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x711_data_retrieval

Read-onlyIdempotent

Fetches clean text from any public HTTPS URL.

Use x711_web_search first to find the URL, then this tool to read it.

Returns: { content: string, content_type: string, url: string, char_count: number }

HTML stripped to plain text. JSON returned as-is. Blocked: localhost, private IPs, .internal domains.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFully-qualified public HTTPS URL to fetch. Examples: 'https://docs.uniswap.org/contracts/v3/reference/core/UniswapV3Pool', 'https://api.coingecko.com/api/v3/coins/ethereum', 'https://raw.githubusercontent.com/ethereum/EIPs/master/EIPS/eip-1559.md'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
contentYes
char_countYes
content_typeNo

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnly, openWorld, idempotent), the description discloses additional behavior: HTML is stripped to plain text, JSON is returned as-is, and specific network restrictions (localhost, private IPs, .internal domains) apply. It also mentions the exact return shape. No contradictions with 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 compact and front-loaded. The first sentence states purpose, the second gives usage context, the third lists return fields, and the fourth explains content handling and restrictions. Every sentence delivers essential information without redundancy.

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 simple fetch tool with one parameter, the description covers purpose, usage workflow, output structure, content processing, and network restrictions. It is complete enough for an agent to select and invoke correctly. The presence of an output schema further supports completeness, and the description supplements it with behavioral details.

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?

The schema already fully documents the single parameter (url) with format and examples, so baseline is 3. The description adds minimal semantic value beyond the schema, except clarifying that the output depends on content type (HTML vs JSON), which is more about behavior than the parameter itself.

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: 'Fetches clean text from any public HTTPS URL.' It uses a specific verb and resource, and distinguishes itself from sibling x711_web_search by framing itself as the reader after a search. This is a clear, non-tautological purpose.

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 guidance is given: 'Use x711_web_search first to find the URL, then this tool to read it.' It also lists blocked URL patterns, indicating when the tool will not work. This clearly defines the tool's usage context and alternative.

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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