Email Report logo

Email Report

Organization
cognyai
email-report

Auto-generate the weekly or monthly email performance report in three formats — Slack update, CEO email, board-deck section — from real ESP data

Overview

Publishercognyai
Repositoryclaude-code-marketing-skills
Skill nameemail-report
Stars
111
Forks
15
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cognyai on GitHub. Read the source before you install it.

Installation

Install the Email Report AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cognyai/claude-code-marketing-skills/tree/main/skills/email-report
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cognyai/claude-code-marketing-skills.git /tmp/claude-code-marketing-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-marketing-skills/skills/email-report .claude/skills/email-report
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Email Report in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Email Report on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Email Report is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Email Report

The 3-hour tax every email marketer pays: pulling last period's numbers, charting the trend, explaining the variance, and writing commentary in the right voice for the audience. This skill does it in one command and outputs three versions — Slack ping, CEO email, board deck section — so you can ship the one your stakeholder needs.

Requires: Cogny MCP + a connected ESP. Sign up

Usage

/email-report — monthly report, all three formats (default) /email-report weekly — last 7 days /email-report monthly ceo — monthly, only the CEO email /email-report weekly slack — weekly, only the Slack update

Step 0: Is Cogny connected?

If no mcp__cogny__* tools exist (no list_integrations, no cogny_status), print this and stop:

Email Report needs your marketing data through Cogny's MCP gateway.

1. Sign up at https://cogny.com and connect your ESP (Klaviyo, Mailchimp, Rule, Get a Newsletter, Brevo, MailerLite, Drip, Salesforce Marketing Cloud, Symplify or Braze); a store, Stripe or GA4 adds revenue context.
2. Add Cogny to .mcp.json in your project:
   {"mcpServers": {"cogny": {"type": "http", "url": "https://app.cogny.com/mcp"}}}
3. Restart Claude Code; it opens a browser for the OAuth login on first use.

Nothing to run without Cogny.

When Cogny is connected but no ESP is, say "connect your ESP in Cogny" and stop; a connected integration that fails its health check gets "reconnect in Cogny".

Prerequisites Check

Detect connected ESP (on Cloud, mcp__cogny__list_integrations; name any unhealthy integration as broken). If none, stop and prompt. Also note which store (Shopify, WooCommerce, Abicart, Litium), billing source (Stripe, for SaaS) and web analytics (GA4, Plausible) are connected — they supply revenue and email-driven sessions.

Health check: health_status misses revoked tokens, so make one cheap read per integration before relying on it (e.g. Mailchimp tool_get_account_info, Get a Newsletter tool_list_senders, Klaviyo get_account, GA4 tool_run_report for one day, Stripe stripe_api_read GetSubscriptions with limit: 1). A 401, Forbidden or scope error means 🔴 "reconnect in Cogny": name it, don't retry, and report from the rest.

Missing tool: if a tool named here isn't exposed by the workspace, call mcp__cogny__refresh_mcp_discovery once, use the fallback named next to the tool for this run, mark that source ⚠ "needs reconnect", and tell the user to reconnect the Cogny MCP. Never loop on refresh. Get a Newsletter fallbacks: tool_get_report_have_not_opened → that report's list contacts minus the openers from tool_get_report_opens; tool_get_report_link_clicks → tool_get_report_opens (per-contact click counts) or tool_get_report_clicks (per-link totals); tool_get_report_opens_aggregated → the totals in tool_get_report. Mailchimp tool_get_campaign_content → tool_get_campaign for the headers, and ask the user for the body.

ESP connected but 0 sends in the window: skip that ESP's campaign section with a one-line note ("Rule: connected, 0 sends in ") and keep its list-size numbers. If no ESP sent anything in the period, see "Zero sends in the period" in step 2.

