Start with an explicit contract

For repeatable results, every prompt should define:
  1. Objective: The decision or output the workflow must produce.
  2. Scope: Domains, hosts, IP ranges, organizations, or CVEs the client may query.
  3. Tools: The FullHunt tools the client may call.
  4. Evidence: Fields and timestamps that must be preserved.
  5. Stopping condition: The point at which the client must stop calling tools.

Separate observations from analysis

Require the client to distinguish fields returned by FullHunt from model-generated conclusions. This is especially important for IP reputation, ownership attribution, vulnerability matching, and brand impersonation. Use an output structure such as:

Control active operations

Most FullHunt tools are read-only lookups. Scan tools initiate work against a target and need tighter controls.
  • Require a user confirmation immediately before a scan call.
  • Match the requested target against an allowlist outside the model.
  • Use only assets you own or are explicitly authorized to test.
  • Record the user, target, purpose, and tool call.
  • For OEM scans, retain scan_id and use oem_scan_status with bounded polling.
  • Do not poll standard or Enterprise scans through a nonexistent status tool.

Keep state outside the conversation

An MCP conversation is not a monitoring database. Store baselines, cursors, last-seen timestamps, deduplication keys, and alert state in your application. For scheduled workflows, persist at least:

Handle limits and failures

  • Call auth_status before large workflows.
  • Set a maximum number of tool calls per run.
  • Retry 429 and transient 5xx responses with exponential backoff and jitter.
  • Do not retry 400, 401, or 403 until the request or configuration changes.
  • Cache stable WHOIS, organization, and advisory data according to your freshness needs.
  • Stop paginating when response metadata indicates the final page.

Protect credentials and sensitive data

  • Keep X-API-KEY out of prompts, repositories, traces, and screenshots.
  • Use a user-level client configuration or secrets manager.
  • Redact passwords and unnecessary personal fields from dark-web results.
  • Limit retention and access to credential-exposure data.
  • Rotate keys after exposure or staff access changes.

Design multi-step research

Use a narrow first query, inspect the result, and then make evidence-driven pivots. Avoid asking the model to call every related tool automatically.

Validate production workflows

Before enabling unattended runs:
  • Test with a fixed input and expected response shape.
  • Verify each tool name against the 63-tool reference.
  • Confirm plan and module behavior with a non-production key.
  • Set time, pagination, retry, and tool-call limits.
  • Review data retention and authorized-scope controls.
  • Add alerts for repeated authentication, entitlement, or rate-limit failures.
Use Data Provenance and Freshness, Responsible Use, and the Agent-Assisted Research guide when designing the surrounding application.