cargo

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Router and overview for the Cargo CLI agent skills. Explains the eleven skills (one outcome skill cargo-gtm + ten capability skills), the UUID flow between them, async polling, end-to-end use cases (enrich one record, enrich and sync to CRM, AI lead scoring, custom workflow, error monitoring, fresh-workspace bootstrap, segment export, GTM context authoring), and common gotchas (`conjonction` spelling, run vs batch, model-uuid vs segment-uuid). Load first whenever working with the Cargo CLI, when unsure which sub-skill applies, when stitching multiple sub-skills together, when bootstrapping a workspace, or when the user asks about Cargo skills in general.

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NPX Install

npx skill4agent add getcargohq/cargo-skills cargo
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Cargo CLI — Skills Overview

This repository contains 11 skills at the repo root: one outcome skill (
cargo-gtm
) and ten capability skills.
  • cargo-gtm
    — application library. The front door for any GTM task ("build a TAM list", "find 5 fintech CTOs", "monitor job changes"). Routes via internal recipes (
    ../cargo-gtm/recipes/*.md
    ) and provider playbooks (
    ../cargo-gtm/provider-playbooks/*.md
    ).
  • Capability skills — standard library. One per CLI domain (orchestration, storage, connection, AI, content, context, analytics, billing, hosting, workspace management). Loaded by
    cargo-gtm
    , or directly when you need a specific CLI domain.
cargo-gtm
delegates to capability skills; capability skills never reference
cargo-gtm
(one-way dependency).
Glossary: See
references/glossary.md
for term-by-term definitions (UUIDs, slugs,
conjonction
, run/batch/play/tool, signal/persona/ICP, etc.).

Installation

bash
npm install -g @cargo-ai/cli
cargo-ai login --oauth                                   # browser sign-in (recommended)
# or: cargo-ai login --token <your-api-token>            # use an existing workspace-scoped API token
# Optional: pin a default workspace at login
cargo-ai login --oauth --workspace-uuid <uuid>
# Verify
cargo-ai whoami
Without a global install, prefix every command with
npx @cargo-ai/cli
instead of
cargo-ai
.
All commands output JSON to stdout. Failed commands exit non-zero and return
{"errorMessage": "..."}
. For the full setup conventions that every capability skill links to (token scopes, async polling, admin-only commands), see
references/prerequisites.md
.

Every Cargo session has three jobs

Automated by the Cargo installer. Jobs 1 and 3 (refresh + session register/finalize) run on their own when the
SessionStart
/
SessionEnd
hooks scaffolded by
curl -fsSL https://api.getcargo.io/install.sh | sh
are present. Do them by hand only when those hooks aren't installed. Job 2 (reporting) is always your responsibility — it can't be automated.

1. At session start — refresh and register

Before any other Cargo command, refresh the CLI and skills, then register the session in workspace management:
bash
# Refresh — idempotent, ~10s
npm install -g @cargo-ai/cli@latest
npx -y skills add getcargohq/cargo-skills

# Register the session (placeholders OK — overwritten at session end)
cargo-ai workspaceManagement session upsert \
  --session-id <claude-session-id> \
  --title "Claude Code session <claude-session-id>" \
  --summary "Session in progress."
Skip the refresh only if the user explicitly pinned a version. Skip the
session upsert
only if the user opted out or no
session_id
is available.

2. Mid-session — re-refresh, or escalate when stuck

Re-refresh the CLI and skills mid-session when:
  • A documented CLI flag or response shape doesn't match what you observe (a fix may have shipped since session start).
  • The user explicitly asks ("bump cargo", "make sure I'm on latest").
Send a workspace management report when the CLI is failing in a way the skill references and
--help
cannot resolve, the user or agent is repeatedly retrying the same command without progress, the syntax for a flag / JSON payload is unclear, or a needed capability seems missing:
bash
cargo-ai workspaceManagement report create \
  --title "<one-line summary of the problem>" \
  --description "<exact command(s) tried, errorMessage, expected vs actual, UUIDs involved>"
Trigger conditions (any one is enough):
  • A command failed ≥ 2 times in a row on the same task and the cause is not obvious.
  • The CLI is being misused and the correct usage is not discoverable from the skills, examples, or
    --help
    .
  • A documented behavior contradicts what you observe.
  • A feature appears to be missing entirely.
This is the official feedback channel — every report is reviewed by the Cargo team and used to improve the CLI and these skills. Do not give up silently — file a report. See
../cargo-workspace-management/SKILL.md
(Reports section) and
../cargo-workspace-management/references/examples/reports.md
for templates.

