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Marketing Loops

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coreyhaines31
marketing-loops

When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other marketing skills. For one-off marketing ideas, see marketing-ideas. For the experimentation loop specifically, see ab-testing.

Overview

Publishercoreyhaines31
Repositorymarketingskills
Skill namemarketing-loops
Stars
50.7K
Forks
7.7K
Bundled files
6
LicenseMIT
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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by coreyhaines31 on GitHub. Read the source before you install it.

Installation

Install the Marketing Loops 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.
  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/coreyhaines31/marketingskills.git /tmp/marketingskills
mkdir -p .claude/skills
cp -r /tmp/marketingskills/skills/marketing-loops .claude/skills/marketing-loops
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Marketing Loops 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 Marketing Loops 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 Marketing Loops 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.

Marketing Loops

You help set up marketing loops — repeatable marketing workflows an AI agent runs on a cadence, each with a defined trigger, a bounded set of steps, a self-check, and an explicit stopping condition. A loop turns a marketing task you'd otherwise do manually (and forget) into an always-on system: the weekly SEO opportunity scan, the ad-fatigue refresh, the churn-signal watch.

This is the operational cousin of marketing-ideas. Ideas tell you what to try once. Loops tell you what to keep doing on a schedule — and wire the other marketing skills together to do it.

How to Use This Skill

Check for product marketing context first: if .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md), read it before asking questions. Use that context and only ask for what's missing.

Then:

  1. Clarify the job. What outcome should this loop protect or grow? (rankings, ad efficiency, activation, retention, revenue, referrals)
  2. Pick a loop from the catalog in references/loop-catalog.md — or adapt the closest one.
  3. Tune the cadence to how fast the underlying signal actually changes (see the cadence rule below).
  4. Confirm the human checkpoint. Decide what the loop does autonomously vs. what it stages for human approval before publishing or spending — see references/loop-guardrails.md.
  5. Schedule it (see "Scheduling a loop" below).

Building more than one loop, or a whole marketing operating system? See references/loop-orchestration.md for how loops compose and the order to adopt them (start with tracking + a weekly review; don't build 43 at once).

Anatomy of a Marketing Loop

Every loop in the catalog has these nine parts. When you author or adapt one, fill all of them — a loop missing a stop condition, a self-check, or its state handling is a liability, not an asset.

PartWhat it defines
Check cadenceHow often the loop looks (weekly / daily / on-trigger). Match it to signal speed.
Acts whenThe action condition — what must be true to actually do something, vs. just check and skip. Most runs of a good loop are "checked, nothing to do."
PurposeThe one outcome this loop exists to move.
Skills usedWhich marketing skills the loop orchestrates each iteration.
Loop bodyThe ordered steps run each iteration.
Self-checkThe verification done before acting — so the loop doesn't act on noise, seasonality, or a tracking bug.
State / idempotencyWhat the loop remembers between runs: last-run marker, dedupe key, cooldown window, "already handled" set. Without this, loops double-act, re-nag the same people, or re-alert the same thing. Non-negotiable for anything scheduled — see references/loop-state.md for where state lives and the idempotency patterns.
Stop / bail-outWhen the loop skips, halts, escalates to a human, or disables itself — plus what it does on error. Every loop needs one, including heartbeat loops (their stop is "manual disable + error-halt," never "n/a").
OutputWhere results go: a file, a PR, a staged draft, a notification, a report.

The Check cadence / Acts when split matters: a churn-signal loop might check daily but only act when an account crosses a risk threshold it hasn't been contacted about inside the cooldown window. Conflating the two produces loops that either miss the window or spam.

The cadence rule

Match cadence to how fast the signal actually changes — not to how often you'd like an update.

SignalRealistic cadenceWhy
Rankings, backlinks, domain authorityWeeklyMove slowly; daily checks are noise
Ad creative fatigue, CPA driftEvery 2–3 daysMeta/Google feedback loops are days, not hours
Activation / onboarding funnelWeeklyNeeds enough signups to be significant
Churn signalsDaily or on-triggerEarly intervention window is short
Content / copy decayMonthlyTraffic erosion is gradual
Competitor changesWeeklyPricing/positioning shifts are infrequent but matter
Social listening / mentionsDailyEngagement windows close fast

Over-frequent loops are the most common failure mode: they generate busywork, burn budget, and train you to ignore the output.

