GTM Engineering skill 01 of 13

GTM Engineering Audit SKILL.md

The GTM Engineering Audit skill makes Claude Code, Codex or another AI agent audit a go-to-market engineering stack from source to revenue. It maps the flow across Clay tables, data providers, scoring, signals, AI copy, CRM and sequencer, measures the funnel and unit costs, scores 14 areas with evidence and builds a 90-day plan with owners, metrics and governance rules.

gtm-engineering-audit/SKILL.md, version 1.0.0, 1,574 words.

GTM engineering stacks grow by accident. A Clay workspace fills with tables nobody owns, three providers enrich the same field, AI columns run on every row whether needed or not, CRM fields multiply, sequences send from mailboxes with no warm-up plan, and nobody can say what a qualified meeting actually costs. Problems stay hidden until reply rates fall, domains get flagged or the credit bill arrives.

This skill audits a go-to-market engineering setup end to end: goals and ICP, data sources and providers, Clay (or similar) tables and workflows, enrichment logic, scoring, signals, AI copy, data quality, CRM and sequencer sync, sending infrastructure, QA, costs, documentation and reporting. It scores each area, finds the leaks that cost the most pipeline or money, and builds a prioritised plan that hands each fix to a specialist skill. It is the entry point for the GTM Engineering set.

Operating principles

  1. Start from pipeline, not tools. Measure what the system produces: qualified accounts, meetings, opportunities and revenue.
  2. Map the whole flow. Leaks hide in the handoffs between tools.
  3. Unit economics matter. Cost per enriched contact, per qualified account and per meeting decides what scales.
  4. Quality before volume. More rows with bad data or weak copy burn domains and reputation.
  5. Own and document everything. Every table, provider and field has an owner and a purpose.

Audit areas

AreaWhat to checkTypical finding
1. Goals and ICPWritten ICP, segments, targets per segmentICP lives in someone's head
2. Data sourcesProviders, coverage, cost, contractsThree providers for the same email field
3. Tables and workflowsStructure, naming, owners, run logic60 tables, 12 in use, no naming convention
4. EnrichmentWaterfall order, match rates, accuracyMost expensive provider runs first
5. ScoringFit and intent scoring rulesEvery account scored "high"
6. SignalsWhich triggers are tracked and usedHiring signals collected but never used
7. AI copyPrompts, inputs, review, resultsGeneric openers; invented facts
8. Data qualityDuplicates, formats, normalisationSame company three times with different names
9. CRM and sequencer syncMapping, ownership, routing, overwritesEnrichment overwrites rep-entered data
10. Sending infrastructureDomains, mailboxes, authentication, volumesSending from the main domain at high volume
11. QASpecs, checks before launchSpot checks only
12. CostsCredits, provider fees, cost per resultNo idea of cost per meeting
13. DocumentationSpecs, runbooks, handoversOne person knows how it works
14. ReportingFunnel from list to revenueOnly send volume and opens tracked

When to use, and when not to

Use it when taking over a GTM stack, before scaling outbound, when results drop, when costs spike, after a new hire inherits workflows, or once a quarter.

Don't use it for paid media or SEO audits (other Marketing skills) or for a single table's pre-launch check (gtm-workflow-qa).

Inputs to ask for, in one message

  1. Revenue goals, ICP and target segments.
  2. Tools: Clay or similar, data providers, CRM, sequencer, email infrastructure.
  3. List of active tables and workflows with owners.
  4. Last 90 days of results: rows processed, sends, replies, meetings, opportunities.
  5. Monthly costs by tool and provider, including credits used.
  6. Known problems and recent changes.

Raw SKILL.md file

.md

This is the exact file agents read, including the credit header and licence notice. Save it as gtm-engineering-audit/SKILL.md.

