cargo-project

Cargo project — a Cargo workspace, declared in a repo

Use this skill to define a Cargo workspace in TypeScript (define* builders from @cargo-ai/cdk) and reconcile it to live infrastructure with cargo-ai project deploy. It is the declarative counterpart to the imperative capability skills: instead of running one CLI command per resource, you write the whole graph once and deploy it repeatably, with a deploy state — held in your workspace, pointed at by a committed cargo.state.json — linking your code to what Cargo created.

"Project" and "workspace" are two different things — keep them apart. A workspace is the Cargo tenant you sign into: it holds the models, connectors, agents, mailboxes and credits, and it is what login --workspace-name selects and what whoami reports. A project is the repo that declares resources and deploys them into a workspace: it is what project init scaffolds, what cargo.state.json points from, and what --dir locates. One project deploys into one workspace at a time — the workspace guard refuses a deploy when the state's workspace isn't the selected one — and the same project reaches a dev and a prod workspace through a different deploy state each. Say "project" for the repo, and don't name a project directory my-workspace.

Bootstrap

Already signed in (cargo-ai whoami returns a workspace)? Skip to the next section.

npm install -g @cargo-ai/cli            # no global install? prefix every command with `npx @cargo-ai/cli`
cargo-ai login --email you@company.com  # emailed code, no browser; creates the account on first use
                                        # alternatives: --oauth (browser) · --token <api-token> (CI)
cargo-ai whoami                         # confirm the active workspace before any write
cargo-ai project --help                     # `unknown command` = CLI too old; reinstall @cargo-ai/cli@latest

Two CDK-specific extras: the project needs @cargo-ai/cdk as a dependency for the define* builders you import (cargo-ai project init scaffolds a package.json with it — then npm install), and the cargo-ai project domain ships with the CLI itself.

Every command prints JSON to stdout; failures exit non-zero with {"errorMessage": "..."}. Anything that creates a run or a batch is async — pass --wait-until-finished or poll the matching get. When the full skill bundle is installed, ../cargo/references/prerequisites.md adds the CLI version pin, token scopes, and the admin-only surface.

1) What this skill governs

• Authoring every Cargo resource with a define* builder that returns a handle; wiring resources by passing handles to each other (the dependency graph is your variable graph).
• Deploying the graph: plan (offline diff) → deploy (create/update, write state) → destroy (tear down). Plus drift (refresh), adoption (import), and recovery (rollback).
• Typing the config against your workspace's real integration schemas (cargo-ai project types).

The CDK spans every resource kind — so it overlaps every imperative capability skill (cargo-connection, cargo-storage, cargo-ai, cargo-orchestration, cargo-content, cargo-hosting, …). Which to reach for is the first decision:

2) CDK or the CLI? — the routing decision

Declarative (this skill) vs imperative (a capability skill).

Use the CDK when the user is managing resources as an artifact:

• "Set up / stand up / bootstrap a whole workspace (as code / from a template)."
• "Make this reproducible / version-controlled / in git / repeatable across environments (dev → prod)."
• "Deploy these connectors + models + agents together" (a multi-resource graph wired by dependency).
• Anything that should be re-runnable and diffable, where losing the definition would be a problem.

Use the matching capability skill (imperative cargo-ai <domain>) when the user is doing a one-off operation or exploring:

• "Create one connector", "add a column to this model", "list connectors", "run this workflow", "query storage", "read this agent's memory."
• Any read, ad-hoc query, or single mutation that doesn't need to live in code.

When unsure, ask whether the result should be committed and re-deployable. If yes → CDK. If it's a quick action or a read → the capability skill (see the cargo router to pick the right domain).

3) The lifecycle

cargo-ai project init <dir>     scaffold from getcargohq/cargo-manifest; resources in infra/
        │
cargo-ai project types          generate per-workspace types for typed config (optional)
        │
   (author define* files)   importing a .ts file IS registration — no manifest
        │
cargo-ai project plan           offline: compile the graph, diff against the deploy state
        │
cargo-ai project deploy         create/update resources in dependency order, write state
        │
cargo-ai project destroy        tear down resources recorded in state

project plan says what resources change; it doesn't show what a play does. For a definePlay / defineTool graph past three nodes, present a Mermaid flowchart of the node graph alongside the plan — routing, fallbacks, and which nodes bill on every scheduled run are what the reviewer is approving. Generate it from the deployed release after the first deploy, or from the node array while authoring: ../cargo-orchestration/references/node-diagram.md.

