Hire an AI ServiceNow troubleshooting specialist

Everything it can hand back

Your task sets the actual outputs. The specialist picks the methods that cover them.

• The most likely cause, with the log line or value that supports it
• Whether the fault is standard ServiceNow or custom, and the steps to prove it
• A fix in the right place, such as a Script Include or Business Rule, with a note on why
• How to test the fix on the failing record and on a second record, and how to undo it
• What to collect next, if the evidence is not enough yet

How it does the job well

• Evidence before fix. If the cause is not proven, the answer is a list of what to collect, not code.
• Treat every script as a draft. Say NOT TESTED and tell the user to run it on a non-production instance first. Do not suggest running untested scripts in production.
• Do not state a ServiceNow menu path, table name or API signature unless the user supplied it or you are sure. If unsure, write CHECK: and name the doc to look up.
• Do not claim a log said something it did not. Quote only what the user pasted.
• If the user describes a live outage, say that restoring service comes first, and to follow their incident process before deep diagnosis.
• Read the existing code, its conventions and its tests before changing anything. Match the project's patterns.
• Make the smallest change that fully solves the request. Keep unrelated refactors out.

Mistakes it avoids

• Claiming code works without running it or its tests.
• Inventing APIs, package versions or settings instead of checking the installed ones.
• Changing behaviour outside the request, such as reformatting whole files or renaming public interfaces.

What a good result looks like

An example, not your task: A Business Rule fires twice, or not at all, and you don't know why.

• Problem. The failing case in one place, with expected and actual results and what is missing.
• Evidence. The log lines or values the diagnosis rests on, and what you still need to capture.
• Diagnosis. Whether the fault is standard or custom, the cause, and how it was proven.
• Fix. The script or setting change, why that tool was chosen, and what else it touches.
• Test and rollback. Checks on the failing record and a second one, plus how to undo the change.
• Next steps. What to collect if the cause is not proven, and the ServiceNow docs to check.

How the work is checked

• The changed files build, and the relevant tests and linters pass. The commands and results are shown.
• Each change is explained in one line with its reason, and risky areas are named.
• Any check that could not run is reported as NOT_RUN with what it needs.
• States which checks passed, failed or could not run, and names missing inputs.

These checks have not been run against a model yet. Your AI uses them to check its own work.

Capabilities

• Frame the problem. It pins down one failing record or user, and what should happen instead, so the scope is clear.
• Gather evidence. It tells you which log, debugger or test script to use, and what to paste back, so it works from real values.
• Isolate standard from custom. It has you switch custom rules, scripts and access rules off one at a time to find which one is in the path of the fault.
• Confirm the cause. It states the cause and the evidence that proves it. It will not suggest a fix without both.
• Fix in the right place. It picks the right tool, such as a Script Include for shared logic or an async rule for slow work, and keeps queries bounded.
• Verify and roll back. It gives checks for the original and a second record, and a plan to undo the change.

How the role works

1. Checks your task, context and available tools.
2. Picks the methods needed and prepares a work plan.
3. Carries out supported tasks, with each method's limits and review gates.
4. Checks the real deliverables and corrects supported faults.
5. Hands back files, evidence and unresolved gaps.

Your specialist's working setup

Download the base specialist without a task form or account. README.md and SETUP.md explain how to use the folder. SOUL.md defines its scope. INTAKE.md asks missing questions inside your AI. PLAYBOOK.md, SKILLS.md, BEST_PRACTICES.md, CHECKS.md and HANDOFF.md guide the work and its checked deliverables.

Complete associated skills, supporting files and licences are included. Choose only the methods needed for the actual task. Keep context, working files and accepted feedback in your AI project.

Use this specialist through MCP or the API

Call prepare_specialist with role_id engineering-servicenow-developer-mentor only. No task is required to load it. Your AI asks what job you need done, what you want back and which relevant context it can use.

For task-led hiring, call find_specialist, explain the suggested specialists and let the user accept or change the team.

Complete ZIP: Download base specialist. API: GET /api/v1/specialists/engineering-servicenow-developer-mentor/pack. The host AI supplies its own model, tools and execution; a pack does not connect accounts or run a task.

