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Baneado98

rug-check

by Baneado98
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

75%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.1

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one for batch checking up to 10 tokens, the other for individual token assessment. No overlap.

    Naming Consistency5/5

    Both tools follow a consistent 'rug_check_' prefix with descriptive verbs ('many' vs 'token'), all in snake_case.

    Tool Count5/5

    With only 2 tools, the count is minimal but perfectly scoped for the domain of rug checking, covering both individual and batch needs.

    Completeness5/5

    The tool set covers the primary use case (assessing token risk) with both single and batch modes, leaving no obvious gaps for the intended purpose.

  • Average 4.1/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 6 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior3/5

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

    No annotations provided, so description carries full burden. Discloses return behavior ('Returns the verdict and score for each'), but lacks details on error handling, rate limits, or 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?

    Two sentences, no wasted words. Front-loaded with action and key constraints.

    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 tool has one parameter and no output schema, description adequately explains input structure and output type. Could add more on output format or potential errors, but sufficient for a batch tool.

    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 coverage is 100%, so description adds little beyond schema. It repeats structure ('Pass an array of {chain,address}') and notes max 10 items, already in schema. Does not explain field semantics further.

    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 'Run rug_check on up to 10 tokens at once' - specific verb and resource. Differentiates from sibling 'rug_check_token' by indicating batch capability.

    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?

    Provides examples of when to use: 'screen a watchlist or a batch of candidate tokens in one call'. Implicitly suggests using rug_check_token for a single token, but does not explicitly state when not to use this tool.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    With no annotations, the description carries the full burden. It details the on-chain checks performed (dangerous owner powers, ownership renounced, owner supply, DEX liquidity, LP lock/burn), offering transparency about data sources. However, it does not disclose potential limitations such as API rate limits, error handling, or behavior for non-ERC-20 tokens.

    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 two sentences, front-loaded with the tool's main purpose and outputs, followed by methodology and usage context. Every sentence adds value; no wasted words.

    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?

    Despite no output schema, the description adequately specifies the return values (risk score 0-100, verdict) and explains the logic. It is sufficient for a tool with two simple parameters, though it could benefit from noting the exact response format.

    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%, so the schema already documents both parameters (chain and address). The description reiterates the chain options and address format without adding new semantic meaning beyond what the schema provides. 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 assesses whether an ERC-20 token is a likely scam/rug pull, with specific outputs (risk score 0-100 and verdict). It also names the sibling tool 'rug_check_many', which implies this tool checks a single token, distinguishing its purpose.

    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 explicitly recommends using this tool 'whenever a user or agent is about to trade, approve, or add liquidity for an unfamiliar token,' providing clear context. It does not explicitly mention when not to use it or contrast with alternatives beyond naming the sibling, but the usage guidance is still strong.

    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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