis are missing, which could hinder an agent's ability to perform comprehensive assessments.
Evaluate LP position risk and calculate R_net & breakeven corridor.
| Name | Required | Description | Default |
|---|---|---|---|
| apy | Yes | Annual Percentage Yield of the pool (e.g. 0.20 for 20%) | |
| days_held | No | Number of days the position has been held (default: 30) | |
| price_ratio | Yes | Current price ratio compared to entry price (e.g. 0.85 for 15% price drop) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not mention whether the tool is read-only, has side effects, requires specific permissions, or how it handles inputs. The description only states the high-level function, leaving the agent without essential operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that captures the tool's purpose without any redundancy or filler. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema and no annotations. The description mentions R_net and breakeven corridor but does not define these terms or indicate the output format, leaving potential gaps for an agent to understand what the tool returns.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter having a clear description and example. The tool description adds no additional meaning about how parameters are used in the calculation, maintaining the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool evaluates LP position risk and calculates R_net and breakeven corridor, providing a specific verb and resource. It distinguishes itself from the sibling tool get_latest_audit, which focuses on audits.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for evaluating LP risk, but it provides no explicit guidance on when to use this tool versus alternatives or any exclusions. The context is implied but not overtly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
get_latest_auditevaluate_poolget_latest_auditSize-aware exit cost, depeg risk & liquidity fragility for a Base token (x402, testnet).
Deterministic crypto futures, on-chain risk, and prediction-market math. 32 tools. Not AI estimates.
DeFi pool yield+security intelligence & token/contract risk scanner. USDC on Base via x402.
Verifiable, deterministic risk math for autonomous agents; re-runnable proof on every answer.
Add one secure layer between your agents and this server.