Works with

ESP (Prefix)Campaigns + metricsFlows / journeysList size + growthESP-attributed revenue
Klaviyo (Klaviyo)list_campaigns, get_campaign_values_reportlist_flows, get_flowlist_profiles✓ (get_campaign_values_report with conversion_metric_id = Placed Order)
Mailchimp (Mailchimp)tool_list_campaigns, tool_get_reporttool_list_automations, tool_get_automationtool_get_audience✗
Rule (Rule)tool_list_campaigns, tool_get_campaign_statisticstool_list_journeystool_list_subscribers✗
Get a Newsletter (Get_a_Newsletter)tool_list_sent, tool_get_report (one report per sent mail)—tool_list_lists (active_subscribers_count per list)✗
Brevo (Brevo)list_email_campaigns (status: "sent"), get_email_campaign (stats are in the campaign's statistics)not exposedlist_contact_lists (subscriber counts per list)✗. get_smtp_report (start_date, end_date) is transactional mail only: report it as its own line
MailerLite (MailerLite)list_campaigns (filter_status: "sent"), get_campaign (stats)not exposedlist_groups (active counts), list_subscribers✗
Drip (Drip)list_campaigns, get_campaign (Email Series: subscriber counts, no per-email open/click rates)list_workflowslist_subscribers (subscribed_after) for new subs✗ (subscriber lifetime_value is LTV, not period revenue)
Salesforce Marketing Cloud (Salesforce_Marketing_Cloud)list_email_sends (start_date, end_date): per-send rates + window totalsget_journey_email_performance, get_triggered_send_summary — lifetime totals, no date filternot exposedconversions count only
Symplify (Symplify)get_campaign_overview (start, end), get_campaign_reportlist_journeys (names only)not exposed✓ conversion amount per delivery
Braze (Braze)braze_list_campaigns → braze_get_campaign_analytics (length ≤ 100, ending_at; daily, email channel only)braze_list_canvases → braze_get_canvas_summarybraze_list_email_unsubscribes (start_date, end_date) for unsubs; list size not exposed✓ Braze-attributed revenue

Revenue from the store and analytics (enhanced when connected):

SourceToolWhat it is
Shopifytool_list_orders (query_filter: "created_at:>=YYYY-MM-DD created_at:<YYYY-MM-DD", page with after)All store orders in the window (context, not email revenue)
WooCommerceget_sales_report (date_min, date_max)Store sales totals
Abicart / Litiumget_sales_summary (start_date, end_date, group_by: "week")Orders + revenue per period, base currency
GA4tool_run_report (dimensions: ["sessionCampaignName"], metrics: ["sessions","keyEvents","purchaseRevenue"], dimension_filter on sessionDefaultChannelGroup = Email)Email-driven sessions and last-click revenue
Plausiblebreakdown (dimension: "visit:utm_campaign", filters: [["is","visit:utm_medium",["email"]]])Email-driven visits and goal conversions
Stripe (SaaS)stripe_api_read: GetInvoices (paid, created in the window), GetSubscriptions (new: created in the window; cancelled: there is no canceled_at filter, so list status: "canceled" and keep rows whose canceled_at falls in the window client-side), GetRefunds. Use limit 20–25 and page with starting_after (a 100-row page is ~370KB)Billed revenue, new subscriptions and churn for SaaS businesses; use it where a store would supply revenue

Report ESP-attributed revenue, GA4 email revenue and store (or Stripe) revenue as separate labeled lines. They use different attribution windows and never add up.

Steps

1. Define the period and read the previous report

ModeCurrent windowComparison
weeklylast 7 daysprior 7 days + 4-week rolling avg
monthlylast 30 daysprior 30 days + 12-week rolling avg

State the exact date ranges up front.

Call read_context_node with path: "insights/email/reports/<weekly|monthly>/latest". If it exists, it holds the previous report's narrative and key numbers: use them in "What happened" ("this matches the trend from last month" / "this reverses the dip we flagged"). If it doesn't exist, this is the first run for that mode; say so.

2. Pull the data

Per-ESP tool adapter. The right tool depends on which ESP is connected:

DataKlaviyoMailchimpRuleGet a Newsletter
Campaign listlist_campaignstool_list_campaignstool_list_campaignstool_list_sent
Campaign metricsget_campaign + list_events (metric-filtered)tool_get_reporttool_get_campaign_statisticstool_get_report
Automation / flow listlist_flowstool_list_automationstool_list_journeysnot available
Flow metricsget_flowtool_get_automationtool_list_journeys (limited)not available
Subscriber list sizelist_profiles (count)tool_get_audiencetool_list_subscribers (count)tool_list_lists → sum of active_subscribers_count (not the tool_list_contacts count, which includes inactive contacts)
Revenue per send✓ via list_events with metric="Placed Order"not availablenot availablenot available

Get a Newsletter: tool_list_sent rows carry subject, send time and report_id, so tool_get_sent isn't needed. Its delivered equals sent_to even when mails bounced, so use sent_to − bounced as the delivered denominator. Exclude test sends (under 10 recipients, or "test" in the subject).