3. At session end — finalize the session row

Produce a short title (5–8 words) and a 1–2 sentence summary of what the session actually worked on, then overwrite the placeholder row and stamp
finished_at
:
bash
cargo-ai workspaceManagement session upsert \
  --session-id <claude-session-id> \
  --title "<5-8 word title>" \
  --summary "<1-2 sentence summary of what was accomplished or attempted>" \
  --finished
--title
and
--summary
are required (NOT NULL).
--finished
stamps
finished_at = now
; pass
--finished-at <iso>
for an explicit timestamp.

Skills at a glance

Outcome skill

Load when the user states a real-world goal.
SkillLoad when you need to…
cargo-gtm
(recap)
Any GTM task — sourcing, enrichment, verification, scoring, sequencing, CRM sync, signal monitoring (job changes, funding, tech-stack/hiring intent). Routes via recipes (
recipes/
), guides (
guides/
), and provider playbooks (
provider-playbooks/
).

Capability skills

Load for a specific CLI domain. The first link in each row jumps to the actual SKILL.md; the parenthetical jumps to the recap on this page.
SkillLoad when you need to…
cargo-orchestration
(recap)
Execute actions, run workflows, trigger batches, chat with agents, query orchestration with SQL (ClickHouse)
cargo-analytics
(recap)
Download run results, export segment data, monitor error rates and metrics
cargo-billing
(recap)
Check credit usage, view subscription details, track costs per workflow or connector
cargo-storage
(recap)
Inspect or modify data models, columns, datasets, and relationships; query workspace storage with SQL
cargo-connection
(recap)
Manage connector authentication, discover available integrations and their actions
cargo-ai
(recap)
Create and configure agents, configure releases, attach knowledge for RAG, manage MCP servers and memories
cargo-content
(recap)
Upload and organize knowledge files, build native/connector-backed knowledge libraries for RAG (the
content
domain)
cargo-context
(recap)
Browse/read/write/edit the workspace's git-backed GTM context repo, run commands in its runtime sandbox, inspect the knowledge graph
cargo-hosting
(recap)
Scaffold, deploy, and promote hosted apps (Vite SPAs on
*.cargo.app
) and edge workers (serverless HTTP handlers), and manage their deployments
cargo-workspace-management
(recap)
Invite users, create API tokens, organize folders, manage roles, report CLI issues to management
Agent knowledge for RAG: files + libraries live in the
content
domain →
cargo-content
; how they attach to an agent →
cargo-ai
. (Files/libraries moved out of the old
ai file …
path in CLI ≥ 1.0.19.)

CLI domains without a dedicated skill yet

The CLI exposes several domains that no capability skill wraps yet. Reach for them directly (
cargo-ai <domain> --help
) when a task needs them, and file a
workspaceManagement report
if the surface is unclear:
CLI domainCovers
segmentation
Segments and changes (
segment list/get/create/fetch/download
,
change
). Some of this is already used from
cargo-orchestration
/
cargo-analytics
.
expression
Recipes and expression evaluation (
eval
,
recipe
) — generate/evaluate the template expressions used in node graphs.
system-of-record
System-of-record, client, and log operations.
revenue-organization
Allocations, capacities, members, territories (revenue/territory planning).
user-management
Current-user operations with no workspace context.

