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BACH-AI-Tools

Website Contacts Scraper

by BACH-AI-Tools
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves a website URL from a keyword, the other scrapes contacts from a given domain. No overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern using snake_case: get_website_by_keyword and scrape_contacts_from_website. Perfectly predictable.

    Tool Count4/5

    With only two tools, the server is minimal but focused. For a website contacts scraper, this covers the core workflow. A few more tools (e.g., email verification) could enhance completeness, but the count is reasonable.

    Completeness5/5

    The tools cover the essential lifecycle: finding a website from a company name and then scraping contacts from it. There are no obvious gaps for the stated purpose of scraping emails, phones, and social profiles from root domains.

  • Average 3.3/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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 provided, so the description bears full responsibility for behavioral disclosure. It claims support for 'up to 20 keywords' but the input schema has no parameters, creating a contradiction. No other behavioral traits (e.g., auth needs, rate limits, error behavior) are mentioned.

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

    Conciseness3/5

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

    The description is relatively concise (three sentences) but includes information that contradicts the schema, reducing its effectiveness. It is front-loaded with the core purpose but the mismatch undermines its value.

    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?

    Given no output schema, the description does not explain return values or possible error cases. It provides some context via the sibling tool mention, but the missing parameter definition makes it incomplete for an agent to use reliably.

    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 coverage is 100% but the schema defines zero parameters. The description adds information about keywords that is not reflected in the schema, causing confusion. It does not clarify how to pass the keywords when the schema has no parameters.

    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: getting a company website URL by keyword or company name. It distinguishes itself from the sibling tool 'scrape_contacts_from_website' by noting it is used to obtain the domain before scraping contacts.

    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 provides explicit usage guidance: it can be used when only a company name is known and the website domain is needed before scraping contacts. It also mentions that up to 20 keywords are supported per query, but does not specify when not to use it.

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

  • Behavior3/5

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

    The description discloses batching behavior and a default email restriction, but without annotations it should provide more behavioral context (e.g., rate limits, auth requirements, read-only nature). The note is incomplete due to truncation, reducing transparency.

    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 concise and front-loaded, but appears truncated at the end (note cut off), which detracts from clarity. Otherwise, efficient in word count.

    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?

    Given no output schema and three parameters (two poorly described), the description lacks critical information on return format, error handling, or rate limits. The truncated note suggests incomplete context for the optional parameters.

    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?

    Despite 100% schema coverage, the descriptions for 'match_email_domain' and 'external_matching' are unhelpful ('Example value: '), adding no meaning beyond parameter names. The main parameter 'query' is adequately described in the description but not linked to schema details.

    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 it scrapes emails, phone numbers, and social profile links from a website root domain, distinguishing it from the sibling tool 'get_website_by_keyword' which likely finds websites by keyword rather than extracting contacts.

    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 mentions batching up to 20 domains and a note about email domain restriction, providing context for when to use the tool. However, it does not explicitly state when to use this tool over the sibling or when not to use it.

    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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