For Brevo, MailerLite, Drip, Salesforce Marketing Cloud, Symplify and Braze, use the tools in Works with above. Pull each ESP's numbers separately; if several are connected, the report gets one metrics column per ESP, never a blended total.

For the current window AND the comparison window, pull:

Campaign broadcasts:

  • Each campaign's subject, send date, recipient count, opens, unique opens, clicks, unique clicks, unsubs, bounces.
  • Revenue attributed — Klaviyo, Braze, Symplify. For Klaviyo, fetch "Placed Order" events scoped to the send window and attribute by campaign (or get_campaign_values_report with revenue_per_recipient). Braze returns revenue in braze_get_campaign_analytics; Symplify returns conversion amount per delivery. For the other ESPs, omit ESP-attributed revenue and use GA4/Plausible email-driven revenue or conversions if connected, labeled as such.

Flows / automations — varies by ESP:

  • Klaviyo: flow name, triggered volume, revenue per flow (via events).
  • Mailchimp: automation name, sends, opens, clicks (no revenue).
  • Rule: journey name + limited metrics.
  • Drip: workflow names from list_workflows; Email Series subscriber counts from get_campaign.
  • Salesforce Marketing Cloud: get_journey_email_performance — lifetime numbers, so show them as "since launch", never as this period's change.
  • Symplify: list_journeys gives names only; journey performance isn't exposed.
  • Braze: Canvas name + braze_get_canvas_summary for the window (revenue included).
  • Brevo, MailerLite: automations aren't exposed; skip and say so.
  • Get a Newsletter: no flow object exists. Skip this section; use a "recurring sends" proxy if the user has a newsletter cadence.

List-level metrics:

  • List size at period start vs end
  • New subscribers in period
  • Unsubscribes in period
  • Net change + growth rate

Zero sends in the period: if no connected ESP sent a broadcast in the current window, don't compute rates (they'd be 0/0). Output a short report instead: "No email sends in (last send: , )", the list-size change, any flow/journey numbers that exist, and the store/Stripe/GA4 context lines. Flag the gap as a finding if the previous report showed a regular cadence.

Unconnected senders (GA4): compare the GA4 email sessionCampaignName values with the connected ESPs' sends in the window. A campaign with email sessions that matches no ESP send means email is going out from a sender Cogny can't see (another ESP, a CRM, a product mailer). List those campaigns with their sessions and say "sent from an unconnected tool; connect it to include it in the report".

3. Compute the report metrics

For each window, compute:

MetricCalcWhy it matters
Sendstotal emails deliveredVolume sanity check
Open rateunique opens / deliveredSubject/preheader effectiveness (MPP-distorted)
CTRunique clicks / deliveredTrue engagement
CTORunique clicks / unique opensContent effectiveness (MPP-resilient)
Unsub rateunsubs / deliveredList health signal
Bounce ratebounces / sentDeliverability signal
Revenue per sendecom revenue / delivered (if available)The only metric execs actually care about
List growth rate(ending - starting) / startingAcquisition health

Show absolute value + % change vs prior period + % change vs rolling baseline.

4. Identify movers

Rank campaigns in the current window by open rate, CTR, and revenue. Identify:

  • Top performer — best campaign by revenue (or by CTOR if no revenue data)
  • Worst performer — bottom by revenue/CTOR
  • Anomaly — campaign whose metrics are >2σ from the user's typical baseline (surprise hit or surprise flop)

For each, write a one-sentence "why" hypothesis based on visible attributes (subject style, send time, segment, content type).

5. Explain variance

Don't just say "CTR dropped 8%." Explain it. Cross-reference:

  • Did send volume change? More sends to less-engaged segments drag rate metrics even if absolute revenue is fine.
  • Did the segment mix change? (All-list sends vs engaged-only)
  • Did cadence change? (More sends per week → fatigue)
  • Did a specific campaign drag the average? (One dud to a huge segment)
  • Did list hygiene change? (Big unsub event or re-engagement deadline)
  • Was there an external event? (holiday, launch, outage)

Phrase findings as claim → evidence:

"Open rate dropped from 28% to 22%. Two of four sends this month went to the dormant 180-day segment (120k recipients at 14% open), which pulled the average down. If you look at engaged-segment sends only, open rate actually rose from 34% to 36%."

