Cold Email Weekly Rhythm

Cold Email Weekly Rhythm

Having 29 cold email skills doesn't help if you don't run them on a schedule. This is that schedule.

This is a pure playbook. No scripts, no automatic reminders. You put the rhythm on your own calendar (Step 1 below) and run the prescribed skill at the prescribed time. That's the entire system.

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Step 1 (required before using this skill): Put the rhythm on your calendar

Open Google Calendar / Outlook / Apple Reminders / whatever you actually look at every day. Create these as recurring events. Copy the titles and cadences exactly.

| Event title | Cadence | |---|---| | Cold email: Monday deliverability audit | Every Monday, 9:00 am | | Cold email: Wednesday positive-reply sweep | Every Wednesday, 10:00 am | | Cold email: Friday campaign retrospectives | Every Friday, 3:00 pm | | Cold email: Inbox rotation | Every other Monday, 11:00 am | | Cold email: Monthly spam placement test | 1st of each month, 10:00 am | | Cold email: Quarterly experiment review | First Monday of each quarter, 1:00 pm |

Do not skip Step 1. The difference between hobbyist and top-1% cold email operators is that the top-1% operators actually run these tasks on their declared cadence, week after week. Your calendar is the accountability system. This skill doesn't have a built-in reminder — intentionally — because if it did and it broke, your ops would silently fail.

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Monday — Deliverability audit (15 min)

Run:

/email-deliverability-audit --days=7

(If using the scoped version: audit-performance.ts --campaign-ids= --days=7)

Review:

• Fleet reply rate over last 7 days — must be ≥1% (the 1% rule)
• Flagged campaigns (flag_low_reply = TRUE)
• Flagged inboxes (flag_high_bounce = TRUE)

Action:

• If any campaign failed the 1% rule: run /deliverability-incident-response → triage decision tree
• If bounce rate spiked above 2%: pause the offending campaign immediately, then triage
• If everything clean: log the check in a weekly journal, close the tab

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Wednesday — Positive-reply sweep (30-60 min depending on volume)

Run:

/positive-reply-scoring  # on all campaigns active in the last 7 days

Review:

• Any positive_interested or positive_soft replies — these are leads wanting to engage
• Any positive_referral replies — these are people saying "talk to Jane instead"
• Any negative_hostile replies — red flag, investigate

Action:

• Respond to every positive_interested reply within 30 seconds of seeing it. Do not batch these — a reply feeling like it took minutes to return converts 3× better than one that took hours.
• For referrals: reach out to the referred person within 24h, mention the referrer by name.
• For hostile: apologize, remove from all lists, investigate why they were flagged for hostility (often signals bad targeting).

Time management: if you have >50 positive replies per week, you're at the scale where you should hand off to a dedicated closer/AE. Do that handoff Wednesday morning so they can work replies by Wednesday afternoon.

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Friday — Campaign retrospectives (20 min per campaign)

Identify campaigns hitting their 21-day mark this week. (21 days is the minimum for reply-rate signal to stabilize.)

For each one:

1. Run /positive-reply-scoring --campaign-id=
2. Compare to previous campaigns' positive reply rate baselines
3. Decide:

• Winner (positive reply rate ≥2×baseline): keep running, consider scaling (clone to more inboxes)
• Middling (near baseline): iterate on copy or list — run /experiment-design Monday to plan the next variant
• **Loser (/experiments/-.json`:
• positive_reply_rate, reply_rate, bounce_rate
• Your decision (keep / iterate / kill) + reasoning
• Hypothesis for next iteration (if iterating)

Critical: do not skip the log. Over a quarter, these logs become the input for /experiment-design quarterly reviews. Without the history, you can't learn across campaigns.

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Every other Monday — Inbox rotation (30 min)

Run:

# Within /smartlead-inbox-manager skill:
npx tsx scripts/list-health.ts --all --out=health-$(date +%Y-%m-%d).csv

Review the CSV:

• Any inboxes with reputation "bad"?
• Any inboxes with is_warmup_blocked: true?
• Any inboxes with --senders=100

(Will use G Suite + Office365 provider pools. 100 senders is a sweet spot — large enough for statistical signal, small enough to avoid API stalls.)

**Review:**

- Overall inbox placement % — target: ≥85%
- Spam filter triggers — which filters fired, which senders affected

**Action:**

- **≥90% inbox placement:** great. Keep doing what you're doing.
- **80-90%:** yellow. Look at spam-filter-details. Start fixing the highest-frequency trigger next week.
- ** retrospective saved to `profiles//retrospectives/-Q.md` with:

- Top 3 campaigns + what made them work
- Bottom 3 campaigns + what to avoid
- 3-5 hypotheses for next quarter's experiments
- Adjust ICP in `client-profile.yaml` if the data suggests a different segment performs better

Use the retrospective as input to design next quarter's experiments via `/experiment-design`.

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## What to skip

You do NOT need to:

- Check Smartlead every day (Wednesday sweep catches everything important)
- Obsess over daily reply-rate fluctuations (wait for 7-day averages)
- Read every positive reply in real time — set up notifications if you want immediacy, but the Wednesday sweep is the system

Daily pokes at your cold email stack are a procrastination pattern, not a performance pattern.

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## What to do next

This skill IS the loop. Your next action is the next calendar event on your list.

**Or if you haven't run a campaign yet:** skip this skill entirely. Come back after your first campaign hits the 7-day mark.

## Related skills

- `/email-deliverability-audit` — the Monday and Monthly tasks
- `/positive-reply-scoring` — the Wednesday and Friday tasks
- `/smartlead-inbox-manager` — the biweekly inbox rotation
- `/deliverability-incident-response` — when the Monday audit flags something
- `/experiment-design` — the quarterly retrospective feeds into this
- `/zapmail-domain-setup-public` — when insurance pool runs low

## Source & license

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

- **Author:** [growthenginenowoslawski](https://github.com/growthenginenowoslawski)
- **Source:** [growthenginenowoslawski/coldoutboundskills](https://github.com/growthenginenowoslawski/coldoutboundskills)
- **License:** MIT

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