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meme-radar

Ranks Solana meme coins by quality score based on buy pressure, liquidity, and volume consistency. Filters low-liquidity rugs for reliable discovery.

Instructions

Solana meme coin quality-volume radar. Returns trending tokens ranked by a quality score that rewards organic buy pressure, liquidity depth, and volume consistency. Filters out low-liquidity rugs. Use for meme coin discovery, social-momentum confirmation, or pump detection. Data: DexScreener free API; no API key required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax tokens to return (1–30). Default: 10.
min_liquidity_usdNoMinimum pool liquidity in USD. Default: 1000 (filters micro-rugs).
min_volume_h24NoMinimum 24h trading volume in USD. Default: 5000.
sort_byNoRanking field. Default: quality (composite buy-pressure + consistency + liquidity score).
Behavior5/5

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

Describes behavioral traits: rewards organic buy pressure, liquidity depth, volume consistency; filters rugs. No annotations contradict. Provides full context for a safe, transparent tool.

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?

Three sentences, each informative, directly addressing purpose, usage, and data source. No wasted words; front-loaded with key function.

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?

Lacks explicit output structure (e.g., what fields returned), but given simplicity and no output schema, description sufficiently covers functionality. Minor gap for exact response format.

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

Parameters5/5

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

Schema coverage is 100% with descriptions, but description adds meaning: explains min_liquidity_usd filters 'micro-rugs', sort_by default 'quality' is composite of buy-pressure, consistency, liquidity. Exceeds schema value.

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?

Description clearly states it's a Solana meme coin quality-volume radar that returns trending tokens ranked by a quality score, filtering low-liquidity rugs. This distinguishes it from sibling tools like address-security or dex-trending-pools.

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 use cases given: meme coin discovery, social-momentum confirmation, pump detection. Also mentions data source (DexScreener free API, no key required), helping users decide when to invoke.

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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