| name | scheduled-summary |
| description | Cron-driven cross-session digest. Aggregates session activity, cron job outputs, memory changes, and tool usage stats into a compact summary for delivery via messaging platforms. Surfaces outstanding tasks and cross-session context that's invisible on chat platforms. |
| version | 1.0.0 |
| author | moonlight-lupin |
| license | MIT |
| platforms | ["linux","macos","windows"] |
| metadata | {"tags":["summary","digest","cron","sessions","activity","cross-session","notification","scheduled"],"related_skills":["decision-log","news-monitoring"]} |
Scheduled Summary
Overview
Messaging platforms are excellent for one active conversation, but they hide the
activity that happened elsewhere: other sessions, scheduled jobs, saved memory,
and unresolved items from earlier work. This skill creates a periodic digest that
surfaces that cross-session activity in a compact format suitable for chat
messaging platforms or any notification channel that accepts Markdown or plain
text.
The digest is designed for a cron scheduler. It reads optional local data sources
(session store, cron output directory, memory JSON files, and log file), filters
activity to a configurable time window, and emits Markdown, JSON, or plain text.
When no data sources are configured, it emits a template digest that an agent can
fill by querying its own platform-specific session history, scheduler status,
and memory tools.
Quick start
From this skill directory:
python scripts/summarize.py generate --since 24h
With explicit data sources:
python scripts/summarize.py generate \
--since 24h \
--sessions-db /path/to/sessions.sqlite \
--cron-dir /path/to/cron-output \
--memory-dir /path/to/memory-json \
--log-file /path/to/agent.log
Show current configuration and skipped sources:
python scripts/summarize.py config
Create a config template to fill in:
python scripts/summarize.py init --output .summary-config.json
What the digest includes
- Session activity — sessions started or completed inside the time window,
plus topic titles where available.
- Cron job status — jobs that ran successfully, jobs that failed, and jobs
marked overdue by their output files.
- Memory changes — new saved memories and updated facts from JSON records.
- Tool usage — most-used tools, total calls, and error counts from a text or
JSONL log file.
- Outstanding items — due decision reviews, incomplete tasks, and TODO-like
items found in session transcripts.
- Time window — every section is scoped to
--since (24h, 7d, 2w,
etc.) unless the source explicitly marks an item overdue.
Workflow
- Pick the delivery cadence. Daily is a good default. Weekly works for
quieter systems. Avoid high-frequency summaries unless the downstream channel
has strong threading or batching.
- Choose data sources. Configure only the stores you trust the digest to
read. Start with cron output and logs, then add session and memory stores once
you understand their schema.
- Generate once manually. Run
generate --since 24h and inspect the result
for length, sensitive fields, and duplicate items.
- Tune sections. Use
--sections sessions,cron,outstanding to keep the
first scheduled digest short. Add memory and tools if they are useful.
- Schedule the command. Run it from a cron scheduler and redirect output to
the channel integration or a file consumed by your notifier.
- Review after a week. Check whether the digest is surfacing actionable
items. Remove noisy sections and add missing source paths.
Completion criterion: the scheduled command produces a digest with a generated
timestamp, the requested sections, and no unexpected secrets or full transcripts.
Cron scheduler setup
Generic daily cron scheduler entry:
0 8 * * * cd /path/to/scheduled-summary && python scripts/summarize.py generate --since 24h --output /tmp/activity-digest.md
Example with environment variables instead of flags:
0 8 * * * SESSIONS_DB=/data/sessions.sqlite CRON_OUTPUT_DIR=/data/cron MEMORY_DIR=/data/memory LOG_FILE=/data/agent.log python /path/to/scheduled-summary/scripts/summarize.py generate --since 24h
To deliver to a messaging platform, pipe or post the generated file using your
own notifier:
python scripts/summarize.py generate --since 24h --output /tmp/digest.md
python /path/to/send_notification.py /tmp/digest.md
Keep the notifier separate from the digest generator so the script remains
portable across platforms.
Output format
Markdown output is optimized for chat platforms:
- Compact
## / ### headings.
- Bullets rather than paragraphs.
- Emoji status markers for quick scanning.
- Short quoted topics instead of transcript excerpts.
- Code blocks only for dense stats when useful.
- A final generated timestamp in UTC.
Supported formats:
python scripts/summarize.py generate --format markdown
python scripts/summarize.py generate --format json
python scripts/summarize.py generate --format text
Write to a file:
python scripts/summarize.py generate --since 7d --output weekly-digest.md
Customization
Include only specific sections:
python scripts/summarize.py generate --sections sessions,cron,outstanding
Common section sets:
- Daily operational digest:
sessions,cron,outstanding
- Weekly review:
sessions,cron,memory,tools,outstanding
- Low-noise health check:
cron,tools
- Agent-filled template: run with no source paths configured, then fill the
placeholders from platform-specific tools.
Configure paths with flags, environment variables, or a generated config file:
| Source | Flag | Environment variable |
|---|
| Session SQLite database | --sessions-db | SESSIONS_DB |
| Cron output directory | --cron-dir | CRON_OUTPUT_DIR |
| Memory JSON directory | --memory-dir | MEMORY_DIR |
| Tool/log file | --log-file | LOG_FILE |
| Decision records | --decisions-dir | DECISIONS_DIR |
See references/data-sources.md for expected formats and schema notes.
Integrations
decision-log
If a decision record directory is available, pass it with --decisions-dir or
DECISIONS_DIR. The digest scans Markdown decision records for accepted or
proposed decisions whose Next review: YYYY-MM-DD is due, then reports the count
and titles in the Outstanding section.
news-monitoring
News monitoring jobs usually write a scheduled output file. Point --cron-dir at
the directory containing those outputs. The digest will report whether monitoring
ran, succeeded, failed, or marked itself overdue. Keep the full news summary in
its own file; the scheduled summary should only mention that monitoring ran and
whether action is required.
Common pitfalls
- Too verbose for chat. Do not paste full transcripts or full cron logs into
the digest. Surface counts, titles, and one-line action items.
- Sensitive data leakage. Session titles, memory facts, and log lines may
contain secrets or personal data. Review the first outputs manually and redact
upstream sources where needed.
- Running too frequently. Hourly summaries often create notification
fatigue and duplicate the active chat. Daily or weekly is usually better.
- No deduplication across summaries. If the same overdue item appears every
day, either resolve it, suppress it upstream, or add a stable decision/task
owner outside this digest.
- Treating template mode as complete data. Placeholder output means no data
sources were readable. The agent or operator must fill it from platform tools.
- Assuming one universal session schema. Session stores vary by platform.
The script uses best-effort SQLite introspection, but exact counts depend on
the available columns.
- Mixing generation and delivery. Keep the digest generator independent from
platform-specific webhook or bot code; this makes testing and migration easier.
What this skill is not
- Not a session search tool. Use your platform's session search or transcript
browser when you need a specific conversation.
- Not a full transcript exporter. It intentionally summarizes titles, counts,
and TODO-like lines only.
- Not a replacement for session browsing. It helps decide what to inspect next.
- Not a complete scheduler dashboard. It reads output files and status markers;
it does not own or run the scheduler.
- Not a secrets scanner. It reduces verbosity, but it cannot guarantee that the
source data is safe to send to a messaging platform.
Reference files
references/digest-format.md — section contract, output variants, daily and
weekly examples.references/data-sources.md — source configuration, expected formats, and
schema examples.templates/digest-template.md — blank Markdown template for agent-filled or
manually curated digests.scripts/summarize.py — stdlib CLI for generating, configuring, and
bootstrapping summary files.
Verification checklist
