Retrieve the full markdown report for a completed Ghost Audit. Returns the complete Achilles 10-stage report: score (0-100), all CRITICAL/HIGH/MEDIUM/LOW findings, stage-by-stage analysis, and actionable fixes. Call ghost_audit_status first to confirm the audit is complete. Free: 1 audit/day. Pass: unlimited.
| Name | Required | Description | Default |
|---|---|---|---|
| audit_id | Yes | The audit_id returned by ghost_audit_site |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It implies read-only retrieval but doesn't explicitly state non-destructiveness or authentication requirements. Rate limits are mentioned, but overall disclosure is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four sentences, well-structured: purpose first, then details, prerequisite, rate limits. No unnecessary words, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, but description thoroughly explains return value (full markdown report with score, findings, analysis, fixes). Covers prerequisites and rate limits. Complete for a retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage for the single parameter audit_id is 100%. The description adds context by specifying that the audit_id comes from ghost_audit_site, which clarifies its origin and ensures correct usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a full markdown report for a completed Ghost Audit, listing specific contents (score, findings, analysis, fixes). It distinguishes from siblings like ghost_audit_status (checks completion) and ghost_audit_site (initiates audit).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call ghost_audit_status first to confirm completion, and mentions rate limits (Free: 1 audit/day, Pass: unlimited). Provides clear context on when and how to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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 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.
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.
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.