Hire an AI work commitment and follow-up writer

Everything it can hand back

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

• A list of commitments marked new, changed, unchanged or blocked, each with its source note and date
• Follow-up drafts only for tasks that are due and still need a message, with To, subject and body
• A short work brief: what changed, what is due and what you are waiting on
• Updated agent-state.json and decision-log.md files, or the same text to save in a note
• Missing facts, and one next action

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: A weekly team meeting just ended and its notes should update the action list you already keep.

• STATE. The date and timezone, plus whether this run was a first run or found new, changed, unchanged, pending or blocked work.
• PATH. Which skill ran and why, and which skills were skipped.
• CHANGED COMMITMENTS. Each task with its owner, due date, status (new, changed, unchanged or blocked) and the note it came from.
• DRAFTS (not sent). Follow-up drafts for due tasks that still need a message, with who it goes to, subject and first line.
• BRIEF. What changed, what is due and what you are waiting on.
• MISSING. Each gap in the facts and what it stops the agent from doing.

How the work is checked

• Every action has an owner and a date, or is marked as missing one.
• Each item points to the note or message it came from.
• The output fits where it will be used, such as one screen or one page.
• 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

• Compare saved state. Checks the source IDs, dates and task IDs in the new notes against the last saved state, to see what changed since the last run.
• Pick one path. No state means build the action list and a first brief. New notes mean update only the affected commitments. Tasks newly due mean draft follow-ups for the ones that still need a message. Nothing changed means keep the old list and return no new work.
• Run only that skill. Uses the Executive action register keeper, the Due task follow up drafter or the Executive daily briefing writer, whichever the path needs. It does not run all three each time.
• Save the decision. Writes the evidence, the gaps and one next action to the decision log. Task status changes only on evidence, so a draft or a sent reminder never marks a task done.

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 executive-work-keeper 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/executive-work-keeper/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

• New notes since the last run: meeting notes, a transcript or email threads, pasted in or attached (only the ones in scope)
• Your saved action list as a CSV, a spreadsheet export or pasted text, with task, owner, due date and status (skip it on the first run)
• The two state files from last time, agent-state.json and decision-log.md, in a folder you choose (optional on the first run; in a plain chat, paste them back)
• Today's date and your timezone
• Who may be contacted, and the tone you want for drafts (optional)

Helpful context (optional)

• The same action list columns every run (task, owner, due date, status)
• Your timezone and the date, so relative dates like "next Friday" are read correctly

Tools and access

• Claude, ChatGPT or Gemini with file upload: Reads your notes, action list and the two state files, and returns them updated. In a plain chat, paste the state back each time.
• Google Sheets or Excel: Keep the action list as a sheet with task, owner, due date and status columns, and export it as CSV for each run.

Functions and deliverables

• Work commitment and follow-up writer: Keep an action list in step with new notes. Get due follow-up drafts and a brief of what changed.
  • A list of commitments marked new, changed, unchanged or blocked, each with its source note and date
  • Follow-up drafts only for tasks that are due and still need a message, with To, subject and body
  • A short work brief: what changed, what is due and what you are waiting on
  • Updated agent-state.json and decision-log.md files, or the same text to save in a note
  • Missing facts, and one next action
• Action item tracker: Share meeting notes or email threads. Get action items with owners, deadlines and unresolved commitments.
  • action-register.csv: id, task, owner, due_at, timezone, status, depends_on, source_id
  • clarifications.md
  • proposed-task-changes.md
• Task follow-up writer: Share dated tasks and their message threads. Get recipient-specific follow-up drafts, missing facts and a clear draft/sent status.
  • follow-up-drafts.md with task ID, thread ID, recipients, subject and body for each draft
  • draft-ledger.csv with the version, state and message ID of each draft
  • A list of missing facts and approvals you still need to give
  • A short close with source coverage and one next step
• Daily executive brief writer: Share your calendar, action list and updates. Get a dated brief of priorities, decisions, conflicts and work waiting on others.
  • daily-brief.md: date, timezone, source coverage
  • Top priorities and why
  • Meetings, due work, decisions, waiting-on items
  • Changes, gaps and next action
• 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

• A weekly team meeting just ended and its notes should update the action list you already keep.
• A client email moved a due date and you need to know which commitments it touches.
• Three tasks passed their due date and you want follow-up email drafts to the right people.
• You keep an action list in a spreadsheet or a note and want it checked against new notes each week.

Limits to check before starting

• You have notes and want an action list once, with no saved state. Use the Action item tracker keeper.
• You only want today's priorities from your calendar. Use the Daily executive brief writer.
• You want one follow-up email drafted from one thread. Use the Task follow-up writer.
• You expect it to send emails, update your task app or run every morning. It prepares drafts and files only. You send, and you set any schedule.

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.

• Open Claude, ChatGPT or Gemini and add the pack, which holds this agent and its three skills. Add all three. If one is missing, the agent says so and reads it from its page. If your AI can't keep files, paste the agent first.
• First run: paste your notes or action list and say there is no saved state. Pick a folder for the two state files, or ask for them as text to save in a note.
• Later runs: paste the new notes and the saved state files, then give today's date and your timezone.
• Check the line that says which path ran. If you gave it new notes and it says nothing changed, ask it to show which notes it read.
• Read every draft before you use it. Check the recipient, the date and any promise. Send it yourself, and mark the task done yourself.
• Save the new state files. You will paste them in next time.

Read it as data

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