Hire an AI staff policy explanation and rollout writer

Everything it can hand back

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

• A plain explanation of each change, with a short answer, details, exceptions and the policy section
• A draft announcement to staff for the policy owner to review
• A rollout list of sign-offs and training, each with an owner and date still to fill
• Questions for the policy owner where the text is unclear
• A list of facts still MISSING

How it does the job well

• Turn every request into owned actions: who, what and by when.
• Work from the real calendar, notes and lists. Never invent meetings, people or dates.
• Put the most important decision or deadline first, then the details.
• Prepare drafts and proposals. Sending, booking and changing records waits for approval.

Mistakes it avoids

• Losing commitments buried in long notes.
• Mixing confirmed facts with guesses about other people's plans.
• Adding process when a short checklist would do.

What a good result looks like

An example, not your task: HR or a manager has approved a policy change and you must tell the whole team.

• outputs/step-01-company-policy-explainer.md. Each change in plain words, with short answer, details, exceptions and the policy section.
• outputs/step-02-stakeholder-update-writer.md. The staff announcement and the rollout list of sign-offs and training, each with an owner to fill in.
• Questions for the owner. Each unclear clause, with why it matters and who can settle it.
• HAND-BACK SUMMARY. Files saved, sources used, MISSING lines, checks missed and one suggested next step.

How the work is checked

• Obligations and exceptions from the policy are all kept, in plain words.
• Every date, role and number traces to the policy or the change list.
• Unclear clauses are in the owner's question list, not decided.
• The announcement is a draft, and nothing was sent.
• 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

• Company policy explainer. Writes one entry per change in plain words, with a short answer, the details, exceptions and the quoted policy section. Uses examples taken only from the policy. Hands step 2 the explanations and the open questions. Check before moving on, nothing a rule requires or allows was dropped.
• Stakeholder update writer. Writes the announcement for staff from the step 1 entries, and lists each acknowledgment or training that still needs an owner. Check before you send, the start date and who is affected match the policy.

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 make-a-new-policy-understandable-to-staff 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/make-a-new-policy-understandable-to-staff/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

• The approved policy text, with its version and start date
• The policy owner's list of what changed, from what to what
• The roles or teams the policy affects
• The policy owner's name or role, so staff know who to ask
• Any sign-off or training the policy needs (optional)

Helpful context (optional)

• The old version of the policy, so changes can be shown side by side.
• Questions staff have already asked.

Tools and access

• A chat AI that reads documents: It can read the full policy and the change list together. In plain chat, paste the changed sections.
• Any good chat AI: It only needs your notes pasted in. A tracker connection is a bonus, not a need.

Functions and deliverables

• Staff policy explanation and rollout writer: Share the approved policy, confirmed changes and start date. Get a plain explanation, staff questions answered and a rollout action list.
  • A plain explanation of each change, with a short answer, details, exceptions and the policy section
  • A draft announcement to staff for the policy owner to review
  • A rollout list of sign-offs and training, each with an owner and date still to fill
  • Questions for the policy owner where the text is unclear
  • A list of facts still MISSING
• Company policy explainer: Ask a plain question about leave, travel or expenses. Get your company policy explained in plain words, with the section it came from.
  • The rule in plain words
  • The section it came from
  • Steps to follow, such as who to ask or what form to file
  • A note when HR should confirm
  Source: Anthropic.
• Stakeholder update writer: Turn your rough progress notes into a weekly, monthly or launch update for leaders, engineers, partners or customers, sized to the reader.
  • A draft update sized to your reader, ready to paste
  • A status colour with a one-line reason
  • Each risk with a plan or an owner
  • Each decision with options and a recommendation
  • A list of facts you still need to add
  • A version for a second reader (optional)
  Source: Anthropic.
• Staff announcement writer: Say what is changing. Get a clear internal announcement, a rollout plan and answers to likely questions.
  • A plain announcement
  • One version for each channel you use
  • Talking points for managers
  • A FAQ of 5 to 8 questions
  • A rollout order with timing
  Source: Tuan Duc Tran.
• 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

Tasks you can use it for

• HR or a manager has approved a policy change and you must tell the whole team.
• Staff keep asking what the new expenses, leave, remote work or conduct rules mean for them.
• The policy is correct but too long and too formal for most people to read.
• You need a list of who must sign or train before the start date.

Limits to check before starting

• The policy is still being drafted or reviewed: finish approval first. This works from the approved text.
• You need the official reading of a rule for a dispute: ask the policy owner or a lawyer. This explains, it does not rule.
• You want to know whether staff understood it after launch: use the Policy adoption support planner workflow.
• You only need to answer one staff question on an existing policy: use the Company policy explainer on its own.

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 workflow pack and add it to Claude, ChatGPT or Gemini, in a chat that accepts files.
• Attach the approved policy. Paste the policy owner's change list and say who is affected and when it starts.
• Tell your AI to follow the pack and save each step's file.
• After step 1, read each explanation against the policy. Every duty, limit and exception must still be there. Send the owner any unclear points.
• After step 2, fill in the owner and date on each rollout item. Have the policy owner approve the announcement before you send it.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/make-a-new-policy-understandable-to-staff 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.