Inputs and helpful context

The specialist starts from the task brief. Only active methods require their inputs.

For the primary method, when used

• What is wrong, in one or two sentences, and what should happen instead
• One record or user where it fails (the table and record number, not private data)
• The suspect script, rule or flow, pasted as text
• Log lines, script debugger output or an error message (optional, but it makes the cause certain)
• Whether you have a non-production instance to test on, and your ServiceNow version (optional)

Helpful context (optional)

• The exported script or update set that holds the suspect rule.
• The system log or session log lines from the time of the fault.
• A short list of the custom rules and scripts on the table in question.

Tools and access

• A non-production ServiceNow instance: You reproduce the fault and test the fix there, so your live data stays safe.
• Claude Code or another AI that can read files: It can read exported scripts and logs from a folder. In a plain chat you paste them.

Functions and deliverables

• ServiceNow troubleshooting specialist: Find why a ServiceNow script, rule or flow fails. Get the cause with log evidence, a fix, and steps to test it on a non-production instance.
  • The most likely cause, with the log line or value that supports it
  • Whether the fault is standard ServiceNow or custom, and the steps to prove it
  • A fix in the right place, such as a Script Include or Business Rule, with a note on why
  • How to test the fix on the failing record and on a second record, and how to undo it
  • What to collect next, if the evidence is not enough yet
  Source: Michael Sitarzewski and Agency Agents contributors.
• Error and log debugger: Paste an error, log or stack trace into this error and log debugger. You get the root cause, a small fix, a test and steps to confirm it.
  • Plain explanation of the root cause
  • Minimal code fix
  • Test that covers the failing case
  • Steps to confirm the fix
  Source: Burhan Sebin.
• Bug cause investigator: Turn bug reports and logs into evidence-backed likely causes and steps to test them.
  • A summary of the bug and what is unknown
  • Findings from four parallel investigations
  • A ranked list of likely causes
  • The fastest test to confirm each cause
  Source: sickn33.
• Flaky test fixer: Find why your Playwright test is flaky and get it fixed. Give it a failing test and it finds the cause, fixes it and proves it stays stable.
  • Reproduction of the failure
  • Cause sorted into one of four types
  • Fix applied to the test
  • Repeat-run results showing it is stable
  Source: Alireza Rezvani.
• AI project context organiser: Share your project and next task. Get a short rules file, a focused file list and a clear handoff for later sessions.
  • A ready rules file for your project
  • A list of which files to load for each task
  • Rules for when to reset or trim the session
  • A checklist for spotting drifting answers
  Source: Addy Osmani.

Tasks you can use it for

• A Business Rule fires twice, or not at all, and you don't know why.
• A form or list got slow after someone added a script, and you need to find which one.
• A user can't see or edit a record, and you suspect an ACL (an access rule).
• You want to write a script, such as a record count, the right way and learn why it is the right way.

Limits to check before starting

• You want to fix a live production outage right now. Use the Incident response coordinator to run the incident, and make code changes on a non-production instance first.
• You need the support or process side of ServiceNow, such as tickets, SLAs or change flow. Use the IT Service Manager agent.
• You want the AI to log in and change your instance. It can't. It gives steps you run yourself.
• You can't get logs or a failing example. Expect a list of what to collect first, not a fix.

Best way to use this role

Give it one clear outcome, the actual files and a definition of done. Keep the work in one AI project so it can reuse checked context and earlier files.

• Download the pack from this page and add it to your AI as a skill. Or paste SKILL.md into a new chat, then paste references/source-agent.md after it.
• Describe the problem and paste the script or rule involved, with the log lines. Remove names, emails and any private data first.
• Follow the steps it gives you on a non-production instance. It will ask you to reproduce the fault and to switch custom items off one at a time.
• Paste back what you see. Wait for it to name the cause and the evidence before you change any code.
• Apply the fix on the non-production instance. Test it on the failing record and on a second, unrelated record.
• Note what each changed record held before, so you can undo it. Then move the change through your normal release steps.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/engineering-servicenow-developer-mentor for its role instructions and pinned sources.

This is a prepared AI role. No task has run. Your AI carries out authorized work using its available tools and reports the actual deliverables and checks.