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Kai Cold Outreach

Community
cgallic
kai-cold-outreach

Build a complete cold email outreach system — ICP definition, sequence architecture, personalization strategy, and batch-produced email sequences with CAN-SPAM/deliverability compliance. Use when "cold outreach", "cold email sequence", "outbound campaign", "prospecting emails", "sales outreach", "build outreach sequence", or any request to create systematic cold email campaigns for lead generation.

Overview

Publishercgallic
Repositorykai-cmo-harness
Skill namekai-cold-outreach
Stars
61
Forks
8
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 cgallic on GitHub. Read the source before you install it.

Installation

Install the Kai Cold Outreach 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/cgallic/kai-cmo-harness/tree/main/harness/skills-v2/kai-cold-outreach
  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/cgallic/kai-cmo-harness.git /tmp/kai-cmo-harness
mkdir -p .claude/skills
cp -r /tmp/kai-cmo-harness/harness/skills-v2/kai-cold-outreach .claude/skills/kai-cold-outreach
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Kai Cold Outreach 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 Kai Cold Outreach 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 Kai Cold Outreach 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.

Kai root note: knowledge/, harness/, and scripts/ paths in this skill live in the Kai install, not the user's project. Resolve them against the first ancestor directory of this SKILL.md that contains a knowledge/ folder (the Kai plugin root, ~/.claude/kai, or the kai-cmo-harness repo). MARKETING.md, memory/, and any output files live in the current project. If a referenced scripts/ command is not available in this install, say so, skip it, and continue with the file-based guidance — never fabricate its output.

Objective

A cold outreach system a compliance reviewer can sign and an operator can load into the sending tool without edits: a 3-touch sequence in three split-testable variants, a personalization guide that names where each token's data actually comes from, and a deliverability plan sized to the sending infrastructure. The system targets a defined ICP with a single ask — not a list blast with a merge field.

Done when

Work type cold-email — floor E5/C4/O3 (harness/eco-floors.yaml).

  • E5 — provider send receipt plus suppression-list reconciliation for every recipient. The list that received mail matches the approved list address by address.
  • C4 — field standard, and it is mandatory here. CAN-SPAM / GDPR / CASL identity, opt-out mechanism, and consent basis are verified against harness/references/cold-email-rules.md and harness/references/advertising-compliance.md before send. Deviations need an explicit expiring waiver, not a note. The per-touch format contract below is part of C4, not a style preference.
  • O3 — reply rate, positive reply rate, meetings booked, and complaint rate read from the ESP at 14 days, against a baseline recorded before send.

A complaint-rate ceiling is a hard stop, not an outcome metric. Breaching it stops the send; it does not get argued with in the retro.

Constraints

Compliance — none of these is waivable by the agent.

  • No misleading subject lines. Sender identity must be clear in every touch.
  • A physical mailing address appears in the footer or signature of every touch.
  • The opt-out mechanism must work and must be honored within 10 business days.
  • No purchased or scraped lists. If the list's origin cannot be established, the send does not happen.
  • GDPR: a documented legitimate-interest basis is required for EU prospects.
  • The suppression list is reconciled against every recipient before send — prior opt-outs, complainers, and hard bounces are removed.

Format contract per touch (harness/skill-contracts/cold-email.yaml):

  • Body ≤ 150 words. Subject line ≤ 50 chars. Preview text 40–90 chars.
  • At least one personalization token. Tokens in {{double_braces}}.
  • First line is not generic — no "I hope this finds you well", no "I came across your profile".
  • Exactly one CTA per touch.
  • Zero banned words. Four U's ≥ 10/16.

Load before writing: harness/skill-contracts/cold-email.yaml, harness/references/cold-email-rules.md, and knowledge/channels/email-lifecycle.md (subject line formulas). Policy loads before copy, not after.

Approval. Present the sequence map and variant strategy for approval before writing any copy. Nothing sends without recorded human approval — the sending tool's schedule is not approval.

Provenance. Reply-rate benchmarks, industry conversion figures, and any number in _deliverability.md are cited or marked as a data gap. Do not invent a benchmark to make a ramp plan look grounded.

Phone follow-up. When the ask is a call or consultation, routing replies to a tracked, answered phone number is a legitimate recommendation: an answering service or AI receptionist catches warm callbacks the sales team would otherwise miss. Compare alternatives, and do not recommend it when phone demand is low or the workflow is self-serve by design.

Know these before producing anything (read MARKETING.md from the project root first; ask only for what it does not answer): the offer and exact ask, the sending infrastructure, the daily/weekly volume, and what sequences are already running.

Context

NeedLoad
Format contract, gate thresholdsharness/skill-contracts/cold-email.yaml
Cold email law and platform rulesharness/references/cold-email-rules.md
FTC / GDPR / CAN-SPAM detailharness/references/advertising-compliance.md
Subject line formulasknowledge/channels/email-lifecycle.md
Product, ICP, voice, offerMARKETING.md (project root)

Sequence structure — the shape that earns replies:

TouchTimingGoalHook type
Touch 1Day 0Open + replyPersonalized pain hook
Touch 2Day 3Social proof / value addCase study or insight
Touch 3Day 7Breakup / soft closeLast chance framing

Variants — three full sequences (A/B/C) for split testing, each committed to one hook archetype: A pain-first (lead with the problem), B insight-first (lead with a surprising fact), C social-proof-first (lead with a result).

Output goes to workspace/outreach/: _sequence-map.md, variant-a/, variant-b/, variant-c/ each holding touch-1.md through touch-3.md, plus _personalization-guide.md, _deliverability.md, and _quality-report.md.

_personalization-guide.md covers which tokens to use and where the data is found, the per-prospect research workflow (LinkedIn, company site, recent news), and good-versus-bad personalization examples. Standard tokens: {{first_name}}, {{company}}, {{role}}, {{pain_point}}, {{recent_trigger}}.

_deliverability.md covers the domain warming schedule for a new domain, the sending volume ramp, SPF/DKIM/DMARC requirements, the spam-word avoidance list, and reply-rate benchmarks by industry with sources.

Escalate when

  • The list's provenance is unknown, or the user cannot say how the addresses were obtained.
  • EU prospects are in scope and no legitimate-interest basis can be documented.
  • The sending domain is new and the requested volume exceeds a safe warming ramp.
  • The requested ask is a purchase rather than a conversation, and the sequence would need claims the brand cannot substantiate.
  • Complaint rate crosses its ceiling mid-flight — stop the send, do not tune the copy and continue.
  • The user asks to send without the physical address, without a working opt-out, or to a list they will not describe.

Frequently asked questions

What does the Kai Cold Outreach AI skill do?

Build a complete cold email outreach system — ICP definition, sequence architecture, personalization strategy, and batch-produced email sequences with CAN-SPAM/deliverability compliance. Use when "cold outreach", "cold email sequence", "outbound campaign", "prospecting emails", "sales outreach", "build outreach sequence", or any request to create systematic cold email campaigns for lead generation.

Why use Kai Cold Outreach on TypingMind?

Because you install it once and use it with any model. Kai Cold Outreach 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 Kai Cold Outreach in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cgallic/kai-cmo-harness/tree/main/harness/skills-v2/kai-cold-outreach. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Kai Cold Outreach?

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 Kai Cold Outreach?

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

Is the Kai Cold Outreach AI skill free?

It is published on GitHub by cgallic. 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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