How the skills relate

            ┌─────────────────────────────────────┐
            │              cargo-gtm              │
            │   Outcome / front door for GTM      │
            │   Recipes, guides, provider-playbks │
            └─────────────────┬───────────────────┘
                              │ delegates to ↓ (one-way)
       ┌──────────────────────┴──────────────────────┐
       │                                             │
┌──────────────────────────────────────────────────────────────┐
│              cargo-workspace-management                      │
│         Authentication, users, tokens, folders               │
└──────────────────────────────────────────────────────────────┘

  ┌─────────────────┐   ┌────────────────────┐   ┌─────────────────┐
  │  cargo-storage  │   │  cargo-connection  │   │    cargo-ai     │
  │ Models, columns,│   │ Connectors,        │   │ Agents, docs,   │
  │ datasets        │   │ integration actions│   │ MCP, memory     │
  └────────┬────────┘   └─────────┬──────────┘   └────────┬────────┘
                                              (cargo-content feeds
                                               files/libraries to agents)
           │                      │  (UUIDs flow down)    │
           └──────────────────────┼───────────────────────┘
             ┌───────────────────────────────────────┐
             │          cargo-orchestration          │
             │   Runs, batches, plays, tools, SoR    │
             └───────────────┬───────────────────────┘
              ┌──────────────┴──────────────┐
              ▼                             ▼
 ┌────────────────────────┐  ┌───────────────────────────┐
 │    cargo-analytics     │  │       cargo-billing       │
 │  Results, metrics,     │  │    Credit usage, costs    │
 │  exports               │  │                           │
 └────────────────────────┘  └───────────────────────────┘

             ┌───────────────────────────────────────┐
             │             cargo-context             │
             │  Git-backed GTM markdown knowledge:   │
             │  personas, plays, proof, signals…     │
             └───────────────────────────────────────┘
           (orthogonal: not part of the workflow flow)
Dependency rules in practice:
  • cargo-gtm
    delegates to capability skills via relative paths (
    ../cargo-orchestration/...
    ). Capability skills never reference
    cargo-gtm
    .
  • cargo-workspace-management
    provides auth context for every skill — set it up first.
  • cargo-storage
    ,
    cargo-connection
    , and
    cargo-ai
    are peer skills that supply UUIDs to
    cargo-orchestration
    . They don't depend on each other.
  • cargo-content
    owns workspace files and libraries (the
    content
    domain). It produces file/library UUIDs that
    cargo-ai
    consumes as agent release
    resources
    (RAG). Uploaded content files also surface read-only under
    .files/
    in the
    cargo-context
    runtime sandbox.
  • cargo-context
    is orthogonal to the workflow-execution flow. It touches the git-backed GTM knowledge base (markdown/MDX), not storage or workflow runs. Use it for capturing/editing the workspace's prose context — personas, plays, proof, objections, signals — and for inspecting the typed knowledge graph.
  • For SQL queries against storage, use
    cargo-ai storage query execute "<sql>"
    (tables as
    <datasetSlug>.<modelSlug>
    ). Load
    cargo-storage
    to discover dataset and model slugs, and to fetch the DDL when you need column types or the SQL dialect.
  • For SQL queries against orchestration runtime tables (
    runs
    ,
    batches
    ,
    spans
    ,
    records
    ) — error rates, per-node failures, time-series — use
    cargo-ai orchestration query execute "<sql>"
    . Workspace scoping is automatic; tables are referenced without a schema prefix.
  • Before building a workflow node graph, load
    cargo-connection
    to get
    connectorUuid
    and
    actionSlug
    .
  • Before executing a workflow that uses an agent node, load
    cargo-ai
    to get
    agentUuid
    .
  • After runs complete, load
    cargo-analytics
    to download results or measure performance. For action output retrieval, prefer
    cargo-ai orchestration run download-outputs
    over
    run download
    — the former returns a signed-URL CSV/JSON of just the output node's data.
  • Load
    cargo-billing
    to understand credit consumption for any of the above.