---
name: gtm-engineering-audit
description: "Audit a GTM engineering stack end to end: ICP, providers, Clay tables and workflows, enrichment, scoring, signals, AI copy, data quality, CRM and sequencer sync, sending infrastructure, QA, costs, documentation and reporting, with a funnel from source to revenue, unit costs, a 0 to 3 scorecard, a 90-day plan and governance rules. Use whenever someone inherits or reviews a Clay or GTM automation setup, wants to scale outbound, sees reply rates or match rates drop, has rising credit or provider costs, or asks where their GTM system is leaking."
license: CC-BY-4.0
metadata:
  author: Afeez Adebayo
  author_url: https://afeezadebayo.com
  author_linkedin: https://www.linkedin.com/in/afeez-adebayo/
  author_x: https://x.com/za_icon
  source: https://afeezadebayo.com/skills-md/marketing/gtm-engineering/gtm-engineering-audit/
  category: marketing
  subcategory: gtm-engineering
  version: "1.0.0"
  created: "2026-10-13"
  updated: "2026-10-13"
---

# GTM Engineering Audit

GTM engineering stacks grow by accident. A Clay workspace fills with tables nobody owns, three providers enrich the same field, AI columns run on every row whether needed or not, CRM fields multiply, sequences send from mailboxes with no warm-up plan, and nobody can say what a qualified meeting actually costs. Problems stay hidden until reply rates fall, domains get flagged or the credit bill arrives.

This skill audits a go-to-market engineering setup end to end: goals and ICP, data sources and providers, Clay (or similar) tables and workflows, enrichment logic, scoring, signals, AI copy, data quality, CRM and sequencer sync, sending infrastructure, QA, costs, documentation and reporting. It scores each area, finds the leaks that cost the most pipeline or money, and builds a prioritised plan that hands each fix to a specialist skill. It is the entry point for the GTM Engineering set.

## Operating principles
1. **Start from pipeline, not tools.** Measure what the system produces: qualified accounts, meetings, opportunities and revenue.
2. **Map the whole flow.** Leaks hide in the handoffs between tools.
3. **Unit economics matter.** Cost per enriched contact, per qualified account and per meeting decides what scales.
4. **Quality before volume.** More rows with bad data or weak copy burn domains and reputation.
5. **Own and document everything.** Every table, provider and field has an owner and a purpose.

## Audit areas
| Area | What to check | Typical finding |
|---|---|---|
| 1. Goals and ICP | Written ICP, segments, targets per segment | ICP lives in someone's head |
| 2. Data sources | Providers, coverage, cost, contracts | Three providers for the same email field |
| 3. Tables and workflows | Structure, naming, owners, run logic | 60 tables, 12 in use, no naming convention |
| 4. Enrichment | Waterfall order, match rates, accuracy | Most expensive provider runs first |
| 5. Scoring | Fit and intent scoring rules | Every account scored "high" |
| 6. Signals | Which triggers are tracked and used | Hiring signals collected but never used |
| 7. AI copy | Prompts, inputs, review, results | Generic openers; invented facts |
| 8. Data quality | Duplicates, formats, normalisation | Same company three times with different names |
| 9. CRM and sequencer sync | Mapping, ownership, routing, overwrites | Enrichment overwrites rep-entered data |
| 10. Sending infrastructure | Domains, mailboxes, authentication, volumes | Sending from the main domain at high volume |
| 11. QA | Specs, checks before launch | Spot checks only |
| 12. Costs | Credits, provider fees, cost per result | No idea of cost per meeting |
| 13. Documentation | Specs, runbooks, handovers | One person knows how it works |
| 14. Reporting | Funnel from list to revenue | Only send volume and opens tracked |

## When to use, and when not to
Use it when taking over a GTM stack, before scaling outbound, when results drop, when costs spike, after a new hire inherits workflows, or once a quarter.

Don't use it for paid media or SEO audits (other Marketing skills) or for a single table's pre-launch check (`gtm-workflow-qa`).

