Hire an AI organizational psychologist

Everything it can hand back

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

• Three to five findings, each with the evidence behind it and how sure the agent is.
• Other explanations to rule out before you act.
• Up to five fixes in the order to try them, with what could go wrong.
• A way to check each fix worked, such as a short anonymous survey.
• A list of gaps in the evidence and checks still needed.

How it does the job well

• Describe conditions, not characters. Never label a named person with a trait, a disorder or a clinical term.
• You are not a clinician or a lawyer. If the evidence suggests someone is in distress, say to contact an employee assistance program or a qualified professional. Do not assess or advise on treatment. Send disputes, discipline, discrimination and harassment questions to HR or an employment lawyer.
• Protect people. Never suggest ways to trace who said what in a survey or one-to-one. Aggregate and keep it anonymous.
• Evidence over pop psychology, always. Every diagnosis and intervention ties to a validated framework or peer-reviewed finding. If something is anecdote or folk wisdom, say so explicitly rather than dressing it up as science.
• Diagnose conditions, not characters. Frame problems in terms of systems, incentives, and psychological needs — never as fixed personality flaws. Avoid armchair clinical labels for individuals.
• Respect the intervention sequence. Foundations come first: build trust before expecting healthy conflict, establish psychological safety before demanding candor. Never recommend a top-of-pyramid fix for a base-of-pyramid problem.
• Stay in your lane on clinical matters. You address workplace dynamics and wellbeing, not diagnosis or treatment of mental illness. When signals suggest clinical concern, direct people to EAPs and qualified professionals.

Mistakes it avoids

• Biased wording in job ads, reviews or interview questions.
• Plans with no owner, timing or way to check progress.
• Treating a template as legal advice.

What a good result looks like

An example, not your task: Two people left this quarter and you want to know if it was pay or something else.

• Question and evidence. What you asked, each piece of evidence marked as fact, said or guess, and what is missing.
• Findings. Three to five patterns in how the team works, each with its evidence and a confidence rating.
• Other explanations. Other causes to rule out for each finding, and how to check them.
• Fixes in order. Up to five actions with an owner, a time to try, a sign it works and a risk.
• How to check it worked. A measure for each fix, such as a short anonymous survey, and when to look.
• Assumptions and checks still needed. Gaps in the evidence and which items need HR or a qualified professional.

How the work is checked

• Criteria are written down before people are assessed.
• Every plan has milestones and owners.
• Sensitive steps are marked for human and legal review.
• 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.

A second opinion

Before it hands back, your AI reviews the draft the way Eric Ries and Taiichi Ohno would. This is a way of reviewing the work. It does not mean they wrote or endorse it.

Capabilities

• Check the evidence. It lists what you gave it and rates each item as a fact, something people said, or a guess. It names what is missing.
• Pick the lenses. It chooses one to three lenses from the profile that fit your question, such as psychological safety or burnout risk, and says why.
• Write the findings. Each finding names a pattern in how the team works, quotes the evidence, says how sure it is and lists other causes.
• Order the fixes. It puts fixes in the order the profile says they must go, with trust first, and says what could backfire.
• Plan the check. It adds a way to see whether each fix worked, using anonymous, grouped survey results.
• Mark the limits. It names what it could not judge and sends HR disputes, individual cases and crisis signs to the right professional.

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 organizational-psychologist 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/organizational-psychologist/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

• Your team in a few lines, with its size, what it does and how long it has worked together.
• What worries you, in one or two sentences.
• Any evidence you have, such as survey scores, exit notes or workload numbers (optional, but it makes the review stronger).
• What you can change, and how much time you have.

Helpful context (optional)

• Results from your last team survey, with names removed.
• Exit interview notes or reasons people gave for leaving.
• Rough workload facts, such as hours worked and holidays taken.

Tools and access

• Claude, ChatGPT or Gemini with file upload: You can attach survey exports and notes so each finding points to real evidence.
• A survey tool you already use, such as Google Forms or Microsoft Forms: Send the short survey the profile describes, then paste the grouped totals back for a second review.

Functions and deliverables

• Organizational psychologist: Get a team health review on why people go quiet, burn out or leave. Each finding comes with evidence, and the fixes come in the order to try them.
  • Three to five findings, each with the evidence behind it and how sure the agent is.
  • Other explanations to rule out before you act.
  • Up to five fixes in the order to try them, with what could go wrong.
  • A way to check each fix worked, such as a short anonymous survey.
  • A list of gaps in the evidence and checks still needed.
  Source: Michael Sitarzewski and Agency Agents contributors.
• Five whys session planner: Plan a five whys review after a failure. Give it what went wrong and get who must attend, a trigger rule, ground rules and a no-blame agenda.
  • One class of failure and a trigger rule
  • A list of who must attend and why
  • A moderator and ground rules
  • A one-page agenda
• Azure service health investigator: Find out why an Azure resource is unhealthy. Give it the resource name and symptoms. You get log findings and a fix plan by priority.
  • A health status for the resource, with the issues ranked by severity
  • Log findings that show where errors and slowdowns come from
  • A likely root cause for each major issue
  • A fix plan in three phases, with commands, checks and ways to undo each change
  • Alert and dashboard ideas to catch the problem sooner
  Source: GitHub Copilot community.
• Order risk review rule planner: Share order numbers, payment disputes and review time. Get draft risk rules, checks of current defaults and limits to confirm with your payment provider.
  • Rules for low, medium and high risk
  • A review checklist for held orders
  • A chargeback watch line
  • A monthly loop to tune the rules
• me.md builder: Answer a few questions, or let your AI use what it remembers. Get one private file that tells any AI who you are.
  • One me.md file with up to ten dated sections
  • A list of facts taken from memory, for you to check
  • A short note of what it removed for privacy
  • The two next steps, to save it and set it up
• Eric Ries: Turn a product plan into testable guesses using Eric Ries’s public approach. Start with the riskiest assumption and measure what customers actually do.
  • Your problem worked on the way Eric Ries would: their questions, their method, their push-back
  • The answer or the work, in Eric Ries's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step
• Taiichi Ohno: Review workflow waste or a recurring defect using Taiichi Ohno’s recorded approach. Observe the work, inspect handoffs and plan one small improvement test.
  • Your problem worked on the way Taiichi Ohno would: their questions, their method, their push-back
  • The answer or the work, in Taiichi Ohno's voice, using their ideas by name
  • Anything that goes beyond their public record, marked
  • One suggested next step

Tasks you can use it for

• Two people left this quarter and you want to know if it was pay or something else.
• Team meetings go quiet and nobody pushes back on ideas, even bad ones.
• A team keeps working long hours and you want to spot burnout early.
• You start leading a new team and want the right questions for your first 90 days.

Limits to check before starting

• You need to settle a dispute between two named people or decide on discipline. Talk to your HR lead or an employment lawyer.
• You want to plan your regular check-ins with one person. Use the One-on-one meeting planner.
• You want to write down how your team should work. Use the Team culture memo writer or the Company values and culture builder.
• Someone shows signs of a mental health crisis. Point them to your employee assistance program or a qualified professional.

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 your team and what worries you. Paste the evidence you have. Use roles instead of names.
• Answer the questions it asks once. Anything you cannot answer is marked MISSING in the result.
• Read the "other explanations" list first. Rule out easy causes, like a recent change in pay or tools, before you act.
• Try the first fix only. Check it after a few weeks with the measure the agent gives you, then move to the next one.
• Take anything about one named person, or any sign of crisis, to HR or a qualified professional.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/organizational-psychologist 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.