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x711_hallucination_pill

Read-only

Pre-flight reality check for on-chain AI agents. Verifies token addresses, prices, chain IDs, and contract existence before your agent acts. Catches hallucinated addresses that would cause irreversible losses. FREE: 5/day per IP, unlimited with API key.

Returns: { verified: bool, hallucination_risk: 'none'|'low'|'medium'|'high'|'critical', correct_value, correction, source, confidence }

Supports batch mode (up to 10 claims). Always run before any on-chain tx.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainNoBlockchain context: base, ethereum, arbitrum, optimism, polygon, bnb. Defaults to 'base'.base
claimNoA single claim to verify. Example: 'USDC on Base is at 0x4Fabb145d64652a948d72533023f6E7A623C7C53'
claimsNoBatch mode: up to 10 claims to verify at once.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, and the description adds useful context: rate limits ('FREE: 5/day per IP'), return format with hallucination_risk levels, and batch mode. It also explains the tool's lifecycle role ('pre-flight'). No contradiction with annotations; the description provides additional transparency beyond the annotation.

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 efficient and front-loaded, stating the core purpose in the first sentence. The subsequent return-format and batch-mode details are necessary given the lack of an output schema. No filler or redundant phrasing; every sentence earns its place.

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?

Given the tool's modest complexity (3 optional parameters, no output schema), the description provides a complete picture: purpose, usage timing, return structure, batch limits, and rate limits. It also clarifies the tool's role in preventing irreversible on-chain losses, making it well-rounded.

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%, with each parameter (chain, claim, claims) already described and an example provided for 'claim'. The tool description adds batch-mode context but does not elaborate on parameter semantics beyond what the schema offers. Since the schema does the heavy lifting, the baseline of 3 is appropriate.

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: 'Pre-flight reality check for on-chain AI agents' that 'Verifies token addresses, prices, chain IDs, and contract existence.' This specific verb+resource pairing distinguishes it from sibling tools like x711_price_feed or x711_tx_simulate, and the phrase 'Catches hallucinated addresses' makes its niche explicit.

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 an explicit when-to-use instruction: 'Always run before any on-chain tx.' It also frames the tool for 'on-chain AI agents' to prevent irreversible losses. While it doesn't mention when not to use or name alternatives, the context is clear and actionable.

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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