Announcement Digest

Adapt for your source — swap the @[SOURCE] label, names, and classification rules.

This is a sanitized version of a working school-email digest skill.

Full walkthrough: https://claudeblattman.com/workflows/school-digest/

v1.0 — Announcement email digest skill

Compile a digest of high-volume announcement emails from a single source (school, employer, nonprofit, professional association). Extract what matters, skip the noise, send a summary.

Prerequisites

• Gmail MCP — for searching and reading emails
• Gmail label + filter — all source emails auto-labeled (e.g., @School, @CompanyNews)
• Classification rules — a config file with your calibrated rules (see walkthrough)
• send-email.py or equivalent — for sending the compiled digest

Config & State Files

• Rules: [YOUR_CONFIG_PATH]/digest-rules.md
• State: [YOUR_STATE_PATH]/digest-state.json

State file tracks: last_digest_date, digest_count, reported_message_ids, reported_message_ids_ttl_days (default 30).

Execution Steps

Step 1: Read State & Check Frequency

1. Read digest-state.json.
2. If last_digest_date is not null and fewer than 2 days have passed:
   • Output: "Nothing new since [last_digest_date]. Next digest available [date]."
   • Exit.
3. Store digest_count (needed for first-time intro check at Step 5).

Step 2: Fetch Labeled Emails

1. Compute lookback date: last_digest_date if set, otherwise 14 days ago.
2. Search Gmail: label:[YOUR_LABEL] after:[lookback_date in YYYY/MM/DD]
   • Do NOT use is:unread — labeled emails may or may not be marked read. Query by date range.
   • Page through all results (follow next_page_token).
3. Filter out any message IDs already in reported_message_ids.
4. If no new emails remain, exit with message.

Step 3: Fetch Email Content

1. For each new message, fetch full content via get_gmail_message_content.
   • Fetch in parallel batches of 10.
2. Group messages by Gmail thread ID. Keep only the most recent non-you message per thread.
3. Accumulate total word count across all fetched message bodies.
4. Prune reported_message_ids: Remove IDs older than reported_message_ids_ttl_days.

Step 4: Classify Each Email

Read your rules config for the full rule set. For each email (or thread), apply classification in this order:

4a. Skip Check

Apply SKIP rules first. If any match, mark as skip and record skip_reason.

4b. Source Assignment

Determine which sub-category the email belongs to (e.g., which child's school, which department, which program).

4c. Urgency Classification

Apply rules from config using this priority order:

1. Sender pattern override: Personal sender (not noreply@) → HIGH
2. HIGH keyword match in subject + first 200 chars → HIGH
3. LLM extraction for everything else:

Extract from this email. Return as JSON. (1) category: action_required / calendar_event / fyi / skip (2) urgency: high / medium / low (3) summary: 1-2 sentences of what you need to know (4) deadline: specific date/time if any, else null (5) deadline_quote: verbatim text from email stating the date/deadline — copy exact wording, do not paraphrase. null if no deadline. (6) skip_reason: if skip, one phrase why

4. HIGH keyword overrides LLM urgency upward (never downward).
5. SKIP keyword overrides to skip unless LLM said action_required.

Step 4.5: Write Classified Artifact

Create a private temp directory with mktemp -d and write full classified data to digest-classified.json inside that directory. This serves as:

• A compaction safeguard — if context is lost, re-compose from this file
• A debug artifact — review classification accuracy after the fact

Step 5: Compose Digest

Format as plain text. Structure:

[YOUR SOURCE] EMAIL DIGEST
[date range]
Compressed ~[W] words across [N] emails ([M] threads) into this digest.
──────────────────────────────

[CATEGORY 1]

▶ ACTION ITEMS
  • [summary] — deadline: [date]
    Source: "[deadline_quote]"

📅 UPCOMING
  • [event/date]

ℹ️ FYI
  • [1-line summary]


[CATEGORY 2]

▶ ACTION ITEMS
  ...

+ [N] lower-priority items not shown
──────────────────────────────

Rules:

• Action items (HIGH) first, deadlines noted inline
• For HIGH items with a deadline_quote, include: Source: "[deadline_quote]" — makes factual errors visible
• Calendar events (MEDIUM) second
• FYI (LOW) third, 1 line each
• Omit empty sections
• First-time send (if digest_count was 0): Prepend intro explaining what this automated digest is and who it's from.

Step 6: Save State & Send

1. Write state file FIRST (before sending):
   • Add ALL processed message IDs to reported_message_ids (including skipped)
   • Set last_digest_date to today
   • Increment digest_count
2. Draft the digest via your preferred method. Ask for explicit approval before sending. The public template must not auto-send.
3. Do NOT mark source emails as read. The digest is additive — it doesn't replace checking the source.

Step 7: Log Performance

Log tool call count, duration, and volume for future optimization.

Edge Cases

• No emails: Exit with message at Step 2.
• All already reported: Exit with message at Step 2.
• Send failure after state write: State is already saved (prevents duplicate digests). Log the error and retry manually.

What This Skill Does NOT Do

• Does not mark emails as read
• Does not apply Gmail labels
• Does not modify any emails

Building Your Own Rules Config

The classification rules are the hardest part. Don't try to write them upfront — calibrate from real data:

1. Pull 20 recent emails from your source
2. Rate each: action_required / calendar / fyi / skip
3. Note where you disagree with your own first instinct
4. Pull 30 more and refine
5. Write the rules that emerge

See the full walkthrough for the calibration method.

Sanitized from a working skill. Adapt the label, categories, and rules for your source.