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Glama

Fee estimate (input token vs DEEP)

estimate_fees
Read-onlyIdempotent

Estimate DeepBook fill fees for a pool, quantity, price, and maker/taker role, then compare input-token versus DEEP payment using live on-chain rates.

Instructions

Estimated DeepBook fee for a fill of qty at price as maker or taker, paid in the input token (rate x 1.25) versus in DEEP (base rate), using the live on-chain fee rates and the DEEP_USDC mid. Education/information only; not financial advice. Read-only public data, may be delayed or wrong.

Input Schema

NameRequiredDescriptionDefault
qtyYesBase quantity
poolYesDeepBook pool name BASE_QUOTE, e.g. SUI_USDC (case-insensitive; '/' or '-' also accepted)
roleNotaker
priceNoPrice; defaults to the current mid

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.3

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare this as read-only, idempotent, non-destructive, and open-world. The description adds useful behavioral context beyond that: it relies on live on-chain fee rates and the DEEP_USDC mid, and it warns that data may be delayed or wrong. It does not cover auth or rate limits, but the annotations lower the bar.

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 front-loaded with the core fee-estimate behavior and stays compact. The disclaimer and data-caveat sentences are relevant, though slightly boilerplate, and do not bloat the definition.

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, so the description must convey the return concept. It does so by explaining that the estimate compares payment in the input token vs DEEP and depends on live rates and the DEEP_USDC mid, while also disclosing freshness limitations. The only minor gap is that it does not explicitly describe the response shape.

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 75%, so the schema documents most parameters, including qty, pool, and price defaults. The description adds conceptual meaning for role ('maker or taker') and the fee formula, but it does not expand on pool naming syntax beyond what the schema already states.

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 states a specific verb and resource: estimate the DeepBook fee for a fill of qty at price as maker or taker, comparing payment in input token vs DEEP. It is clear enough to distinguish the tool from generic pool-data siblings, but it does not explicitly name an alternative tool or scope boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no explicit when-to-use or when-not-to-use guidance, nor does it name alternatives such as get_pool_params or get_mid_price. Usage is only implied by the phrase 'Estimated DeepBook fee'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.