Skill details

cargo-gtm

The outcome skill — front door for any GTM task. Bundles routing (
SKILL.md
), phase guides (
guides/
), scenario recipes (
recipes/
), per-provider playbooks (
provider-playbooks/
), references (
references/
), and a sub-agent (
agents/
).
Recipes shipped:
RecipeUse when…
recipes/prospecting.md
End-to-end find → enrich → verify → sync (P1/P2/P3 variants).
recipes/build-tam.md
Build a Total Addressable Market list at scale (100–10,000 companies).
recipes/linkedin-url-lookup.md
Resolve LinkedIn URL from name + company with strict validation.
recipes/portfolio-prospecting.md
Investor / accelerator → portfolio companies → contacts.
recipes/job-change-monitoring.md
waterfall.detectJobChange
(cargo-unique) on a contact segment.
recipes/funding-watch.md
Track companies that recently raised funding.
recipes/tech-intent.md
Find companies by tech-stack or hiring-intent signals.
recipes/icp-discovery.md
Diff Closed-Won vs Closed-Lost segments, surface ICP signals.
recipes/outreach-activation.md
Turn a signal segment into send-ready outreach (enrich → verify → personalize → sequencer handoff).
recipes/re-engagement.md
Wake up stale contacts only when a fresh signal fires (job change, funding, tech intent).
recipes/lost-deal-revival.md
Revive Closed-Lost CRM deals by branching on
lost_reason
(champion left, budget, timing).
recipes/account-expansion.md
Multi-thread customer accounts — net-new buyers, deduped against the Contacts model.
Priority provider stack (recipes lead with these): salesNavigator (sourcing), cargo native (firmographics + signals), waterfall (multi-source enrichment + email verify + job-change), FullEnrich (premium contact lookup), theirStack (tech-stack + hiring intent), peopleDataLabs (heavyweight backfill).
Critical rules:
  • All recipes use credits-based actions (
    cargo-ai connection integration list
    → 141 credits-based actions across 120 integrations).
  • Action shape:
    {"kind":"connector","integrationSlug":"<slug>","actionSlug":"<slug>","config":{}}
    no
    connectorUuid
    in
    config
    .
  • Output retrieval:
    cargo-ai orchestration run download-outputs --output-node-slug <slug>
    (NOT
    run download
    ).
  • peopleDataLabs filter shape:
    searchX
    uses cargo's
    {conjonction, groups, conditions}
    shape;
    queryX
    takes a PDL SQL string — never Elasticsearch.
References:
../cargo-gtm/SKILL.md

cargo-orchestration

The execution hub. Execute actions, run workflows, chat with AI agents, query orchestration runtime tables (
runs
/
batches
/
spans
/
records
) with SQL, and fetch segment records.
Critical rules:
  • See the decision flowchart at the top of
    ../cargo-orchestration/SKILL.md
    for when to use
    action execute
    vs
    run create
    vs
    batch create
    .
  • Prefer built-in actions + expressions when building a node graph. Avoid
    python
    ,
    script
    (JS), and raw HTTP nodes unless necessary: use
    variables
    for transforms, the native
    agent
    node for LLM calls, the integration's dedicated connector action for APIs, and
    branch
    /
    filter
    /
    switch
    for routing. See
    ../cargo-orchestration/references/node-selection.md
    .
  • Filter JSON uses
    conjonction
    (not
    conjunction
    ) — breaks silently if misspelled.
  • Query orchestration runtime tables (ClickHouse) with
    cargo-ai orchestration query execute "<sql>"
    against
    runs
    ,
    batches
    ,
    spans
    ,
    records
    (no schema prefix; workspace scoping is automatic).
  • For SQL against workspace storage (Companies, Contacts, …), use
    cargo-ai storage query execute "<sql>"
    — documented in
    cargo-storage
    .
  • All operations are async — poll or pass
    --wait-until-finished
    . See Async polling.
References:
../cargo-orchestration/SKILL.md

cargo-analytics

Measurement and export. Download run results, export segment data, and monitor error rates and success metrics.
Critical rules:
  • segment download
    requires
    --model-uuid
    , not
    --segment-uuid
    .
  • For batch result download, get the
    output-node-slug
    from
    release get <release-uuid>
    nodes[].slug
    .
  • For billing and credit usage, use
    cargo-billing
    instead.
References:
../cargo-analytics/SKILL.md

cargo-billing

Cost and credit management. Track credit consumption per workflow, connector, or agent; check subscription status; view invoices.
Critical rules:
  • Requires a token with admin access.
  • Invoice amounts are in cents — divide by 100 for dollars.
  • subscriptionAvailableCreditsCount - subscriptionCreditsUsedCount
    from
    subscription get
    = remaining credits.
References:
../cargo-billing/SKILL.md