Side branches: cargo-ai project check (validate the tree, no state, no API calls — the CI/editor subset of plan) · cargo-ai project info (what is here: every declared resource, the file that declared it, whether it is deployed) · cargo-ai project refresh (read-only drift report) · deploy --refresh (re-apply code over out-of-band edits) · deploy --prune (delete resources removed from code) · cargo-ai project import <id> <uuid> (bind an existing live resource into state) · cargo-ai project pull (generate define* source from a live workspace and adopt it) · cargo-ai project rollback (restore the pre-deploy state snapshot) · cargo-ai project state (inspect and repoint the deploy state).

plan and info answer different questions. plan answers what will deploy do — its unit is the change, and it exits non-zero so CI can gate on it. info answers what is here — its unit is the resource, and it never fails. check is plan minus the diff: it needs no state, so it is what an editor or a pre-commit hook runs. Running cargo-ai project with no arguments does info inside a project and init outside one.

4) Documentation hierarchy

• Level 1 — SKILL.md (this file): the decision model, lifecycle, critical rules, and routing.
• Level 2 — Guides: guides/authoring-resources.md, guides/deploy-and-state.md, guides/typed-config.md.
• Level 2.5 — Recipes: recipes/*.md — step-by-step playbooks to follow as your execution plan.
• References — references/resources.md (the full builder catalog), references/commands.md (every cargo-ai project subcommand + flags), references/troubleshooting.md, and references/examples/full-workspace.md.

5) Read behavior — match the task to a doc and READ IT

When the task involves…	Read this first	What it gives you
Writing define* files, wiring resources, secret()/env(), defineWorkflow bodies (tool/play logic)	guides/authoring-resources.md	The builder catalog, the handle/ref model, secrets, and how workflow bodies compile.
plan / deploy / destroy, the state file, drift, adopting existing resources, CI	guides/deploy-and-state.md	The deploy lifecycle, cargo.state.json semantics, drift/import/rollback, async builds.
Typed config, cargo-ai project types, tsconfig wiring, integrations.* in workflow bodies	guides/typed-config.md	What project types generates and how to wire it into your project.
A field/spec/output for a specific builder	references/resources.md	Every builder → spec fields → which ref each takes → outputs.
Exact command flags	references/commands.md	Every cargo-ai project subcommand and its flags.
A deploy error / footgun	references/troubleshooting.md	The known failure modes and fixes.
A known GTM outcome, before authoring one	references/cookbooks.md	The cookbook menu: gtm-skills that carry a worked CDK example, and the adaptations each supports.

Cookbooks — check the menu before authoring a known outcome from scratch

getcargohq/gtm-skills holds, beside its one-off skills, cookbooks: skills that carry worked CDK resources, the same job as a deployed pipeline that keeps producing the result (TAM building, account scoring, contact sourcing, routing engine, AI SDR, rep cockpit, …). Every folder is self-contained: its own models, connectors and folders, no shared foundation, no requires graph.

The menu is local: references/cookbooks.md. Read it before authoring a common GTM outcome from scratch. It is generated from gtm-skills' catalog.json, so it cannot drift.

A cookbook is a worked example, not a template to fill in. Each one declares in its SKILL.md what may be reshaped, what must hold or it stops working, and what has to be answered either way, and it carries its own procedure. project add is the copy step in that procedure:

cargo-ai project add cookbook/tam-building               # inside a CDK project
cargo-ai project init my-project --cookbook tam-building # no project yet: both at once

That writes the resources to infra/tam-building/ and the procedure to .claude/skills/tam-building/, skipping any file it would overwrite. Then start the skill at its Adapt section — its opening steps are written for someone who found the folder on GitHub and still has to place it, so following them from the top scaffolds a second project and copies the folder in again.

What is left after the copy is the part only you can do: reconcile it with what is already declared, adapt the copied files in place to the project's real shape (do not regenerate them from the skill's prose — the safety lives in the TypeScript), plan and stop, deploy on a yes, walk its Done when.

