# Ops And Scale Os

> The router for Ops & Scale OS. Use when the user says "ops and scale", "GTM engineering", "AI ops", "build the GTM system", "our data is a mess", or is not sure which skill they need. Reads the situation, names the constraint, and routes to exactly one skill. Also use to orient somebody new to the repo. Front door only. It routes and does not do the work: the audit itself is `gtm-systems-audit`, and scoping one agent is `agent-scoping`.

- Skill: `guerrilla2799/ops-and-scale-os` (Agent Skill)
- Install (CLI): `npx skillmds@latest add guerrilla2799/ops-and-scale-os`
- Raw SKILL.md: https://api.skillmd.com/api/skills/guerrilla2799/ops-and-scale-os/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: guerrilla2799 (https://skillmd.com/u/guerrilla2799)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/guerrilla2799/ops-and-scale-os

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# Ops & Scale OS

The entry point. Diagnoses which of the four layers is the constraint and routes to one skill.

## When to use
- First session in a new environment
- The user describes a symptom rather than a task ("our lists are bad", "the agent gives wrong answers")
- Two or more skills could plausibly apply
- Somebody wants a tour of what is here

## The routing question

Ask exactly one thing first: **what is broken, and what does the evidence look like?**

Then route on the symptom, not on the request. People ask for the fix they have heard of, and that is usually a layer above the actual problem.

| Symptom | Actual layer | Route to |
|---|---|---|
| "We need an AI agent for outbound" | Usually data, not agents | `gtm-systems-audit` first |
| Reports disagree with each other | Systems of record | `reporting-architecture` |
| Match rates are low or credits are burning | Data plane | `enrichment-waterfall`, then `credit-and-cost-control` |
| The score does not predict anything | Data plane | `icp-scoring-engine` |
| Duplicates, stale records, bad emails | Data plane | `data-hygiene` |
| Signals fire and nothing happens | Data plane | `signal-pipeline` |
| Nobody uses the thing we built | Agent plane | `agent-rollout` |
| The agent output is confidently wrong | Quality plane | `eval-loop`, then `eval-spec-authoring` |
| Quality was fine and now is not | Quality plane | `eval-calibration` |
| We have too many tools | Systems of record | `martech-stack-audit` |
| Somebody wants a warehouse, a CDP, or reverse ETL | Data plane | `warehouse-and-pipes` |
| People are pasting customer data into a chatbot | Agent plane | `ai-governance` |
| Leads sit untouched, or go to the wrong rep | Systems of record | `lifecycle-and-routing` |
| Nobody agrees what marketing sourced | Systems of record | `attribution-architecture` |
| We do not know where to start | All four | `gtm-systems-audit` |

## The rule that governs routing

**Never route up the stack to solve a problem that lives down the stack.** An agent will not fix a data model, an eval will not fix an agent nobody uses, and a dashboard will not fix a definition nobody agreed on.

If the answer to "what is broken" involves records, fields, duplicates, or scores, the answer is Layer 1 regardless of what the user asked for. Say so plainly, and explain the order.

## The layers

| Layer | Question it answers | Skills |
|---|---|---|
| **Data plane** | Who is worth touching, and when | `data-model-and-sync` · `tam-and-sourcing` · `enrichment-waterfall` · `icp-scoring-engine` · `signal-pipeline` · `data-hygiene` · `credit-and-cost-control` · `warehouse-and-pipes` |
| **Agent plane** | What does the work | `agent-scoping` · `context-portfolio` · `skill-authoring` · `agent-guardrails` · `ai-governance` · `agent-rollout` |
| **Quality plane** | Is any of this good | `eval-spec-authoring` · `eval-loop` · `eval-calibration` · `agent-observability` |
| **Systems of record** | What is true, and who owns it | `martech-stack-audit` · `attribution-architecture` · `lifecycle-and-routing` · `reporting-architecture` |

Gates that run on output regardless of layer: `writing-quality`, `artifact-eval`.

## Cold start, in order

1. `gtm-systems-audit` – score all four layers, get the constraint
2. `data-model-and-sync` – define the objects before building on them
3. `data-hygiene` – clean what exists before enriching it
4. `icp-scoring-engine` – score, then set thresholds from the real distribution
5. `context-portfolio` – write the operating manual before any agent reads from it
6. `agent-scoping` – decide what deserves to be built
7. `ai-governance` – set the data boundary before anything reaches a team
8. `eval-spec-authoring` – write the rubric before the thing it judges
9. `agent-observability` – instrument before scaling

## Output
- Names the constraint in one sentence
- Routes to exactly one skill, with the reason
- States what to do after that skill finishes

## Rules & quality bar
- **One skill at a time.** Loading four skills in parallel bloats context and produces mush
- **Diagnose before routing.** No route without a stated symptom and its evidence
- **Say the unwelcome thing.** If somebody wants an agent and needs a data cleanup, say that first
- **Refuse to build on a broken layer.** Note the dependency and route down the stack

## Related skills
- Everything in this repo. Start at `gtm-systems-audit` when the answer is unclear
- See also: `docs/architecture.md` for the layer model, `docs/build-surface.md` for the build primitives