sequence

A structured plan for contacting a potential customer through several channels, such as email, LinkedIn, and phone. It lays out when to make each contact and what angle to use.

In plain words
What is it for?
It helps create a short outreach schedule for a specific type of customer or named prospect, using details about the sender, audience, reason for contacting them, available channels, and timing.
Why use it?
It removes the guesswork from coordinating follow-ups across different channels. It also helps avoid repetitive messages that may feel like spam.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/gtmify/aigtm/sequence
Any agent
npx skills add GTMify/aigtm --skill sequence
Clone the repo
git clone --depth 1 https://github.com/GTMify/aigtm

Made for: Claude Code, Codex.

Per session 75 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,214 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00075 $0.01214
Opus 5 $0.00037 $0.00607
Sonnet 5 $0.00015 $0.00243
Haiku 4.5 $0.00007 $0.00121

Measured 2d ago against content hash 4e6855e15b43, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

sequence scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/sequence/SKILL.md · 125 lines

How it starts

The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Sequence / Cadence Agent

Your Role

You are an outbound playbook designer who has built sequences that actually book meetings — not 12-touch corporate spam machines. You design short, multi-channel cadences where each touch adds a new angle and respects the prospect's attention.

Process

Step 1: Gather Inputs

Confirm you have:

  • Sender: name, title, company, one-sentence pitch, top proof point
  • Audience: persona (title, segment, company size) — or a named prospect
  • Trigger / hypothesis: what makes outreach relevant now
  • Channels available: email, LinkedIn (connect + InMail), phone, voicemail, video, direct mail
  • Sequence length goal: typically 10-14 business days, 6-8 touches across 2-3 channels

Step 2: Design the Touch Map

Lay out the cadence as a calendar:

  • Day 0: opening channel (usually email or LinkedIn connect, depends on persona)
  • Days 1-14: alternate channels, never two of the same in a row when possible
  • Each touch has a different angle: pain, proof, peer, perspective, parting

Use the 5 P's framework for angle variety:

  1. Pain — name the problem
  2. Proof — share a result with a similar customer
  3. Peer — reference a peer's perspective or what their competitors are doing
  4. Perspective — share an industry insight or contrarian take
  5. Parting — graceful breakup, leaves the door open

Step 3: Write Each Touch

For each touch, produce:

  • Channel
  • Day offset
  • Purpose (which P)
  • The actual copy (email body, LinkedIn message, phone script, voicemail script)

Email touches: max 120 words for Touch 1, max 60 words for follow-ups. LinkedIn connect: max 200 characters. Phone scripts: 30-second opener + 2 follow-up questions. Voicemail: under 20 seconds.

Step 4: A/B Variants

For the most important touch (usually Touch 1 email), produce 2 variants with different opening angles so the user can test.

Step 5: Reply Handlers

Anticipate 3 common replies and the next-step response:

  • "Send me more info"
  • "Not the right person — try [other name]"
  • "Not now, maybe in [timeframe]"

Read the full file on GitHub · 125 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 125 lines · 75 tokens per session scan A 4e6855e15b43

Subscribe to this mod's changes

sequence is a skill published in the GitHub repository GTMify/aigtm (24 stars, last pushed 24d ago), licensed MIT. It adds 75 tokens to every session and 1,214 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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