## Inputs to ask for, in one message
1. Revenue goals, ICP and target segments.
2. Tools: Clay or similar, data providers, CRM, sequencer, email infrastructure.
3. List of active tables and workflows with owners.
4. Last 90 days of results: rows processed, sends, replies, meetings, opportunities.
5. Monthly costs by tool and provider, including credits used.
6. Known problems and recent changes.

## Workflow

### Step 1. Map the flow
Draw the path from source to revenue: list building, enrichment, scoring, signals, copy, QA, CRM, sequencer, sending, replies, meetings, pipeline.

### Step 2. Inventory assets
Tables, workflows, providers, AI columns, CRM fields, sequences, domains and mailboxes, each with owner, purpose and last run.

### Step 3. Measure the funnel
Rows sourced, enriched (match rate), qualified (by score), sent, delivered, replied (positive replies), meetings, opportunities, revenue, by segment.

### Step 4. Calculate unit costs
Cost per enriched contact, per qualified account, per positive reply and per meeting.

### Step 5. Score each area 0 to 3
With one line of evidence each.

### Step 6. Find the biggest leaks
Rank by pipeline or cost impact: for example low match rates in a key region, poor deliverability, weak copy, unqualified accounts reaching sequences.

### Step 7. Build the 90-day plan
Top fixes with owner, skill, metric and date; quick wins first.

### Step 8. Set governance
Naming conventions, ownership, change process, QA before launch and a monthly review.

## Funnel template
```
| Stage | Volume | Rate | Cost | Benchmark or target | Problem |
| Accounts sourced | 12,000 | - | £180 | - | - |
| Contacts enriched with valid email | 7,400 | 62% | £1,950 | 75% | Low match in DACH |
| Qualified by score | 3,100 | 42% | - | - | Scoring too loose |
| Sent | 3,100 | - | - | - | - |
| Positive replies | 46 | 1.5% | - | 2%+ | Generic copy |
| Meetings | 22 | 48% of positive | - | - | - |
| Cost per meeting | | | £110 | <£80 | - |
```

## Scorecard template
```
| Area | Score (0-3) | Evidence | Fix | Skill | Owner |
| Enrichment | 1 | Most expensive provider first; 62% match | Reorder waterfall, add regional provider | enrichment-waterfalls | |
| Infrastructure | 0 | Sending 400/day from main domain | Secondary domains, warm-up, limits | outbound-infrastructure | |
```

## Governance basics
- Naming: `<team>-<purpose>-<segment>-<yyyy-mm>` for tables and workflows.
- Every table has an owner, a spec and a status (active, paused, archived).
- Changes to live workflows go through a short checklist and QA.
- Archive unused tables monthly; document what each provider is for.

## Edge cases and judgement calls
| Situation | What to do |
|---|---|
| No historical data | Start tracking now; audit structure and costs first |
| One builder, no documentation | Prioritise documentation and handover before scaling |
| Several teams in one workspace | Folders, naming and ownership by team |
| Very small volume | Focus on ICP, copy and infrastructure; skip complex automation |
| Regulated markets | Add legal review of data sources and outreach rules |
| Sudden drop in replies | Check infrastructure and deliverability first |

## Handoffs to specialist skills
- Table structure: `clay-table-design`
- Provider logic: `enrichment-waterfalls`
- Scoring: `icp-account-scoring`
- Triggers: `signal-based-outbound`
- AI personalisation: `ai-copy-columns`
- Data cleaning: `data-deduplication-normalisation`
- CRM and sequencer: `crm-sync-routing`
- Sending setup: `outbound-infrastructure`
- Pre-launch checks: `gtm-workflow-qa`
- Costs: `gtm-cost-control`
- Specs and runbooks: `gtm-workflow-documentation`
- Results: `gtm-reporting`

## Worked example
A B2B SaaS team ran outbound through 58 Clay tables built by one person who had left. The audit found 14 tables in use, three providers enriching emails with the most expensive first, a 62% match rate in Germany, every account scored "high", generic AI openers, enrichment overwriting rep notes in the CRM and 400 emails a day from the main domain. Cost per meeting was about £110. The 90-day plan reordered the waterfall and added a regional provider, rebuilt scoring with three tiers, moved sending to warmed secondary domains, rewrote AI prompts with real signals, protected rep-owned CRM fields and introduced specs, QA and naming. After a quarter, match rate rose to 78%, positive reply rate doubled and cost per meeting fell below £70.

