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ghost_audit_site

Run Achilles 10-stage ghost audit on any website. Returns SEO gaps, AI discoverability issues, conversion leaks, brand presence gaps, and competitor intelligence. 10 stages: RECON → INFRASTRUCTURE → SEO → PAGE COVERAGE → AI LAYER → CONVERSION → BRAND PRESENCE → COMPETITION → CREATIVE GAPS → SYNTHESIS. Score: 0-100 with CRITICAL/HIGH/MEDIUM/LOW findings per stage. Returns audit_id + stream_url (SSE for live stage-by-stage output) + download_url (full markdown report). Stream starts immediately; full report ready in ~90 seconds. Free: 1 audit/day per IP. Zambo Pass: unlimited. One-time purchase at zambo.dev/ghost-audit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull website URL to audit (e.g., https://yoursite.com). Include https://.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description fully discloses behavior: it returns an audit ID, streams output via SSE, and generates a full report in ~90 seconds. The read-only nature is implied by 'audit,' and rate limits are mentioned. No contradictions present.

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 dense with information but well-structured: purpose first, then stages, then outputs, then limits. It could be slightly shorter, but each sentence adds value. The stage list is clear.

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 tool with one parameter and no output schema, the description adequately covers the audit scope, output formats, and timing. It lacks fine details on finding types but is complete enough for an agent to decide to use it.

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?

The input schema has one param (url) with 100% description coverage. The description adds clarity by requiring 'https://' and providing an example, going beyond the schema's minimal description.

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 runs a '10-stage ghost audit' on any website, specifying the output categories (SEO gaps, AI discoverability issues, etc.) and the stages. This distinguishes it from sibling tools like ghost_audit_report and ghost_audit_status, which handle results separately.

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 usage context: it mentions the free tier (1/day), Zambo Pass for unlimited, and a link for purchase. It also explains the output delivery (stream and download). However, it does not explicitly state when not to use it or suggest alternatives, though the context is clear.

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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TDQS

A3.5/5.0
Disambiguation3/5

Many tools have distinct purposes, but there are several overlapping or redundant tools (e.g., leadsignal vs leadsignal_generate, multiple code audit tools, multiple trading proposal/journal tools, and several 'universal' entry points like zambo_help, zambo_ask, zambo_universal). Descriptions help, but the volume creates ambiguity.

Naming Consistency3/5

Naming conventions vary across prefixes (zambo_, zambot_, axis_, presence_, trading_, etc.), with some tools using single words (weather, translate) and others using verb_noun patterns. Aliases like leadsignal_generate for leadsignal break consistency. While prefixes provide some grouping, the overall pattern is mixed.

Tool Count2/5

125 tools is excessive for a single MCP server, even if the server aims to be a universal stack. This makes it overwhelming for agents to navigate and increases the likelihood of misselection. Many tools could be split into domain-specific servers.

Completeness5/5

The tool surface is extraordinarily comprehensive, covering agent identity, cross-layer orchestration, code analysis, content generation, legal scanning, lead generation, trading, on-chain data, and more. Nearly any common agent task is supported with multiple tools, leaving few obvious gaps.

Resources