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LeadIntel

LeadIntel

by rushikesheleven
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

analyze_website

Audit a business website for technical readiness, structure, and public contact details. Checks SSL, headings, alt tags, contact info, social profiles, and broken internal links to qualify leads.

Instructions

    Analyze a business website for technical readiness, structure, and contacts.

    Performs non-invasive examination of the target website:
    - HTTP/HTTPS status and SSL verification.
    - Title, meta description, and mobile viewport configuration.
    - H1/H2 heading hierarchy and image alt tag presence.
    - Public email addresses, telephone numbers, and contact forms.
    - Linked social media profiles.
    - Sampled check for broken internal links.

    Security & Compliance:
    - Respects robots.txt directives before scraping.
    - Protects against SSRF (blocks localhost, private networks, cloud metadata).
    - Enforces request timeouts and max page size limits.
    - Does not scrape private or sensitive personal info.

    Args:
        url: The target website URL (e.g. 'https://example.com').
        check_broken_links: If True, spot-checks up to 10 internal links for broken status (default: True).

    Returns:
        Structured diagnostic dictionary.

Input Schema

NameRequiredDescriptionDefault
urlYes
check_broken_linksNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does so well: it declares the examination is non-invasive, honors robots.txt, blocks SSRF targets (localhost, private nets, metadata), and enforces timeouts and page-size caps. What it still omits is the read-only guarantee stated outright and any rate-limit or failure-mode behavior for unreachable sites.

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 one-line summary is front-loaded, then grouped bullets for scope, a security block, and an Args block. The bulleted inventory is longer than strictly necessary but each item maps to real work the tool performs, so little is wasted.

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?

For a two-parameter read audit with an output schema present, the description covers scope, safety posture, and both inputs. The return value is legitimately left to the output schema, so the only shortfall is the absent routing guidance against overlapping siblings.

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 0%, so the description must compensate and largely does: the Args block gives a URL format example and explains that check_broken_links spot-checks up to 10 internal links. The 'up to 10' cap is genuine added meaning beyond the schema's bare boolean; only minor gaps (URL normalization, scheme handling) remain.

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 first line gives a concrete verb and resource ('Analyze a business website') followed by an enumerated scope (SSL, meta, headings, contacts, socials, broken links). It is clear what the tool does, but it never distinguishes itself from the overlapping sibling check_seo or find_social_profiles, which a reader could otherwise confuse with this sweep.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied — an agent can infer this is the pre-outreach technical audit step, but there is no explicit when-to-use statement, no prerequisites, and no pointer to alternatives like check_seo when only SEO data is needed. The default-on broken-link check is the only decision guidance offered.

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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