## Common mistakes
- Measuring sends and opens instead of meetings and pipeline.
- Adding providers without measuring match rates and cost.
- No owner or documentation for tables.
- Scaling volume before fixing infrastructure and copy.
- No QA before launches.

## Output format
```
# GTM engineering audit: <company>, <date>
## Summary: biggest leaks and first moves
## Flow map
## Asset inventory
## Funnel and unit costs
## Scorecard
## 90-day plan
## Governance rules
```

## Self-check before you answer
- Is the funnel measured from source to revenue?
- Are unit costs calculated?
- Is every area scored with evidence?
- Does each fix have a skill, owner, metric and date?

---
Created by Afeez Adebayo, Marketing, SEO & Growth Expert
Website: https://afeezadebayo.com
LinkedIn: https://www.linkedin.com/in/afeez-adebayo/
X: https://x.com/za_icon
Source: https://afeezadebayo.com/skills-md/marketing/gtm-engineering/gtm-engineering-audit/

Licence: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). You may copy, share and adapt this skill, including for commercial use, as long as you credit Afeez Adebayo and link to the source URL above. Keep this notice in any copy or adapted version.

Workflow

Step 1. Map the flow

Draw the path from source to revenue: list building, enrichment, scoring, signals, copy, QA, CRM, sequencer, sending, replies, meetings, pipeline.

Step 2. Inventory assets

Tables, workflows, providers, AI columns, CRM fields, sequences, domains and mailboxes, each with owner, purpose and last run.

Step 3. Measure the funnel

Rows sourced, enriched (match rate), qualified (by score), sent, delivered, replied (positive replies), meetings, opportunities, revenue, by segment.

Step 4. Calculate unit costs

Cost per enriched contact, per qualified account, per positive reply and per meeting.

Step 5. Score each area 0 to 3

With one line of evidence each.

Step 6. Find the biggest leaks

Rank by pipeline or cost impact: for example low match rates in a key region, poor deliverability, weak copy, unqualified accounts reaching sequences.

Step 7. Build the 90-day plan

Top fixes with owner, skill, metric and date; quick wins first.

Step 8. Set governance

Naming conventions, ownership, change process, QA before launch and a monthly review.

Funnel template

| Stage | Volume | Rate | Cost | Benchmark or target | Problem |
| Accounts sourced | 12,000 | - | £180 | - | - |
| Contacts enriched with valid email | 7,400 | 62% | £1,950 | 75% | Low match in DACH |
| Qualified by score | 3,100 | 42% | - | - | Scoring too loose |
| Sent | 3,100 | - | - | - | - |
| Positive replies | 46 | 1.5% | - | 2%+ | Generic copy |
| Meetings | 22 | 48% of positive | - | - | - |
| Cost per meeting | | | £110 | <£80 | - |

Scorecard template

| Area | Score (0-3) | Evidence | Fix | Skill | Owner |
| Enrichment | 1 | Most expensive provider first; 62% match | Reorder waterfall, add regional provider | enrichment-waterfalls | |
| Infrastructure | 0 | Sending 400/day from main domain | Secondary domains, warm-up, limits | outbound-infrastructure | |

Governance basics

  • Naming: <team>-<purpose>-<segment>-<yyyy-mm> for tables and workflows.
  • Every table has an owner, a spec and a status (active, paused, archived).
  • Changes to live workflows go through a short checklist and QA.
  • Archive unused tables monthly; document what each provider is for.

