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minghsuy

ctscout

by minghsuy
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v0.2.5

  • Disambiguation5/5

    The two tools have completely distinct purposes: one converts domain to organization, the other converts organization to list of domains. Descriptions explicitly warn against misusing them, with clear 'Don't use when' instructions. No overlap.

    Naming Consistency5/5

    Both tools follow a consistent pattern: 'ctscout_' + verb + '_' + noun ('lookup_domain' and 'search_company'). The naming is uniform and predictable.

    Tool Count3/5

    The server has only 2 tools, which is on the low end for a typical MCP server. However, for the focused domain of domain-attribution lookup (forward and reverse), the count is adequate and not overly thin.

    Completeness5/5

    The tool surface covers the two essential operations of the domain-attribution warehouse: lookup by domain and search by company name. There are no obvious gaps for the stated purpose; additional tools like listing coverage or quota checks are handled via external resources.

  • Average 4.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 43 commits in the last 12 weeks
    • Last stable release on
    • 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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    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

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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

  • Behavior5/5

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

    Adds substantial context beyond annotations: auth requirements (CTSCOUT_API_KEY), error handling (401, 429), rate limits (free vs pro tiers), truncation behavior, and the legal-vs-brand caveat which is critical for correct usage.

    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?

    Well-structured with headers (Args, Returns, Examples, etc.) and front-loaded with core purpose. Slightly long due to necessary caveats, but every section earns its place.

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

    Completeness5/5

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

    Comprehensive for a 2-param tool with no output schema. Covers purpose, parameters, return formats, usage guidance, auth, errors, and important caveats. Leaves no gaps.

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

    Parameters4/5

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

    Schema coverage is 100% so baseline is 3. Description adds value by explaining partial matching behavior and giving format use cases (markdown for humans, JSON for programmatic). Minor improvement over schema.

    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 the tool searches ctscout.dev's domain-attribution warehouse by organization name and returns apex domains. It distinguishes from sibling tool ctscout_lookup_domain by explicitly stating when not to use this tool.

    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?

    Provides explicit when-to-use examples like 'Find all domains owned by Cloudflare' and when-not-to-use guidance directing to ctscout_lookup_domain. Also includes caveats about legal-vs-brand names and coverage limitations.

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

  • Behavior5/5

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

    Adds details beyond annotations: returns 0 if domain not in warehouse, explains missing domains, cert-subject org nuance, and auth/limits. No contradiction with annotations.

    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?

    Well-structured with purpose, arg details, returns, examples, and caveats. Every sentence adds value, front-loaded main purpose. ~200 words, appropriately concise.

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

    Completeness5/5

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

    Covers return values (no output schema), edge cases, usage alternatives, and auth/limits. Complete for the tool's complexity.

    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%, and description adds examples for domains, explains max 10, behavior of sibling domains, and return format details for both response_format options.

    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 reverse-looks up organization for domains and distinguishes from sibling ctscout_search_company with explicit when-to-use examples.

    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?

    Provides explicit when-to-use ('Who owns gs.com?'), when-not-to-use (company name → use search_company), and coverage caveats about DV-only domains and subsidiary ownership.

    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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  • Evaluate tool definition quality.

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