cex_fx_get_fx_risk_limit_table
Get a specific risk limit tier table by table ID.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| settle | Yes | Settlement currency: usdt or btc | |
| table_id | Yes | Risk limit table ID |
Get a specific risk limit tier table by table ID.
| Name | Required | Description | Default |
|---|---|---|---|
| settle | Yes | Settlement currency: usdt or btc | |
| table_id | Yes | Risk limit table ID |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description adds no additional behavioral context (e.g., auth, rate limits, side effects) but is consistent with 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, direct sentence that immediately communicates the tool's purpose. No filler or redundant information—ideal conciseness.
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?
Given the simplicity of the operation, the existing annotations, and fully documented parameters, the description is complete enough for an agent to select and invoke the tool correctly. A minor improvement could be mentioning the return payload, but it's not necessary given the clear scope.
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?
The input schema already provides 100% coverage with descriptions for both parameters (settle and table_id). The description does not add further semantic detail beyond what the schema documents, so baseline 3 applies.
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 action ('Get'), the resource ('risk limit tier table'), and the identifier ('by table ID'). It distinguishes itself from sibling tools that list contracts or get other resources.
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 usage context is clear: this is for fetching a single specific table by ID. No exclusions or alternatives are mentioned, but given the tool's specificity and the absence of a sibling list tool for fx risk limit tables, the context is sufficiently evident.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool is clearly scoped by its domain prefix (spot, fx, options, etc.) and resource type, with no two tools serving the same purpose. Even similar data types like candlesticks and order books are unambiguously separated by market.
The naming follows a strong pattern: cex_<domain>_<verb>_<resource>. However, the use of 'get' vs 'list' is occasionally inconsistent (e.g., cex_fx_get_fx_tickers vs cex_spot_list_currencies), and some names are verbose with version suffixes like 'v4'.
With 63 tools, this is an extreme count that will overwhelm an agent. While the breadth covers many product lines, the vast number of endpoints makes selection difficult and violates the typical scope for an MCP server.
The tool surface comprehensively covers public market data across spot, futures, options, delivery, earn, margin, lending, launch, and social products. Minor gaps exist (e.g., no historical trade depth, no single-ticker convenience methods), but the core data needs are fully addressed.