journey-architect

journey-architect is a skill for Claude Code, Codex from varunk130/ai-gtm-skill-library. It costs 51 tokens per session (1,050 once invoked), scanned A, original, MIT.

A framework for mapping how a potential customer moves from first learning about a problem to recommending a product. It breaks that journey into seven stages and scores friction at each stage.

In plain words
What is it for?
Use it to plan customer journeys, improve conversion funnels, organize content by buying stage, design sales processes, and improve customer experience.
Why use it?
It helps reveal where people lose interest, hesitate, or fail to move toward a purchase.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to plan customer journeys, improve conversion funnels, organize content by buying stage, design sales processes, and improve customer experience.

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Install with agentmods
npx agentmods add skills/varunk130/ai-gtm-skill-library/journey-architect
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.

Any agent
npx skills add varunk130/ai-gtm-skill-library --skill journey-architect
Clone the repo
git clone --depth 1 https://github.com/varunk130/ai-gtm-skill-library

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

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README.md
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Your own site
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Per session 51 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00051 $0.01050
Opus 5.5 $0.00020 $0.00420
Sonnet 5.5 $0.00010 $0.00210
Haiku 4.5 $0.00005 $0.00105

Measured 1mo ago against content hash bc0ea7beb24a, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

journey-architect 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 1mo 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.

gtm-skills/journey-architect/SKILL.md · 97 lines

How it starts

The opening of the file, as written. The whole thing — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Journey Architect (7-GATE Model)

Design the complete customer journey with measurable gates. Maps every touchpoint from first awareness through purchase, activation, and advocacy with friction scoring at each stage.

When to Use

  • Pre-launch journey design
  • Conversion funnel optimization
  • Content strategy planning
  • Sales process design
  • Customer experience improvement

What You'll Need

Critical inputs (ask if not provided):

  • Product/service being mapped
  • Primary buyer persona(s)
  • Current sales motion (PLG, sales-led, hybrid)

Nice-to-have:

  • Market Analyzer segment data
  • Existing funnel metrics
  • Customer feedback or interview data

Process

Step 1: Define the 7 Gates

Each gate represents a cognitive/behavioral milestone customers must pass through:

Gate Name Customer State Key Question They Ask
G1 Awakening Recognizes they have a problem "Is this actually a problem worth solving?"
G2 Exploration Begins researching solutions "What options exist to solve this?"
G3 Consideration Builds a shortlist "Which 2-3 solutions should I evaluate seriously?"
G4 Conviction Commits to a solution "Can I justify this purchase internally?"
G5 Activation Starts using the product "How do I get value from this quickly?"
G6 Integration Product becomes embedded in workflow "How does this fit into everything else I do?"
G7 Amplification Becomes an advocate "Who else needs to know about this?"

Step 2: Per-Gate Analysis

For EACH gate, document:

Entry Trigger: What event causes the customer to enter this gate?

  • Example G1: "Budget review reveals 30% waste in current tooling"

Information Needs: What content/evidence do they need?

  • Example G3: "Feature comparison matrix, pricing transparency, peer reviews"

Touchpoints: Where do they interact?

  • Example G2: "Web search, peer communities, review sites, analyst reports"

Read the full file on GitHub · 97 lines

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. 1mo ago First seen · 97 lines · 51 tokens per session scan A bc0ea7beb24a

Subscribe to this mod's changes

journey-architect is a skill published in the GitHub repository varunk130/ai-gtm-skill-library (7 stars, last pushed 10d ago), licensed MIT. It adds 51 tokens to every session and 1,050 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.

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