Hire an AI study practice progress reviewer

Everything it can hand back

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

• A dated progress review showing what is done, on track and behind
• The mistakes that keep repeating, taken from your real answers
• An adjusted plan for the next one to two weeks, with what was kept, moved or dropped
• The next understanding check, written but not run
• A list of what is missing, and a review log for next time

How it does the job well

• Practice answers are evidence. Confidence is not mastery. Never write that a topic is mastered from a feeling alone.
• Never invent a learner's answers, scores or session notes. If the learner is not present, review only the answers supplied and write the next check without running it.
• Do not promise a score improvement or a result on the exam.
• Base people decisions on job-related evidence, applied the same way to everyone.
• Write in plain, respectful language the person affected could read.
• Keep personal data to what the task needs, and handle it privately.
• Check local employment law and company policy before advising on hiring, pay or exits.

Mistakes it avoids

• Treating "I feel ready" as proof.
• Rebuilding the whole plan when one topic needs work.
• Repeating an old recommendation as a new finding.
• Keeping personal records the review does not need.
• Biased wording in job ads, reviews or interview questions.
• Plans with no owner, timing or way to check progress.

What a good result looks like

An example, not your task: You have a study plan and a week of sessions behind you, and want to know if the plan still fits.

• progress-review.md. What is done, on track and behind against your plan, with dates.
• error-patterns.md. The mistakes that repeat across your real answers, and which topic each belongs to.
• adjusted-plan.md. Your next one to two weeks of sessions, marking what was kept, moved, added or dropped and why.
• next-check.md. Questions on your weak topics, written but not run, with what a good answer shows.
• review-log.md. Missing facts, checks not done, what changed since last time and the state for the next review.

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.

Capabilities

• Read the last state. It keeps your goal, topic, last practice date, observed mistakes and the next check you planned. The first run sets a baseline.
• Check what triggered the review. A checkpoint is due, practice showed a new gap or your free time changed.
• Read your real answers. It uses the Study understanding check on your recent answers. Without answers, it reviews only what you supplied.
• Decide what to change. It keeps what works. It reworks the plan only for a missed prerequisite, a repeated mistake or new free time.
• Write the next check. It prepares questions on the weak topics. It does not run them or invent your answers.
• Save the review. It records what changed, what is missing and the state for next time.

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 study-plan-progress-review-assistant 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/study-plan-progress-review-assistant/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 learning goal and your exam or deadline date
• Your current study plan
• The sessions you finished, with dates and topics
• Your real practice answers or scores, by topic
• The hours you have free now
• Your last review file (optional)

Helpful context (optional)

• Past exam papers or practice sets you have already done.
• Your teacher's or tutor's feedback.
• A note on when in the day you study best.

Tools and access

• Claude, ChatGPT or Gemini with file upload: It reads your plan, your answers and your last review together.
• Claude, ChatGPT or Gemini with web access: Web access lets the AI confirm that suggested readings exist. Without it, readings are marked unverified. They read the pasted text or files and keep each step's result as a file. None of them can run a lesson, a class or a check for you.

Functions and deliverables

• Study practice progress reviewer: Review actual practice answers and available study time. Keep what works and adjust the next practice for observed gaps.
  • A dated progress review showing what is done, on track and behind
  • The mistakes that keep repeating, taken from your real answers
  • An adjusted plan for the next one to two weeks, with what was kept, moved or dropped
  • The next understanding check, written but not run
  • A list of what is missing, and a review log for next time
• Study roadmap and weekly session planner: Map what you need to learn, choose practice methods and fit sessions with recall checks into your available time.
  • A roadmap of topics in order, with what to know first and a checkpoint for each
  • A study method for each part of the material, and the habits to drop
  • Weekly sessions with minutes, tasks and questions to answer from memory
  • An opening goal, a method check and a closing reflection for each type of session
  • A summary of anything missing, such as readings that could not be confirmed
• Study understanding checker: Check your understanding after you study. Share your notes or a chapter and get questions or a worked practice problem, plus feedback on each answer.
  • Four to six numbered questions that ask you to apply, explain, connect, spot an error or predict
  • A step-by-step worked example, if you want to practise a method
  • A slightly harder practice problem for you to solve
  • Short feedback on each answer: what is right, where the reasoning went off and a hint
  • A summary of what is solid, where the gaps are and where to look in the source
  Source: Jacquard Labs.
• Study revision coach: Plan your exam revision in one session. Share your topics, past mistakes and deadline, and get a ranked review plan that starts with your weakest topics.
  • A ranked revision plan with clear priorities.
  • Recall prompts and practice exercises.
  • A summary of passed checks and topics still needing review.
  Source: edu-agent-skills contributors.
• 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

• You have a study plan and a week of sessions behind you, and want to know if the plan still fits.
• A practice test showed a gap you did not expect.
• Your free time changed, for example a new job or a closer exam date.
• You tutor or parent a learner and want a weekly review built from their real answers.

Limits to check before starting

• You have no plan yet. Use the Study roadmap and weekly session planner workflow.
• You want to check one topic today. Use the Study understanding checker on its own.
• The learner has no practice answers yet. Do a session first, then come back to this.

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. If you cannot add it, paste SKILL.md into a new chat.
• Paste or attach your goal, deadline, current plan and the sessions you finished. Add your real practice answers, even if some are wrong.
• Tell it how many hours you have free now. Attach your last review if you have one.
• Say "Review my progress and adjust the plan. Do not invent any answers." Your AI asks once for anything missing.
• Read progress-review.md and error-patterns.md first. Check that the mistakes it lists match your own answers.
• Do the next check in next-check.md, then bring your answers to the next review.

Read it as data

Read the complete role setup as JSON. Connect your AI to the AI Blocks MCP library and read aiblocks://roles/study-plan-progress-review-assistant 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.