cargo-storage

Data schema management and SQL queries. Inspect models, create or update columns, navigate datasets, understand workspace data structure, and run SQL against workspace storage.
Critical rules:
  • Query via
    cargo-ai storage query execute "<sql>"
    (or
    storage query download --query "<sql>"
    for full exports) using
    <datasetSlug>.<modelSlug>
    table names (e.g.
    default.companies
    ).
    model get-ddl
    is optional — useful for column types and SQL dialect.
  • For SQL against orchestration runtime tables (
    runs
    /
    batches
    /
    spans
    /
    records
    ), use
    cargo-ai orchestration query execute "<sql>"
    — documented in
    cargo-orchestration
    .
  • For advanced record queries (filtering, sorting, pagination), use
    segmentation segment fetch
    from
    cargo-orchestration
    .
References:
../cargo-storage/SKILL.md

cargo-connection

Connector and integration management. Authenticate external services, discover supported actions, get the
connectorUuid
and
actionSlug
values needed for workflow node graphs.
Key concepts:
  • Integration = external service type (HubSpot, Clearbit, Salesforce, …)
  • Connector = authenticated instance of an integration (referenced by
    connectorUuid
    in nodes)
References:
../cargo-connection/SKILL.md

cargo-ai

Agent resource management. Create and configure agents, configure releases, attach knowledge for retrieval-augmented generation (RAG), connect MCP servers, manage memories.
Critical rules:
  • Knowledge for RAG attaches to an agent via the release's
    resources
    : files + libraries come from
    cargo-content
    . Wire them in with
    release update-draft --resources …
    then
    release deploy-draft
    .
  • CLI ≥ 1.0.19: files and libraries moved out of the
    ai
    domain into the top-level
    content
    domain (now the
    cargo-content
    skill). The old
    cargo-ai ai file …
    commands no longer exist.
For using agents (sending messages, multi-turn chat, polling), use
cargo-orchestration
.
See
../cargo-ai/SKILL.md
for model and temperature guidance by use case.
References:
../cargo-ai/SKILL.md

cargo-content

Workspace knowledge files & libraries. Upload, list, rename, move, and remove files (PDFs, CSVs, text); create and sync libraries
native
(workspace-managed) or
connector
-backed (synced from an external source via an unstructured-data extractor). These are the RAG knowledge resources agents reference.
Critical rules:
  • New top-level
    content
    domain in CLI ≥ 1.0.19 —
    cargo-ai content file …
    /
    cargo-ai content library …
    . The old
    cargo-ai ai file …
    path is gone (
    unknown command
    → you're on the old path; bump the CLI).
  • A file or library is inert until attached to an agent's deployed release
    resources
    — that wiring lives in
    cargo-ai
    .
  • Uploaded content files are also readable (read-only) under
    .files/
    in the
    cargo-context
    runtime sandbox.
  • For batch-run input files (CSVs that drive a batch), use
    cargo-ai workspaceManagement file upload
    (a different surface) — see
    cargo-workspace-management
    .
References:
../cargo-content/SKILL.md

cargo-context

GTM context repository. Browse, read, write, and edit the workspace's git-backed knowledge base of typed markdown/MDX files — personas, plays, proof, objections, signals, ICPs, etc. — via the runtime sandbox. Inspect cross-references with the knowledge graph.
Key concepts:
  • Context repository = the GitHub repo backing the workspace's context. Canonical example:
    getcargohq/cargo-workspaces
    . Files use
    kebab-case.md
    names, YAML frontmatter with required
    title
    +
    description
    , and
    domain/slug
    cross-refs (no
    .md
    ).
  • Runtime sandbox = a checked-out, executable copy of the context repo.
    runtime write
    and
    runtime edit
    push to the default branch;
    runtime execute
    does not push.
  • Knowledge graph = the typed graph over every md/mdx file, with frontmatter and outbound cross-refs per node. Built via
    cargo-ai context graph get
    .
Critical rules:
  • runtime write
    /
    runtime edit
    commit and push.
    runtime execute
    is ephemeral — use it for
    grep
    /
    ls
    /inspection, never for persistent changes.
  • runtime edit --old-string
    must match the file content exactly once. Read first, copy whitespace verbatim.
  • Set
    title
    +
    description
    frontmatter on every
    .md
    /
    .mdx
    file — a strong convention, not enforced: missing/malformed frontmatter is still committed, it just indexes poorly (graph falls back to filename + first paragraph, and reads
    summary
    , not
    description
    ).
  • Graph edges form only from frontmatter
    references:
    , markdown links, or wikilinks — a bare path in prose creates no edge. Cite source files in
    references:
    .
  • For domains, conventions, and per-domain templates, see
    ../cargo-context/references/conventions.md
    .
Lifecycle:
  • For bootstrapping a fresh workspace's context from a domain (ICP, personas, proof, signals — idempotent, skips already-seeded domains), see
    ../cargo-context/references/examples/bootstrap-from-domain.md
    .
  • For the full bootstrap + ongoing call-driven refresh playbook (Phase 1 + Phase 2 + cadence), see
    ../cargo-context/references/examples/lifecycle.md
    .
References:
../cargo-context/SKILL.md