If you are mid-task and the skill is not in this session, npx skills add getcargohq/gtm-skills/<slug> fetches the procedure alone and you can read .agents/skills/<slug>/SKILL.md directly; no reload needed. To read one without installing, npx skills use getcargohq/gtm-skills@<slug> prints it. Neither brings the CDK resources — for those you still want project add.

Routing rule: one-off versus standing. A user who wants the list today wants cargo-gtm (or gtm-skills' one-off build-tam-list); a user who wants a pipeline that keeps producing it wants tam-building. The same words describe both ("build our TAM"), so listen for whether the result is meant to keep arriving. A cookbook matches → install it and follow it. No match → author from the recipes below.

Never cargo-ai project init --force into a directory that is not empty. It replaces the project's package.json and reverts adapted code, while cargo.state.json survives, so the next plan diffs a live workspace against code nobody wrote. Copy the skill folder in as a sibling instead.

Caveat: the examples typecheck, but they are not yet deploy-verified against a live workspace, and every one is to-be-approved. Treat each skill's Done when as the acceptance test, and always review cargo-ai project plan before deploying.

Recipes — follow step-by-step when one matches

Recipe	Use when…
recipes/scaffold-a-project.md	Standing up a new project from scratch (init → types → plan → deploy).
recipes/add-connector-and-model.md	Adding a data source + a model sourced from it, wired by handle.
recipes/build-an-agent.md	Composing a model + tool + agent (with uses / models / tools) and deploying.
recipes/migrate-existing-workspace.md	Bringing an already-live workspace under a project via project import.
recipes/deploy-from-ci.md	Deploying non-interactively from CI (token auth + committed state).

6) Critical rules

• Commit cargo.state.json — it is a pointer now, not the state. The deploy state lives in your workspace; the repo commits only {"stateUuid": "8f2c…"}. project init creates the state and writes that pointer, so it lands in the scaffold commit. Commit it: without the uuid a fresh checkout can't find its state, and a deploy will not quietly create a replacement (that would orphan everything the old one tracks). The state records only uuids, hashes and outputs — never secret values. It is still the only handle on a deployed play, agent, or alert (they have no slug); recover a lost link with project state bind <uuid>, or per-resource with cargo-ai project import. Git-ignore the working files (project init scaffolds this):

  .cargo-ai/
  cargo.state.lock
  cargo.state.bak.json
  cargo.state.cache.json
  cargo.state.audit.jsonl
  

  One state per repo, and at most 10 live states per workspace:

  cargo-ai project state list            # every state here, and which one this project is on
  cargo-ai project state create          # create one for this project, write the pointer
  cargo-ai project state bind <uuid>     # repoint at an existing one
  

  A project scaffolded before states moved to the workspace has the resource map inline in cargo.state.json, and keeps deploying against that file for as long as you leave it there — nothing migrates behind your back. state create is what moves it: the map goes onto a new state, the file becomes a pointer, and you commit it. Don't migrate without telling the team, since a teammate who deploys before pulling the new pointer is deploying from a state that no longer exists. (Deleting a state — state remove — is in the CDK README but is not in CLI 1.0.96; it lands in the next release.)

• Three ways to get a value in, and they are not interchangeable.

  • secret("ENV_VAR") — read from your environment at deploy time, excluded from the content hash and from state. Export the env var before deploying; a missing one fails the deploy with an unresolved ${ENV_VAR} placeholder.
  • env("ENV_VAR") — read from your environment at load time, and its value enters the spec and therefore the content hash, so changing it shows as drift. Use it for non-secret config you want tracked.
  • workspaceEnv("NAME") — a pointer at a workspace env-var catalog entry. Nothing is read locally and nothing can fail; the value stays server-side and is re-read on every use, so rotating it in the workspace reaches the resource with no redeploy. Manage the catalog with cargo-ai workspaceManagement envVar (see ../cargo-workspace-management/SKILL.md).

  secret() and workspaceEnv() are accepted at secret-typed schema positions only — cargo-ai project types prints the union at exactly those positions. A resource's own env block takes env() or secret() and rejects a pointer, because a worker, app, agent or script already inherits the whole workspace catalog; a pointer there could only restate a variable it can read anyway.

• A rotated secret() needs more than a plain deploy to land. Keeping the value out of the content hash is what stops rotation reading as drift — and it is also why deploy won't push the new value: nothing in the hash changed, so the resource isn't re-applied. Roll it with deploy --refresh, or any other edit to that resource. workspaceEnv() has no such step; that is most of its appeal.

