Skip to main content
Glama

ContrastAPI

by com.contrastcyber

Geo Audit

geo_audit
Read-onlyIdempotent

Deterministic GEO / AI-visibility readiness audit of a domain's homepage with a 0-100 score + a missing_signals fix list. Answers "can AI assistants (ChatGPT, Claude, Perplexity, Google AI) discover, crawl, and recommend this site?" using STRUCTURAL signals ONLY — no LLM is queried, fully deterministic. 7 weighted rules: llms.txt present (15), AI-crawler robots.txt access — 9 crawlers incl. GPTBot/ClaudeBot/PerplexityBot/Google-Extended/CCBot (25 — the dominant signal; blocking = invisible to that AI surface), schema.org @type coverage Organization/Product/FAQPage (20), server-side rendering vs client-only SPA (15 — a JS-only SPA serves AI crawlers empty HTML), discovery signals og/canonical/sitemap (10), semantic headings single-H1 + H2 structure (10), competitor-comparison content (5). Use to triage why a brand is absent from AI recommendations, as a pre-flight before GEO/AEO content work, or to score a prospect's AI-readiness. Strictly homepage-only — we do NOT crawl. Ethical floor: target's robots.txt is honoured — Disallow: / for ContrastAPI returns 403 error.code = robots_txt_disallow and we DO NOT fetch. Cache-Control: no-store/private skips our cache write (cache_respected=false). Per-target eTLD+1 throttle (60 req/min). Free: 30/hr, Pro: 500/hr. Returns {domain, fetched_url, status_code, llms_txt_present, ai_crawlers_total, ai_crawlers_allowed, ai_crawlers_blocked, schema_types, client_side_rendered, render_framework, has_canonical, og_tag_count, sitemap_count, h1_count, h2_count, comparison_content, score, missing_signals, cache_respected, summary}. Returns 502 on DNS/TCP/TLS failure; 403 robots_txt_disallow when the target opted out.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYesRegistrable domain to audit for AI-visibility / GEO readiness (e.g. 'example.com', 'shopify.com'). No scheme, no path, no port. Strictly homepage-only — the bot fetches https://<domain>/ with HTTP fallback (we do NOT crawl).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already indicate read-only and idempotent behavior, but the description adds substantial context: 'no LLM is queried, fully deterministic', robots.txt honoring with 'Disallow: /' returning 403, cache-control handling, rate limits, and specific error returns (502 on DNS/TCP/TLS). This goes well beyond the annotations.

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 long but well-structured and front-loaded with the core purpose. It packs essential details (scoring rules, ethical behavior, output fields) into a logical flow. Minor redundancy like 'we do NOT crawl' appears, but overall efficient.

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?

The description covers purpose, methodology (7 weighted rules), ethical constraints, throttling, error handling, and the full return object. Combined with rich annotations and an output schema, it provides all necessary context for an agent to select and invoke the tool correctly.

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?

The sole parameter 'domain' is fully described in the input schema (100% coverage), including format ('No scheme, no path, no port') and behavior ('fetches https://<domain>/ with HTTP fallback'). The tool description does not add significant new parameter-level information, so baseline 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 it performs a 'deterministic GEO / AI-visibility readiness audit of a domain's homepage' with a '0-100 score + missing_signals fix list'. It differentiates from siblings by emphasizing 'structural signals ONLY' and 'homepage-only', which distinguishes it from general SEO audits or domain reports.

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?

Explicit use cases are provided: 'triage why a brand is absent from AI recommendations', 'pre-flight before GEO/AEO content work', and 'score a prospect's AI-readiness'. Constraints like 'Strictly homepage-only — we do NOT crawl' signal when not to use, but no alternative tool names are explicitly mentioned, leaving a minor gap.

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

All ContrastAPI toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.5/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, with differences between lookup/search/scan/audit for each domain. However, some overlap exists (e.g., email_mx vs email_security_posture, scan_headers vs contrast_scan) which could cause occasional confusion. Overall, boundaries are well-defined.

Naming Consistency5/5

Tool names follow a consistent verb_noun pattern (e.g., cve_lookup, check_headers, bulk_cve_lookup) with all lowercase underscores. Variations like kev_detail or ssl_check are minor and still predictable. No chaotic mixing of conventions.

Tool Count4/5

54 tools is high but justified by the broad cybersecurity scope (CVE, ATLAS, D3FEND, Sigma, domain, email, IOC, scanning). Some redundancy exists (e.g., three email-related tools), but the count is not excessive given the API's comprehensive feature set.

Completeness5/5

The tool set thoroughly covers the threat intelligence and domain investigation lifecycle: CVE/KEV/exploit/CWE, ATLAS/D3FEND/Sigma, DNS/WHOIS/SSL/subdomains, email security, IOC enrichment, and active scanning. No significant gaps are apparent for the stated cybersecurity purpose.

Resources