Story-style community daily report

Disclaimer: The content shown on this page is generated by an AI model and is for reference only. It does not constitute any guarantee of results. Actual output and Credits consumption are subject to "Usage Details" in the console.

This playbook runs the full chain on a day's group-chat material: first the text model structures the material into story.json, then locally renders it offline into branded HTML and a PNG long-image daily report, turning community content into a durable asset. Call chain: qwen3.7-max (group-chat material → story.json, official open-source solution group-daily-waytoagi-edu) → local rendering of HTML / PNG long image (offline, does not consume Credits).

Real output

Ran the full chain on a day's group-chat material; the rendered story-style group daily report long image (excerpt):

Step 1: set the editor persona

Use a System Prompt to fix the editor persona and output structure (excerpt):

You are the group-daily-report editor of the WaytoAGI-EDU education community.
Task: Organize the user-provided group-chat material into a renderable story.json.
- Output only one JSON object; do not fabricate names, viewpoints, links, or data that don't exist
- The style is an education-AI co-creation community: warm, story-driven, with characters and a sense of being on the scene; do not write it as meeting minutes
- Each timeline entry contains no/time/badge/cast/theme/story/quotes/output
- footer_quote picks the one sentence that best captures the vibe of the day
Top-level output fields: group_name, date, time_range, lead_title, opening,
timeline, highlights, sops, qas, stats, footer_quote ...

Step 2: attach group-chat material to generate story.json

Use a User Prompt to pass in the day's group-chat material:

Please generate story.json based on the group-chat material below.
Group name: WaytoAGI-EDU Intel Bureau ｜ Date: 2026-07-28 ｜ Time range: 09:18 → 20:10
Safety rule: Do not output any private information such as phone numbers, emails, addresses, or accounts.
Group-chat material:
{Manually organized group-chat text, e.g. [09:18] Sample Teacher A: I have a classroom question today...}

Notes

Consumption: In this playbook only the text-generation step consumes Credits (qwen3.7-max, group-chat material → story.json); the subsequent offline rendering of HTML and PNG long image does not consume Credits.
Cost variance: Consumption varies with the length of the group-chat material—the longer the material, the higher the consumption.

​Real output

​Step 1: set the editor persona

​Step 2: attach group-chat material to generate story.json

​Notes

Real output

Step 1: set the editor persona

Step 2: attach group-chat material to generate story.json

Notes