mcpbeat

Cold Outreach Sequence

brianrwagner/cold-outreach-sequence

Build personalized cold outreach sequences for LinkedIn and email. Use when someone needs to reach prospects, warm up cold leads, or build a systematic outreach engine. Covers research, connection requests, follow-ups, and conversion.

3k tokens
context cost
the whole folder, loaded on every use
2
files
instructions only
0
copies elsewhere
how many repositories repackaged it
386
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/BrianRWagner/ai-marketing-claude-code-skills --skill cold-outreach-sequence

The instruction itself

14 sections, as written by the author

Cold Outreach Sequence

Here's what I've learned about cold outreach: the word "cold" is the problem.

Spray-and-pray templates don't work. 10 minutes of research + a specific reference = not cold anymore. This skill builds the second kind.


Mode

Detect from context or ask: *"One message, full sequence, or full outreach system?"*

| Mode | What you get | Best for |

|------|-------------|----------|

| quick | 1 connection request + 1 follow-up for a single prospect | Testing an angle, one-off outreach |

| standard | Full 4-touch sequence for a single prospect | Active pipeline, individual targets |

| deep | Multi-prospect sequence system + A/B variants + tracking framework | Launching an outreach campaign |

Default: standard — use quick if they give you one name and say "draft something." Use deep if they're building a repeatable outreach engine.


Context Loading Gates

Before writing any message, collect:

  • [ ] Prospect name and company — full name, company, role/title
  • [ ] Research signals — run tool calls first (see below); do not write without them
  • [ ] Sender positioning — what does the sender do, for whom, with what result? (Use positioning-basics output if available)
  • [ ] Platform — LinkedIn DM, email, or both?
  • [ ] Batch size — how many prospects? (determines tier assignment)

Research tool calls — run before writing:

web_search('[Company] [Founder/Name] news 2026')
web_search('[Company] funding recent')
web_search('[Person name] [Company] LinkedIn')

Personalization constraint: Do not write a Tier 1 message without a named specific signal from research. If search yields 0 signals, default to Tier 3 and say so explicitly.


Phase 1: Research & Signal Assessment

For each prospect, document findings before drafting:

Signal types (ranked by message strength):

  • Recent news event (funding, launch, hire, press) → strongest signal
  • Recent LinkedIn post activity → strong signal
  • Company stage/growth data → medium signal
  • Role + industry awareness only → weak signal (Tier 3)

Personalization tier assignment:

| Research Result | Tier | Approach |

|---|---|---|

| Named signal (news + post + context) | Tier 1 | Fully custom, reference signal in every message |

| Company info + role context | Tier 2 | Template + personalized opener |

| No signals found | Tier 3 | Volume template, minimal customization |


Phase 2: Sequence Generation

Connection Request (LinkedIn) — 300 chars max

Formula: [Specific observation from research] + [Simple reason to connect]

Rules:

  • No pitching
  • Prove you did research (name the signal)
  • One sentence, conversational
  • Never "I'd love to pick your brain"

By signal type:

Recent funding: "Congrats on the Series A — the [investor] backing is a smart signal. Would love to connect."

Recent post: "Your post on [specific topic] resonated — been thinking the same thing. Happy to connect."

News/launch: "Saw the [product] launch — [specific detail] is smart positioning. Would love to connect."

First Message (After Accept — Wait 24-48 Hours)

Formula: [Thanks] + [Bridge to relevance] + [Light value] + [Soft question]

Template:

Thanks for connecting. I work with [ICP description] on [specific outcome].

Curious — is [relevant function] something you own directly at [Company], 
or is that still founder-led?

Happy to share what I'm seeing work at similar-stage companies either way.

Follow-Up #1 (Day 7)

Formula: [Light nudge] + [New signal or angle] + [Easy out]

Constraint: Do NOT write "following up" with nothing new. Add one new piece:

  • A relevant article or trend
  • A related insight you recently had
  • A connection to something they posted

Template:

Bumping this up — came across [specific article/trend/insight] and 
thought of your situation at [Company].

[One sentence on why it's relevant to them.]

Happy to share more if useful. If not, no worries.

Follow-Up #2 (Day 14)

Shift to email if LinkedIn hasn't converted, or try a different angle.

Subject line options:

  • "[Company]'s [function] as you scale"
  • "Saw your [post/news] — quick thought"
  • "Question about [specific thing they're doing]"

Email structure:

[1-line hook tied to their specific situation]

[2-3 sentences: why you're reaching out + one proof point]

[Soft CTA — 1 sentence]

Break-Up Message (Day 21)

I'll assume timing isn't right — totally get it. 

If [relevant pain point] becomes a priority down the road, happy to reconnect. 
Best of luck with [specific thing they're working on based on research].

Post-break-up action: Add to 6-month re-engagement list with a resurface date.


Phase 3: Self-Critique Pass (REQUIRED)

After generating the full sequence, evaluate:

  • [ ] Does every message reference the specific signal from research, or are they generic?
  • [ ] Is the connection request under 300 characters?
  • [ ] Does the first message ask a question (invite dialogue) rather than pitch?
  • [ ] Does follow-up #1 add something genuinely new, or is it just "following up"?
  • [ ] Does the break-up message reference something specific about their situation?
  • [ ] Did I correctly assign the personalization tier, or am I over-personalizing a Tier 3 prospect?

Flag any issue: "The first message doesn't include a soft question — it reads as a pitch. Revised to invite dialogue."


Pipeline Tracking Table

Always output a tracking table for the batch:

| Prospect | Company | Platform | Tier | Sent Date | Response | Stage | Next Action | Resurface Date |
|---|---|---|---|---|---|---|---|---|
| [Name] | [Co] | LinkedIn | 1 | [date] | — | Connection sent | Wait 24-48h | — |
| [Name] | [Co] | Email | 2 | [date] | — | First email sent | Follow-up Day 7 | — |

Iteration Protocol

After each response (or non-response), ask:

  • Did the connection request get accepted? If low acceptance rate → revise the observation line
  • Did the first message get a reply? If no → was the question soft enough, or did it feel like a pitch?
  • Did follow-ups get ignored? If yes → try a different angle or acknowledge the silence directly

Output Structure

## Outreach Sequence: [Prospect Name] — [Date]

### Research Summary
- Signal type: [news / post / company info / none]
- Signal found: "[Specific detail]"
- Personalization tier: [1/2/3]
- Source: [URL or platform]

### Sequence

**Connection Request (LinkedIn):**
[Text — max 300 chars]

**First Message (Day 1-2 after accept):**
[Text]

**Follow-Up #1 (Day 7):**
[Text]

**Follow-Up #2 (Day 14):**
Platform: [LinkedIn / Email]
Subject: [if email]
[Text]

**Break-Up (Day 21):**
[Text]

### Pipeline Entry
| Prospect | Company | Platform | Tier | Stage | Next Action | Resurface Date |
|---|---|---|---|---|---|---|
| [Name] | [Co] | [Platform] | [Tier] | Connection sent | Wait 24-48h | — |

### Self-Critique Notes
[Any issues flagged + revisions made]

*Skill by Brian Wagner | AI Marketing Architect | brianrwagner.com*

How to use it

Copy the folder

Take brianrwagner/cold-outreach-sequence from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.