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End-of-Term Report Comment Drafter

Example prompt: "I teach Year 9 English to 28 students. Read each student's grades, effort score, and the lesson notes I've kept in this Google Sheet for the term. For each student, draft a 60–90 word report comment in my voice that names a genuine strength, identifies one specific area to work on, and ends with an actionable target for next term. Put the drafts in a Google Doc grouped by class with a heading per student so I can edit before pasting into the school MIS."

The Problem

End-of-term report writing is one of the most disliked teaching tasks. Subject teachers can be asked to write 60–150 personal comments in a fortnight, and the temptation to fall back on bland sentence stems is strong when you're 40 students in at 11 pm. Generic comments help nobody — parents want to know what their child is actually like in your lessons. The information needed to write a good comment exists in the mark book and lesson notes, but stitching it together for every student, in the teacher's own voice, is what eats the evenings.

How GloriaMundo Solves It

We build a workflow that takes the teacher's own data and produces personal first drafts the teacher can edit. An integration step reads the student list, grades, effort scores, and any lesson notes from the teacher's tracking Google Sheet. A sub-agent step processes the class in parallel, with one child workflow per student. Inside each child, an LLM step drafts a 60–90 word report comment grounded in that specific student's data — naming a genuine strength shown in the notes, identifying one area to develop, and ending with a target. The drafts deliberately match the teacher's voice rather than the model's default tone, by being shown a short sample of comments the teacher has written before. A final integration step compiles the drafts into a single Google Doc grouped by class with a heading per student. Glass Box preview shows every comment before anything is written to the doc, so the teacher can spot a comment that needs more substance and feed in a note before regenerating.

Example Workflow Steps

  1. Trigger (manual): The teacher provides the class, the data sheet link, and a short sample of their previous comments to anchor the voice.
  2. Step 1 (integration): Read each student's row from the tracking Google Sheet — grades, effort score, attendance, and lesson notes for the term.
  3. Step 2 (sub_agent): Spawn one child workflow per student to draft a comment in parallel.
  4. Step 3 (LLM, inside each child): Draft a 60–90 word comment naming a genuine strength, one development area, and a concrete target, anchored in the student's actual data and the teacher's sample voice.
  5. Step 4 (code): Collect the drafted comments back from every child and order them by class register.
  6. Step 5 (integration): Compile the drafts into a single Google Doc grouped by class with a heading per student.

Integrations Used

  • Google Sheets — holds the mark book, effort scores, and lesson notes
  • Google Docs — receives the compiled draft comments ready for review

Who This Is For

Subject teachers, form tutors, and heads of department writing end-of-term, mid-year, or interim reports. Most useful in secondary schools where a single teacher can have 100–150 students to comment on in one reporting cycle, but equally valuable in primary settings where one teacher writes long-form reports across the whole curriculum.

Time & Cost Saved

A subject comment written from scratch takes a careful teacher 5–10 minutes. With 120 comments to write, that's a full working week of evening time. This workflow brings the writing time down to a few minutes per student of review and editing — typically two evenings rather than two weeks. Critically, the drafts are based on the teacher's real notes rather than a generic library of phrases, so the editing is genuine refinement rather than starting over. The workflow uses several LLM calls per student plus integration steps, costing in the order of low single-digit credits per student.