Daily Standup Prep

Use the Dagu skill to create a daily standup preparation workflow. Refer to the schema, coding agent, and pitfalls references for correct syntax. Ask the user: - How many days back should the report cover? (default: 1) - What time should it run on weekdays? (default: 8:00 AM) - Which AI coding agent CLI do they have installed? (check for claude, codex, gemini, opencode, aider in that order — use the first one found, or ask if none detected) Prerequisites: gh CLI authenticated (gh auth login), at least one AI coding agent CLI installed. The workflow should: 1. Fetch the user's GitHub activity using gh api graphql with --jq for server-side JSON formatting (do NOT use jq CLI). Fetch commits per repo (with messages via REST), merged PRs (with body), open/draft PRs updated in the period (with recent commits and timestamps, grouped by repo), and reviews. 2. Auto-discover all organizations from the activity and group everything by org. 3. For each org with activity, use an inline sub-DAG (--- separator) to generate a spoken standup draft using the user's AI agent CLI. Use the cheapest/fastest model available for that agent since this is a simple text summarization task. Skip the call entirely for orgs with no activity to avoid wasting tokens. 4. The agent command, model, and draft prompt should all be defined as top-level env variables (use YAML multiline | for the prompt) so users can easily swap agents or customize the output without editing step logic. 5. Assemble each org section as markdown: spoken draft, merged PRs, open PRs grouped by repo with commit history and timestamps, and reviews. 6. Combine all org sections into a single report saved to DAG_DOCS_DIR. 7. Schedule on weekdays with catchup, retry defaults, and timeouts on agent steps. Important: review the pitfalls reference for known workarounds. Follow the coding agent reference for the correct non-interactive command and model flags for each agent CLI.