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cex_square_list_square_ai_search

Read-onlyIdempotent

Search Gate Square content using AI (posts, analysis, signals)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination, starting from 1
sortNoSort order: 0=hottest (default), 1=newest
limitNoNumber of results, 1~50, default 10
keywordNoSearch keyword (currency name or content keyword, e.g. BTC, ETH)
currencyNoCurrency filter (exact currency code, e.g. BTC, ETH, SOL)
time_rangeNoTime range: 0=all (default), 1=last day, 2=last week, 3=last month

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the 'using AI' detail, hinting that results may be AI-ranked or curated, which is useful behavioral context. However, it does not disclose potential variability, rate limits, or output specifics beyond 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that fronts the key action ('Search Gate Square content') and adds parenthetical examples. Every word earns its place, with no redundancy or filler.

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 search tool with 6 optional parameters and no output schema, the description provides the essential scope (content types) and technology (AI). It does not explain return value structure, but that is not required since no output schema exists. The content type list compensates for missing context, making it 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 all parameters are already documented. The description does not add additional meaning to parameters beyond what the schema provides. Baseline score of 3 is appropriate since the description adds no parameter-specific insight.

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 action ('Search') and the resource ('Gate Square content'), and elaborates on content types: 'posts, analysis, signals'. This distinguishes it from sibling tools like cex_square_list_live_replay, which is a list operation for a different content type.

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?

No guidance is provided on when to use this tool vs alternatives. The description does not mention exclusions, prerequisites, or when a non-AI search might be preferred. It simply states what it does without contextualizing its usage.

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

B3.1/5.0
Disambiguation5/5

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.

Naming Consistency4/5

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'.

Tool Count1/5

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.

Completeness4/5

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.