Edge cases and judgement calls

SituationWhat to do
No historical dataStart tracking now; audit structure and costs first
One builder, no documentationPrioritise documentation and handover before scaling
Several teams in one workspaceFolders, naming and ownership by team
Very small volumeFocus on ICP, copy and infrastructure; skip complex automation
Regulated marketsAdd legal review of data sources and outreach rules
Sudden drop in repliesCheck infrastructure and deliverability first

Handoffs to specialist skills

  • Table structure: clay-table-design
  • Provider logic: enrichment-waterfalls
  • Scoring: icp-account-scoring
  • Triggers: signal-based-outbound
  • AI personalisation: ai-copy-columns
  • Data cleaning: data-deduplication-normalisation
  • CRM and sequencer: crm-sync-routing
  • Sending setup: outbound-infrastructure
  • Pre-launch checks: gtm-workflow-qa
  • Costs: gtm-cost-control
  • Specs and runbooks: gtm-workflow-documentation
  • Results: gtm-reporting

Worked example

A B2B SaaS team ran outbound through 58 Clay tables built by one person who had left. The audit found 14 tables in use, three providers enriching emails with the most expensive first, a 62% match rate in Germany, every account scored "high", generic AI openers, enrichment overwriting rep notes in the CRM and 400 emails a day from the main domain. Cost per meeting was about £110. The 90-day plan reordered the waterfall and added a regional provider, rebuilt scoring with three tiers, moved sending to warmed secondary domains, rewrote AI prompts with real signals, protected rep-owned CRM fields and introduced specs, QA and naming. After a quarter, match rate rose to 78%, positive reply rate doubled and cost per meeting fell below £70.

Common mistakes

  • Measuring sends and opens instead of meetings and pipeline.
  • Adding providers without measuring match rates and cost.
  • No owner or documentation for tables.
  • Scaling volume before fixing infrastructure and copy.
  • No QA before launches.

Output format

# GTM engineering audit: <company>, <date>
## Summary: biggest leaks and first moves
## Flow map
## Asset inventory
## Funnel and unit costs
## Scorecard
## 90-day plan
## Governance rules

Self-check before you answer

  • Is the funnel measured from source to revenue?
  • Are unit costs calculated?
  • Is every area scored with evidence?
  • Does each fix have a skill, owner, metric and date?

When to use this skill, and when not to

Use it when you inherit a Clay workspace, before scaling outbound, when reply or match rates drop, when credit bills rise or once a quarter.

GTM stacks grow by accident: unowned tables, overlapping providers, AI columns on every row and nobody able to say what a meeting costs. Problems stay hidden until results or budgets slip.

For a single table's pre-launch check, use GTM Workflow QA.

Example prompts

  • “Audit our Clay and outbound setup.”
  • “What does a meeting from outbound cost us?”
  • “I inherited 58 Clay tables. Where do I start?”
  • “Why did our reply rate halve this quarter?”
  • “Build a 90-day plan to fix our GTM system.”

Example output

The skill returns a fixed structure. A shortened example for an imaginary site:

Funnel: 12,000 accounts -> 7,400 valid emails (62%) -> 22 meetings
Cost per meeting: \u00a3110 (target under \u00a380)
Leaks: costly provider first, every account tier high, main-domain sending
Scorecard: 14 areas, 0 to 3 each
90-day plan: 8 fixes with owners and metrics

The audit measures meetings, pipeline and unit costs, not sends and opens, and every fix is handed to a specialist skill.

What the agent needs from you

The skill asks for revenue goals and ICP, tools and providers, active tables with owners, 90 days of results and monthly costs including credits.

How this skill hands off to related skills

How to run GTM Engineering Audit step by step

  1. Install the skill as gtm-engineering-audit/SKILL.md.
  2. Share goals, tools and results.
  3. Map the flow.
  4. Measure the funnel and unit costs.
  5. Score the 14 areas.
  6. Agree the 90-day plan.

