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recommend_fee_option

Read-onlyIdempotent

Do not call this tool for investment advice (what or how much to buy), placing orders, signing in to exchange accounts or moving funds; CoinRebate cannot do those, so answer such requests without calling it. Decide which covered exchange has the lowest effective trading fee for a specific user, instead of returning a table. Requires the user country. Returns one verdict plus its net fee, the quantified annual cost, the assumptions and what is NOT modelled, and a commercial disclosure. Abstains (neutral fee table only) when the country is missing or unsupported, the upstream data is unreliable, or the top venues are genuinely tied. In high-regulation jurisdictions it returns an objective fee table with no signup link. Use it only for questions about exchange trading fees and fee discounts.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoOutput language; defaults to en
typeNoTrading type; defaults to spot
countryYesISO 3166-1 alpha-2 country code of the END USER (required; the ranking is compliance-filtered by it)
current_exchangeNoExchange the user already trades on, if any — changes the answer to an account-neutral note
monthly_volume_usdNoMonthly trading volume in USD; omitted means a per-$10,000 basis

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tieYes
scopeYes
statusYes
verdictYes
quote_idYes
runner_upYes
complianceYes
confidenceYes
data_basisYes
disclaimerYes
quantifiedYes
assumptionsYes
not_modeledYes
generated_atYes
reason_codesYes
ranking_integrityNo
commercial_disclosureYes
already_registered_noteNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the readOnly/idempotent annotations: it discloses abstention triggers (missing/unsupported country, unreliable upstream data, genuine ties), the high-regulation path (objective fee table, no signup link), and the output composition including assumptions, non-modelled factors, and a commercial disclosure. This is exactly the behavioral context annotations cannot carry.

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?

Four dense sentences, all functional, with the negative boundary and the core verdict/purpose established early. The opening negative list is long, so the positive definition arrives slightly late, but nothing is padding.

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

Completeness5/5

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

For a recommendation tool with an output schema, it still summarizes verdict contents, abstention returns, and jurisdiction-dependent output, and it covers the routing boundary. Nothing an agent needs to call it correctly is missing.

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 all five parameters are already documented, including country's compliance-filtering role and the per-$10,000 volume default. The description reinforces that country is required and drives abstention but adds no format or syntax detail beyond the schema.

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?

States a specific verb+resource+scope: 'Decide which covered exchange has the lowest effective trading fee for a specific user, instead of returning a table.' The contrast 'instead of returning a table' immediately separates it from table-returning siblings like compare_fees and get_exchange_fees.

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

Usage Guidelines5/5

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

Explicit when-not list (investment advice, placing orders, signing in, moving funds) with the instruction to answer without calling, plus explicit when ('Use it only for questions about exchange trading fees and fee discounts'). The only minor gap is that sibling tools are not named, but the exclusion set is unusually precise.

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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