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x711_social_oracle

Read-only

Crypto social sentiment — narrative pulse, hype velocity, community data via CoinGecko + DexScreener. Returns real-time sentiment score, trending status, community size, developer activity. Use before trading decisions. Returns: { token, sentiment_score, trending, community_score, dev_score, narrative, source }. Requires API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tokenYesToken symbol or CoinGecko ID to analyze. Examples: 'ETH', 'bitcoin', 'solana', 'monad'.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the description adds value by noting the requirement for an API key, specifying the real-time nature, and listing the exact return fields (token, sentiment_score, trending, etc.). It also mentions the data sources, giving the agent insight into what to expect. This exceeds the baseline but stops short of full transparency (no error/rate-limit details).

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 compact and front-loaded with the core purpose ('Crypto social sentiment'), followed by key output fields, a usage directive, and a prerequisite. Every sentence/section earns its place; no 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?

With no output schema, the description compensates by listing the return object fields. It also covers the main use case and API key requirement. However, it lacks details on score ranges or interpretation of the fields, which would make it more complete for an agent. Overall, it is adequately complete for a simple single-parameter read-only tool.

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 100% and the description does not add semantic detail beyond the schema's token description. The schema already provides examples ('ETH', 'bitcoin'). The description's mention of 'token symbol or CoinGecko ID' is redundant with the schema, so the description adds no extra parameter meaning.

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 tool's function: analyzing crypto social sentiment with specific outputs (sentiment score, trending, community size, developer activity). It distinguishes itself from siblings by specifying data sources (CoinGecko + DexScreener) and its unique focus on narrative and hype, which sets it apart from price feeds or general data retrieval.

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

Usage Guidelines4/5

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

The description gives explicit usage context: 'Use before trading decisions.' This provides a clear when-to-use scenario. However, it does not mention when not to use it or name alternatives, so it lacks the full exclusions that would merit a 5.

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

A3.9/5.0
Disambiguation3/5

Many tools have overlapping purposes, such as multiple search tools (web_search, deep_search, data_retrieval) and multiple communication tools (agent_ping, agent_telegram, swarm_broadcast). The descriptions help differentiate, but the boundaries are not always clear.

Naming Consistency4/5

All tools consistently use the 'x711_' prefix and lowercase_with_underscores format. Submodules like agent, hive, and tx follow predictable patterns. Minor deviations (e.g., x711_ask_clerk) are rare and still descriptive.

Tool Count2/5

With 47 tools, the server is excessively large for a typical MCP service. While it aims to be a comprehensive platform, the high count makes navigation and selection cumbersome for an agent.

Completeness4/5

The tool set covers a wide range of agent needs: web access, memory, communication, on-chain transactions, code execution, and more. Minor gaps exist (e.g., no agent deletion tool), but overall it is remarkably complete for the stated purpose of an agent platform.

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