• Wire by handle, never by .uuid. Pass a define* handle directly (dataset: hubspot, tools: [enrich]), or xxRef("uuid") for a resource you didn't define in code (connectorRef, modelRef, folderRef, toolRef, agentRef, …). Where a reference needs per-call options, wrap it as { ref, …options } (e.g. models: [{ ref: contacts, readOnly: true }]).

• Run cargo-ai project types after workspace integrations change — it regenerates .cargo-ai/ so defineConnector/defineModel config (and integrations.* in workflow bodies) type-check against the real schemas. Typing is a bonus, never a gate: deploy works without it.

• Any subdirectory of the repo is fine (CLI ≥ 1.0.83). Commands walk up to the package root where @cargo-ai/cdk is declared, then back down to the resource directory (infra/ in a scaffolded repo), so .cargo-ai/ and cargo.state.json land in the right place from anywhere inside the project. --dir <path> still overrides it. This is why resources live in infra/ and not at the root: the loader imports every .ts under the directory it is given, and a repo root also holds scripts/ — whose files run on import. Pointing a command at the root would execute them.

• --yes in CI. deploy and destroy prompt for confirmation; non-interactive runs must pass --yes.

• A definePlay/defineTool graph with paid nodes gets a sample run before it goes wide. Deploying is not running, but the first thing that runs a deployed play is usually a batch over the whole segment — and a scheduled play re-bills every node on every run. Before enrolling everything (or enabling a schedule), run the deployed workflow on 10–20 records — cargo-ai orchestration batch create --data '{"kind":"filter","modelUuid":"…","filter":…,"limit":15}', or batch create --file ./plays/x.ts to test-run the module without deploying — then ask the user to approve the full enrollment with the record count and credit estimate. Read the provider's playbook (../cargo-gtm/provider-playbooks/<slug>.md, esp. its Recurring use section) and the gate in ../cargo-gtm/references/cost-discipline.md.

• A defineAlert whose actions call paid nodes re-bills on every breach. An alert's actions fire as real runs, so a badly-sized threshold on a tight schedule can breach — and bill — every tick. Size the threshold with cargo-ai observability alert preview before deploying, prefer cheap notification actions (an agent that posts, a connector notification) over anything that fans out, and apply the same cost gate above when an action calls a credits-based provider. Scope/threshold and firing semantics: ../cargo-observability/SKILL.md.

• defineMailbox bills monthly, and defineDomain rewrites a DNS zone. A mailbox is 100–160 credits per month for as long as it exists (cargo-ai mailboxManagement pricing get for live figures), so a + create mailbox:… line in the plan is a recurring charge the user approves, not a one-off. Its domain, username and type are create-only — changing any of them is destroy + recreate, i.e. a brand-new inbox back at the bottom of a 45-day warm-up ramp. The deploy polls refreshStatus for up to 5 minutes waiting for active. On defineDomain, dnsRecords is the whole zone, not a patch: declaring it replaces every live record (including the ones the registrar wrote at purchase), and omitting it leaves the zone untouched. redirectUrl, dmarcEmail and dmarcPolicy are additive and are the supported way to configure a zone without replacing it, so reach for dnsRecords only when you mean to own every record. Use adopt: true for a domain or mailbox bought in the UI. Ramp, suppression and sending: ../cargo-mailbox-management/SKILL.md.

• Route CDK-managed resources into a clearly-labelled folder. Set folder: on each builder so everything CDK owns lands in a dedicated folder whose name signals "owned by code — don't hand-edit" to anyone in the UI (manual UI edits read back as drift on the next plan). Folders are per-kind, so give each kind its own but share one short, recognizable prefix — recommended: 🔒 CDK (e.g. 🔒 CDK Models, 🔒 CDK Agents). Keep names short (long labels truncate in the folder tree); the lock emoji is the "don't touch" cue. See guides/authoring-resources.md.

Help

• cargo-ai project --help and cargo-ai project <subcommand> --help for the live flag surface.
• When a documented command/flag/response doesn't match what you observe, file a report: cargo-ai workspaceManagement report create (see ../cargo-workspace-management/SKILL.md).