Situations this skill handles

GTM Engineering Audit handles these situations:

SituationWhat the skill does
No historical dataStructure and costs first
One builder, no docsDocumentation before scaling
Several teamsFolders and ownership
Small volumeICP, copy, infrastructure
Regulated marketsLegal review of sources
Sudden reply dropCheck deliverability first

What makes this skill different

Most GTM reviews look at one tool. This audit follows data from source to revenue, puts a cost on every stage and ranks fixes by pipeline impact, so effort goes where it pays.

Practical tips from real projects

  • Start from pipeline.
  • Map the whole flow.
  • Unit economics matter.
  • Quality before volume.

A worked example: a B2B SaaS team ran outbound through 58 Clay tables built by someone who had left. The audit found 14 tables in use, three providers enriching emails with the most expensive first, a 62% match rate in Germany, every account scored high, generic AI openers, enrichment overwriting rep notes and 400 emails a day from the main domain, with cost per meeting around one hundred and ten pounds. The plan reordered the waterfall, rebuilt scoring with tiers, moved sending to warmed secondary domains, rewrote prompts around real signals, protected CRM fields and introduced specs and QA. After a quarter, match rate reached 78%, positive replies doubled and cost per meeting fell below seventy pounds.

The 14 areas are goals and ICP, data sources, tables and workflows, enrichment, scoring, signals, AI copy, data quality, CRM and sequencer sync, sending infrastructure, QA, costs, documentation and reporting. Each gets a score from zero to three with one line of evidence, a fix, the skill that owns it and an owner. The funnel template records volume, rate, cost and target at each stage, from accounts sourced through valid emails, qualified accounts, sends and positive replies to meetings and cost per meeting, so the biggest leak is obvious.

The workflow maps the flow from list building to revenue, inventories tables, providers, AI columns, CRM fields, sequences, domains and mailboxes with owners and last-run dates, measures the funnel by segment, calculates unit costs, scores each area, ranks leaks by pipeline or cost impact and builds a 90-day plan with quick wins first. Governance follows: a naming pattern of team, purpose, segment and month, an owner, spec and status for every table, a short checklist and QA for changes to live workflows, and monthly archiving of unused tables.

Edge cases are handled pragmatically. Without history, structure and costs come first while tracking starts. A single undocumented builder means documentation and handover before scaling. Shared workspaces get folders, naming and ownership by team, very small volumes focus on ICP, copy and infrastructure rather than automation, regulated markets add legal review of data sources and outreach, and a sudden reply drop sends the audit straight to deliverability. Common mistakes are measuring sends and opens, adding providers without benchmarks, unowned tables, scaling before fixing infrastructure and copy, and launching without QA.

The output is a short audit document: a summary of the biggest leaks and first moves, a flow map, the asset inventory, the funnel with unit costs, the scorecard, the 90-day plan and governance rules. It works with Claude Code, Codex or any agent that can read exports and tables, and it never changes live workflows itself; the team approves each fix.

Run it again at the end of the 90 days to measure progress against the original funnel and costs, and use the comparison to set the next quarter's priorities.

Teams usually find the largest savings and pipeline gains in three places: enrichment order, scoring tiers and sending infrastructure.

Each finding in the audit links to evidence, such as a table export, an invoice line or a funnel number, so decisions can be checked rather than argued. Leaders see the cost of each leak in pipeline or pounds, which makes it easier to fund the fixes that matter most and to stop work that does not pay back.

Frequently asked questions

A review of the data, tools, workflows, costs and results behind go-to-market automation, scored by area with a prioritised plan.

The funnel from accounts sourced to meetings, opportunities and revenue, plus unit costs such as cost per meeting.

Quarterly, and whenever results drop, costs spike or ownership changes.

Expensive providers first, loose scoring, generic AI copy, CRM overwrites, sending from the main domain and no QA.

No. Without history, audit structure and costs first and start tracking now.

Naming conventions, owners per table, a change checklist, QA before launch and monthly reviews.

Changelog

  • 1.0.0, 10 October 2026: first release.

Use, adapt and share this skill under CC BY 4.0: credit Afeez Adebayo and link to this page.