cargo-hosting

Cargo Hosting. Scaffold, deploy, and manage hosted apps (Vite SPAs on
https://<slug>.cargo.app
, built on
@cargo-ai/app-sdk
) and workers (serverless edge
fetch(request, env)
handlers on
@cargo-ai/worker-sdk
), plus the deployments that ship and promote them.
Lifecycle:
init
(local scaffold) →
create
(slot + globally-unique slug) →
deployment create
(build+upload) →
deployment promote
(go live).
Critical rules:
  • --slug
    is the live subdomain — globally unique within the hosting domain.
  • Deploying ≠ going live.
    deployment create
    builds; the URL only moves on
    deployment promote
    .
    deployment get-promoted
    shows what's live.
  • --source
    is the package root, not
    dist/
    — the build (
    npm ci && vite build
    for apps, bundling for workers) runs server-side.
  • Builds are async — poll
    deployment get
    until terminal before promoting.
  • --app-uuid
    /
    --worker-uuid
    are mutually exclusive on deployment commands;
    remove
    cascades to deployments.
  • Folders come from
    cargo-workspace-management
    ;
    --folder-uuid null
    moves to root.
References:
../cargo-hosting/SKILL.md

cargo-workspace-management

Workspace administration. Invite users, create and rotate API tokens, organize plays/tools/agents into folders, manage roles, and submit reports to workspace management when the CLI fails or is being misused.
Critical rules:
  • Most commands require a token with admin access.
  • workspaceManagement token create
    requires
    --name
    (the legacy
    --from-user
    flag was removed). Pick a name that makes the token's purpose obvious in
    token list
    later.
  • Token values are only shown once at creation — store immediately in a secrets manager (GitHub Secrets, AWS Secrets Manager, etc.).
  • Always send a
    workspaceManagement report create
    when the CLI errors, is being used incorrectly, or you (user or agent) are struggling to make progress on a CLI task — see the section at the top of this file and
    ../cargo-workspace-management/references/examples/reports.md
    .
References:
../cargo-workspace-management/SKILL.md

Async polling

All operations are asynchronous. Pass
--wait-until-finished
to block, or poll:
Result typePoll commandIntervalTerminal when
Run
cargo-ai orchestration run get <uuid>
2s
status
is
success
,
error
, or
cancelled
Batch
cargo-ai orchestration batch get <uuid>
5s
status
is
success
,
error
, or
cancelled
Agent message
cargo-ai ai message get <uuid>
2s
status
is
success
or
error
action execute
returns a run;
action execute-batch
returns a batch — same polling applies.
See
../cargo-orchestration/references/polling.md
for retry strategies, error handling, and large-batch guidance.

UUID flow between skills

See
references/uuid-flow.md
— producer/consumer table for every UUID and slug that crosses skill boundaries (
workflowUuid
,
modelUuid
,
connectorUuid
,
actionSlug
, …), the standard discovery sequence to run before any workflow, and the
app.getcargo.io
URL patterns for resolving UUIDs in the UI.

End-to-end use cases

See
references/use-cases.md
— 8 worked recipes (single-record enrich, batch + CRM sync, AI lead scoring, custom workflow from scratch, error monitoring, fresh-workspace bootstrap, segment export with filter+sort, GTM context audit) showing which skills to load and the command sequence for each.

Common gotchas

See
references/gotchas.md
— silent-failure footguns and frequently confused command pairs (
conjonction
spelling,
run create
vs
batch create
,
--model-uuid
vs
--segment-uuid
, storage query table naming, token-shown-once, invoice cents, third-party connector rate limits,
context runtime execute
vs
write
/
edit
, …).