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BACH-AI-Tools

bach-bin_ip_checker

by BACH-AI-Tools
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Python
Remote

Server Quality Checklist

50%
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  • Latest release: v1.0.0

  • Disambiguation2/5

    bin_checker and binip_checker have identical descriptions, making them indistinguishable. ip_lookup is distinct, but the overlap between the other two is severe.

    Naming Consistency2/5

    Inconsistent verb choice: 'checker' vs 'lookup'. Also, 'binip_checker' appears to combine BIN and IP, but its description is only about BIN. No clear pattern.

    Tool Count4/5

    Three tools is a reasonable number for a focused utility like BIN and IP checking, though the duplication of BIN tools is unnecessary.

    Completeness3/5

    Covers BIN lookup and IP lookup, but lacks additional operations like history, validation details, or batch processing. Somewhat incomplete for a full fraud-checking service.

  • Average 1.9/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

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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

  • Behavior1/5

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

    No annotations are present, and the description does not disclose any behavioral traits (e.g., read-only, rate limits, data source). The description fails to carry the full burden of transparency.

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

    Conciseness2/5

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

    The description is extremely short but does not earn its place as it is tautological and under-specified. It is not appropriately sized for providing minimal useful information.

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

    Completeness2/5

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

    For a simple tool with one parameter and no output schema, the description is incomplete. It does not explain what the lookup returns or any context about the data.

    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% with a parameter description example, so the baseline is 3. The description adds no additional semantics beyond the schema.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose1/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'IP Address Lookup' is a tautology that merely restates the tool name 'ip_lookup', adding no new information about what the tool does.

    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 is provided on when to use this tool vs. alternatives (e.g., bin_checker or binip_checker), nor are there any exclusions or prerequisites mentioned.

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

  • Behavior2/5

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

    Lacks annotations. The description provides no behavioral details: no mention of read-only nature, output format, rate limits, or side effects. It is purely promotional.

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

    Conciseness1/5

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

    Excessively verbose marketing text not suitable for an API description. Critical information is buried or absent.

    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?

    Given 2 parameters and no output schema, the description should explain return value and usage. It does not, leaving the agent completely uninformed about tool behavior.

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

    Parameters2/5

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

    Schema coverage is 100% but parameter descriptions are only example values. The description adds no semantic meaning beyond 'BIN lookup' and does not explain the ip parameter's role or expected format.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description uses marketing language ('Shield your business from fraud') rather than clearly stating it performs a BIN/IP lookup. It does not explicitly state the tool combines BIN and IP data, and does not distinguish from sibling tools bin_checker and ip_lookup.

    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 vs bin_checker or ip_lookup. No mention of prerequisites, limitations, or typical scenarios.

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

  • Behavior1/5

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

    With no annotations, the description should disclose behavioral traits. It mentions fraud prevention but does not explain what happens on invalid BIN, return format, rate limits, or authentication requirements.

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

    Conciseness1/5

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

    The description is overly verbose marketing language ('Shield your business', 'unparalleled accuracy') and cuts off mid-sentence. It wastes words without providing useful technical information.

    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?

    No output schema is provided, and the description fails to specify what data the tool returns (e.g., card brand, bank info). For a single-parameter tool, this is insufficient.

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

    Parameters2/5

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

    The input schema has 100% coverage but the description adds no meaning beyond 'BIN numbers'. The parameter description only gives an example value, and the tool description doesn't clarify the BIN length or format.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states it's a BIN lookup tool for fraud prevention, verifying and validating card details. However, it does not distinguish from the sibling tool 'binip_checker' and the description cuts off.

    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 like 'binip_checker' or 'ip_lookup'. The description is purely promotional with no contextual usage advice.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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