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arian-gogani

Nobulex MCP Compliance Server

get_audit_log

Retrieve the complete hash-chained audit trail of all compliance checks to maintain a tamper-evident record of actions and verify integrity.

Instructions

Returns the full hash-chained audit trail of all compliance checks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Registration and handler implementation for the "get_audit_log" tool within src/index.ts. It calls the AuditLog.getAll() method to retrieve the logs.
    server.tool(
      "get_audit_log",
      "Returns the full hash-chained audit trail of all compliance checks.",
      {},
      async () => {
        const entries = auditLog.getAll();
        return {
          content: [
            {
              type: "text" as const,
              text: JSON.stringify({ count: entries.length, entries }, null, 2),
            },
          ],
        };
      }
    );
  • Helper method inside the AuditLog class in src/audit.ts that retrieves all audit log entries.
    getAll(): AuditEntry[] {
      return [...this.entries];
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'full hash-chained audit trail', hinting at data structure and completeness, but fails to address critical aspects like whether this is a read-only operation, potential performance impacts, rate limits, or authentication requirements for a compliance-related tool.

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?

The description is a single, efficient sentence that front-loads the core purpose ('Returns the full hash-chained audit trail') without any fluff. Every word earns its place, making it highly concise and well-structured for quick comprehension.

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

Completeness2/5

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

Given the complexity of audit trails and compliance checks, the description is insufficient. With no annotations and no output schema, it lacks details on return format (e.g., structure of the hash chain), data volume, or error handling. This leaves significant gaps for an agent to use the tool effectively in a compliance context.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, avoiding redundancy. A baseline of 4 is applied since it doesn't need to compensate for any schema gaps.

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 description clearly states the tool's purpose with a specific verb ('Returns') and resource ('full hash-chained audit trail of all compliance checks'), making it immediately understandable. However, it doesn't explicitly distinguish this tool from its siblings like 'verify_log', which might also deal with audit logs, leaving room for ambiguity.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'check_action' or 'verify_log'. It lacks context about prerequisites, timing, or scenarios where this tool is preferred, leaving the agent to infer usage from the purpose alone.

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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