6. Generate the three outputs

6.1 Slack update (≤500 chars, 3 bullets)
📧 Email – <period label>
• Sends: <N> ( <±>% vs prior)  |  Open: <X>% ( <±>pp)  |  CTR: <Y>% ( <±>pp)
• 🏆 Top: "<subject>" — <metric>  |  ⚠️ Watch: <one-line variance call>
• Revenue: $<X> ( <±>% vs prior)  |  List: <±>% net growth  |  Next week: <1-line plan>
6.2 CEO email (≤250 words, narrative)
Subject: Email performance — <period label>

Hi <CEO first name>,

Quick update on email this <period>:

Headline: <one-sentence summary — is it good, bad, or mixed?>

What happened:
[2-3 sentences explaining volume, rate-metric movement, revenue. Tie to a
business narrative — launches, campaigns, segment focus.]

What's notable:
[1-2 sentences. Top campaign or surprise win or flagged concern.]

What's next:
[1-2 sentences. Concrete plan for next period. Pick ONE action, not five.]

Happy to dig deeper on any of this.

<signoff>
6.3 Deck section (full)
EMAIL PERFORMANCE — <period label>

Summary
  <two-sentence narrative>

Key metrics
  [table: current / prior / rolling / %Δ]
  Sends, Open rate, CTR, CTOR, Unsub rate, Revenue per send, List size

Trend
  [describe what a chart should show — up-and-to-the-right, step change, etc.]

Campaign roundup
  🏆 Best:  "<subject>"
           <segment>, <recipients>, <metric wins>
  📉 Worst: "<subject>"
           <what happened>

Flow performance (if applicable)
  [table of top 3 flows by revenue, with recipient count and conv rate]

What moved the needle
  [2-3 bullets — claim → evidence]

Plan for next <period>
  [2-3 bullets — concrete, owned, measurable]

7. Save the narrative

Persist the period summary to Cogny's context tree so future /email-report runs have historical continuity:

json
{
  "path": "insights/email/reports/<weekly|monthly>/latest",
  "body": "<period dates + the narrative summary + key numbers per ESP>"
}

Overwrite latest (step 1 reads it next run) and also write the same body to insights/email/reports/<weekly|monthly>/<YYYY-MM-DD> as the dated archive.

8. Create findings for notable issues

For anything serious (unsub rate spike, deliverability drop, revenue collapse, an unconnected sender), record it so it lands in the dashboard — not just the report. On Cloud call create_ticket first (fields mapped per section 2 of the routing guide); on Solo call create_finding:

json
{
  "title": "Unsub rate doubled vs prior month (0.18% → 0.37%)",
  "body": "<which campaigns drove it, which segment, recommended fix>",
  "action_type": "list_hygiene",
  "priority": "high"
}

Output defaults

  • If the user didn't specify a format, output all three and label them clearly.
  • Lead with the Slack version — fastest to read if they're skimming.
  • Include the raw metric table at the end so the user can copy numbers out.

Notes

  • Open rate is noisy since Apple MPP. Always report CTR and CTOR alongside. If open rate moves >5pp but CTOR doesn't, it's probably MPP population change, not real behavior.
  • For first-ever run, there's no prior period to compare to — call this out explicitly and use absolute numbers only.
  • Don't invent revenue numbers. ESP-attributed revenue exists only for Klaviyo ("Placed Order" events with a value field), Braze and Symplify. For Mailchimp, Rule, Get a Newsletter, Brevo, MailerLite, Drip and SFMC, say "revenue not exposed by this ESP's MCP" and use GA4/Plausible email-driven revenue, store or Stripe totals for context, or user-pasted revenue — each labeled with its source.
  • Definitions differ per ESP. Klaviyo, Mailchimp and Brevo opens include Apple MPP machine opens unless the payload separates them; Get a Newsletter reports per sent mail; SFMC journey totals are lifetime. Name the ESP on every number and never average rates across ESPs.

Recording findings

Use create_ticket when the workspace has it (Cloud) and create_finding otherwise (Solo). The fields differ; see section 2 of ../marketing-engineer/references/mcp-routing.md.

Frequently asked questions

What does the Email Report AI skill do?

Auto-generate the weekly or monthly email performance report in three formats — Slack update, CEO email, board-deck section — from real ESP data

Why use Email Report on TypingMind?

Because you install it once and use it with any model. Email Report is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Email Report in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cognyai/claude-code-marketing-skills/tree/main/skills/email-report. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Email Report?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Email Report?

As many as you like. As long as a model supports skills, you can use Email Report with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Email Report AI skill free?

It is published on GitHub by cognyai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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