When NOT to loop

Not everything should be automated on a cadence. Skip a loop — or add a mandatory human checkpoint — when:

  • Strategy or creative direction is the real work. Loops maintain and optimize; they don't set positioning, invent campaigns, or make brand calls.
  • The action publishes or spends without review. Auto-drafting an ad, email, or post is fine. Auto-publishing or auto-shifting budget needs a human checkpoint unless the user has explicitly authorized autonomous action and set guardrails (caps, allowlists).
  • The signal is too sparse to be significant. A weekly conversion-rate loop on 40 visitors/week is measuring noise.
  • It's a vanity loop. If nobody acts on the output, delete the loop. A loop that emails a dashboard nobody reads is worse than nothing.

For any loop that sends, spends, publishes, or touches personal data, apply references/loop-guardrails.md — the two-tier action model (autonomous-safe vs. gated), spend/send caps, CAN-SPAM/GDPR/FTC/ToS rules, the always-escalate list, and a required kill switch.

Scheduling a loop

These loops are agent-agnostic — the body works in any agent. The scheduling depends on your environment:

  • Claude Code — native options: /loop (self-paced, until a condition), ScheduleWakeup (dynamic pacing that reacts to state), and CronCreate (fixed cron schedule). If you have a loop-mechanics skill such as loopify installed, use it to choose between them and tune delays; otherwise the guidance below is enough.
  • Any agent + cron — wrap the loop body as a scheduled prompt/script (0 9 * * 1 for Mondays 9am, etc.).
  • Manual cadence — for high-judgment loops, "run this skill every Monday" is a perfectly good loop. The value is the repeatable body, not the automation.

Default to time-of-day cron for review-style loops (weekly review, ranking watch) and dynamic pacing for monitor-until-threshold loops (churn watch, launch-day tracking).

The Catalog

references/loop-catalog.md holds the full library — 43 marketing loops with thorough funnel coverage: SEO & Content, Paid, Earned/Social/Partnerships, Activation, Retention, Revenue, Referral & Advocacy, and Ongoing Ops. Each is a complete, adaptable spec. Start there, pick the closest match, and tune it to the user's product, stage, and tooling.

Authoring a new loop

When nothing in the catalog fits, author a new loop from references/loop-template.md — a copy-paste template with fill-in prompts, a worked before/after example, and a ship checklist. Fill all nine anatomy parts; if you can't answer the self-check, state/idempotency, and stop/bail-out concretely, the loop isn't ready to run.

Anti-patterns

  • Looping without a stop condition → runaway spend or infinite churn.
  • Same cadence for every loop → most run too often and get ignored.
  • No self-check → the loop acts on noise, seasonality, or a tracking bug.
  • No human checkpoint on spend/publish actions.
  • Building 10 loops at once → start with one, prove it earns its keep, then add the next.

Banned vocabulary

Avoid: "set it and forget it," "fully autonomous marketing," "AI does everything," "10x on autopilot," "growth hacking machine." Loops are disciplined systems with checkpoints, not magic. Describe them honestly.

Related Skills

  • marketing-ideas — one-off tactics and inspiration (what to try). Loops operationalize the ones worth repeating.
  • ab-testing — the experimentation loop specifically (hypothesis → test → promote winner → repeat).
  • analytics — most loops read from analytics to decide whether to act.
  • Individual channel skills (ads, seo-audit, emails, social, churn-prevention, pricing, referrals) — the loop bodies orchestrate these.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Marketing Loops AI skill do?

When the user wants to set up a recurring, self-running marketing workflow — a repeatable loop an AI agent runs on a cadence (weekly, daily, on a trigger) rather than a one-off task. Also use when the user mentions 'marketing loop,' 'recurring marketing workflow,' 'automate my marketing,' 'marketing on autopilot,' 'weekly marketing review,' 'ad fatigue check,' 'content refresh loop,' 'churn watch,' 'ranking drop alert,' 'always-on marketing,' 'marketing automation workflow,' or 'run this every week.' Use this to pick, adapt, and schedule an ongoing marketing loop that orchestrates the other...

Why use Marketing Loops on TypingMind?

Because you install it once and use it with any model. Marketing Loops 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 Marketing Loops in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coreyhaines31/marketingskills/tree/main/skills/marketing-loops. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Marketing Loops?

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 Marketing Loops?

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

Is the Marketing Loops AI skill free?

Yes. It is published on GitHub by coreyhaines31 under the MIT license. 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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