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get_meme_analyze

Rug risk analysis: risk score, flags, liquidity, holder analysis. $0.05.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYes
api_keyYes

Schema Changelog

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

  1. Changed2 schema fields changed
    • removedInput schema / properties / address / description
      Removed value: -"Token contract address"
    • removedInput schema / properties / api_key / description
      Removed value: -"Your API key"
  2. First observed

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the burden. It only mentions the cost ($0.05) but does not disclose read-only behavior, authentication requirements, or any side effects.

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 extremely concise: one sentence plus a cost note. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With two undocumented required parameters, no output schema, and no annotations, the description is insufficient for an agent to use the tool correctly. It lacks details on input format, output structure, and behavior.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the parameters 'api_key' and 'address'. It adds no meaning beyond the schema's property names.

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 performs rug risk analysis with specific outputs (risk score, flags, liquidity, holder analysis). It distinguishes from siblings like analyze_contract and get_meme_scan by focusing on rug risk for meme coins.

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 on when to use this tool versus alternatives. The description does not specify prerequisites, exclusions, or compare with similar tools.

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

C2.8/5.0
Disambiguation4/5

Tools generally have distinct purposes, but some overlap exists between price history tools (get_ohlc vs get_price_summary) and meme-related tools (analyze vs scan vs trending). Overall, descriptions help differentiate.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (e.g., get_price, set_price_alert, analyze_contract). No mixing of conventions.

Tool Count3/5

48 tools is on the higher side, but it covers a broad spectrum of crypto data (prices, DeFi, sentiment, alerts, etc.) and each tool seems justified. However, the count could be slimmed down by grouping similar functions.

Completeness4/5

Very comprehensive coverage of crypto data: prices, market stats, DeFi, sentiment, gas, alerts, portfolio, arbitrage, token analysis. Minor gaps like NFT data or direct exchange rate queries.

Resources