Weekly Report

Weekly Report

> 🚨 OUTPUT CONTRACT: Every execution MUST produce a clickable report URL. A text-only summary without a URL = FAILED. If scripts fail, report the error — do NOT fall back to plain-text.

> ⚠️ SILENT OPERATION: Never narrate internal actions to the user. Just do it and respond with the result.

> 🚨 ALL reports use template+data separation. generate-report-html.py outputs JSON data. The HTML template renders client-side. WRITING HTML YOURSELF IS FORBIDDEN.

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Principles

1. Show, don't lecture. Let data speak. Short commentary.
2. Celebrate consistency over perfection. 5/7 is great — don't dwell on the 2.
3. One week is noise, trends are signal. No dramatic single-week conclusions.
4. Personalize everything. User's name, foods, goals — never generic.
5. Actionable > informational. Suggestions must be doable next week.

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Execution Flow

Step 1: Get Date Range

python3 {diet-tracking-analysis:baseDir}/scripts/nutrition-calc.py local-date --tz-offset {tz_offset}

Use current_week (monday–sunday) as report range. Never calculate dates yourself.

Step 2: Gate Check (cron only)

bash {baseDir}/scripts/should-send-report.sh --workspace-dir {workspaceDir}

If output starts with "no" → reply NO_REPLY. Stop.

Step 3: Collect Data (once, reuse in Step 6)

Read PLAN.md (or health-profile.md) to extract targets for --targets:

• protein_range: daily protein grams [min, max] — pass if explicitly stated
• fat_range: daily fat grams [min, max] — pass if explicitly stated
• carb_range: daily carb grams [min, max] — pass if explicitly stated

Calorie target: Do NOT estimate or convert single values into ranges yourself. Only pass cal_min if PLAN.md already has an explicit range (e.g. "1138 - 1390"). If PLAN.md only has a single value (e.g. "1264 kcal"), omit cal_min — the script will read it and convert to ±10% range automatically.

Pass whatever you find verbatim; the script fills all missing fields from health-profile as fallback.

python3 {baseDir}/scripts/collect-weekly-data.py \
  --workspace-dir {workspaceDir} \
  --start-date {monday} --end-date {sunday} --tz-offset {tz_offset} \
  --targets '{"protein_range":[min,max],"fat_range":[min,max],"carb_range":[min,max]}' \
  2>/dev/null > /tmp/weekly-data-{username}.json

This outputs ALL data as JSON. Do NOT call individual scripts per-day. Save to a temp file (use workspace username to avoid multi-user collision) — you'll read it now for analysis and pipe it to the report generator in Step 5.

Step 4: Read Context

• USER.md → name, health flags, language preference
• health-profile.md → unit preference
• Previous report log: data/logs/weekly-report-{prev_monday}.json → check next_week_focus

All calorie/macro targets, weight loss rate, phase, progress bar, and week number are already in the collect output (meta.* and plan.*). No need to read PLAN.md separately.

Step 5: Generate Report

cat /tmp/weekly-data-{username}.json | \
python3 {baseDir}/scripts/generate-report-html.py \
  --output {workspaceDir}/data/reports/weekly-data-{start_date}.html \
  --workspace-dir {workspaceDir} \
  --nickname {user_nickname} \
  --tagline '{short fun summary of the week}' \
  --plan-rate {weight_loss_rate_per_week} \
  --commentary '{JSON object}' \
  --highlights '{JSON array}' \
  --suggestions '{JSON array}'

Script stdout = report URL. Capture it.

What the script does automatically:

1. Generates JSON data file
2. Copies latest + template to reports dir
3. Uploads 3 files to cloud storage
4. Writes report log
5. Outputs public URL

What YOU provide:

| Param | Description | |-------|-------------| | --nickname | User's display name (from USER.md) | | --tagline | Short witty one-liner summarizing the week (spoken Chinese, like a friend roasting with love) | | --commentary | JSON: {"logging": "...", "calories": "...", "weight": "...", "macros": "..."} — 2-4 sentences each, casual spoken Chinese, funny/witty, backed by real numbers | | --highlights | JSON array: 2-3 specific data-backed wins | | --suggestions | JSON array of strings: 1-2 concrete actionable improvements. Each element MUST be a plain string like "🍽 标题：描述", NOT an object. | | --plan-rate | kg/week — use meta.plan_rate from collect output (default 0.5) | | --lang | Report language: zh (default) or en. Read from user's profile or infer from conversation language |

> 🚨 ALL parameters are REQUIRED with real content. Empty '{}' or '[]' = degraded experience. Read the data, think, write real commentary.

For section-by-section rules: read references/report-sections.md For edge cases (zero data, no plan, ED flags): read references/edge-cases.md

Step 6: Compose Chat Message

Use values directly from collect output (meta.*):

📊 第{meta.week_number}周周报
完整分析 👇
{report_url}

{meta.progress_bar} 已走 {meta.progress_pct}%
{meta.start_weight} → {meta.current_weight} {unit} → 目标 {meta.target_weight} {unit}

{data_hook}

• Skip progress bar line if meta.phase is "初始" OR meta.progress_pct is 0
• 快完成 phase: Append 只差 {remaining} {unit} after target weight

data_hook: ONE sentence citing specific data, sparking curiosity to click report. For style examples: read references/hook-examples.md

ED/avoidweightfocus flags: Omit progress bar, weight fields, and ⚖️ line. Hook focuses on consistency/variety.

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Pre-send Checks (cron auto-send)

1. Stage ≥ 3 → skip (still generate if manually requested)
2. < 2 days data in period → short encouragement message instead
3. All clear → generate and send

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Schedule & Trigger

• Auto: Sunday 21:00 user local time via per-user cron
• Manual: User says "周报" / "weekly report" → most recent completed Mon–Sun

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Report URLs

• https://nanorhino.ai/user/{username}/weekly-report.html?week={start_date}
• Latest: https://nanorhino.ai/user/{username}/weekly-report.html (no ?week= → loads latest)

Username auto-resolved from workspace path. Do NOT pass --username manually.

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Writes

| Path | When | |------|------| | data/reports/weekly-data-{start_date}.html | JSON data file | | data/logs/weekly-report-{start_date}.json | Report log (auto by script) |

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Skill Routing

Priority Tier P4 (Reporting). Owns all weekly summaries including exercise data. Exercise-tracking does NOT produce separate weekly summary when this skill generates.

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Performance

• Single message, no back-and-forth
• Chat message: scannable in under 10 seconds
• Commentary per section: 2-4 sentences max

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: NanoRhino
• Source: NanoRhino/weight-loss-skill
• License: MIT
• Homepage: https://nanorhino.com/

Install and usage instructions live in the source repository linked above.