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mainstreet_onchain_info

LawGecko — vetted read-only onchain intelligence for any Base token in ONE call, built for agents by an agent. Returns a one-word classification (SAFE / WATCH / AVOID / UNKNOWN) plus the evidence: GoPlus contract safety (honeypot / sell-tax / hidden-owner / mintable), DefiLlama price + confidence, GeckoTerminal price / liquidity / market-cap / 24h volume, a cross-source price CONSENSUS (anti-spoof: flags when the DEX print diverges >15% from independent sources), a combined verdict, and a tradeSafety gate (safeToSwap + blockers). Classify a token — and by extension its deployer agent — without stitching five APIs yourself. MainStreet vets the data; it never executes a trade.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesBase token contract address.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added
  2. Removed
  3. Added

TDQS

A3.9/5.0
Behavior4/5

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

The description explicitly states the tool is read-only and never executes a trade, which is crucial for behavioral transparency. It details the output components (classification, GoPlus, DefiLlama, GeckoTerminal, consensus, verdict, tradeSafety gate). However, without annotations, it could further clarify any potential side effects or limitations like data freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

The description is detailed but front-loaded with the main purpose and key outputs. It uses a few long sentences that pack information efficiently. While slightly dense, it avoids unnecessary fluff and remains understandable.

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?

Given the complexity of aggregating multiple data sources, the description covers the main return fields comprehensively: classification, evidence from GoPlus, DefiLlama, GeckoTerminal, price consensus, verdict, and tradeSafety gate. With no output schema, it provides sufficient context for an agent to understand what to expect.

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 only parameter (address) is fully described in the schema with a pattern and description. The description adds 'Base token' context which is already present in the schema description. Schema coverage is 100%, so the description adds no significant new meaning, earning a baseline 3.

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 purpose: providing read-only onchain intelligence for any Base token, returning a one-word classification (SAFE/WATCH/AVOID/UNKNOWN) along with evidence from multiple sources. It distinguishes itself from siblings by focusing on token classification rather than other agent-related functionalities.

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

Usage Guidelines3/5

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

The description implies usage for classifying token safety without specifying when to use alternatives. It mentions avoiding multiple API calls but does not explicitly state when not to use this tool or compare it to siblings. More explicit guidance would improve clarity.

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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