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cargo-skills

cargo-skills

github.com/getcargohqMarketing & growth2162 installsUpdated 3d ago
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About cargo-skills

Seven CLI skills for Cargo AI-native revenue infrastructure cover workflow execution, analytics, billing, storage, connections, agents, and workspace administration. Their dependency and UUID guidance helps select and combine commands by task.

Key features

  1. 01Covers seven Cargo CLI skill areas
  2. 02Execute actions, workflows, and batches
  3. 03Manage data models and connectors
  4. 04Create agents and connect MCP servers
  5. 05Administer users, tokens, and workspaces

Use cases

  1. 01Run Cargo workflows and batch tasks
  2. 02Export run results and monitor metrics
  3. 03Configure connectors or agent resources
  4. 04Manage workspace users, roles, and tokens

MCP support

The cargo-ai skill can create and manage MCP servers through the CLI.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/getcargohq/cargo-skills --skill cargo-skills

After installing, type/cargo-skillsin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

GLOSSARY.md
README.md
cargo-ai/references/
response-shapes.md
troubleshooting.md
cargo-ai/references/examples/
agents.md
files.md
mcp-servers.md
templates.md
cargo-analytics/references/
response-shapes.md
troubleshooting.md
cargo-analytics/references/examples/
exports.md
run-analytics.md
cargo-billing/references/
response-shapes.md
troubleshooting.md
cargo-billing/references/examples/
usage-metrics.md
cargo-connection/references/
response-shapes.md
troubleshooting.md
cargo-connection/references/examples/
connectors.md
integrations.md
cargo-orchestration/references/
actions.md
agents.md
filter-syntax.md
nodes.md
plays.md
polling.md
queries.md
response-shapes.md
segments.md
templates.md
tools.md

Details

From the project README
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Cargo CLI — Skills Overview

This repository contains seven skills for the Cargo AI-native revenue infrastructure. Each skill covers a distinct domain. This file tells you which skill to load for any given task and how to combine them.

Installation

npm install -g @cargo-ai/cli
cargo-ai login --token <your-api-token>
# Optional: target a specific workspace
cargo-ai login --token <your-api-token> --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": "..."}.

When the CLI fails or you're stuck — send a workspace management report

Whenever 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 — escalate by submitting a report to workspace management:

cargo-ai workspace 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.


Skills at a glance

SkillLoad when you need to…
cargo-orchestrationExecute actions, run workflows, trigger batches, chat with agents, query your data warehouse
cargo-analyticsDownload run results, export segment data, monitor error rates and metrics
cargo-billingCheck credit usage, view subscription details, track costs per workflow or connector
cargo-storageInspect or modify data models, columns, datasets, and relationships
cargo-connectionManage connector authentication, discover available integrations and their actions
cargo-aiCreate and configure agents, upload files for RAG, manage MCP servers
cargo-workspace-managementInvite users, create API tokens, organize folders, manage roles, report CLI issues to management

How the skills relate

┌──────────────────────────────────────────────────────────────┐
│                  cargo-workspace-management                  │
│             Authentication, users, tokens, folders           │
└──────────────────────────────────────────────────────────────┘

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

Dependency rules in practice:

  • 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.
  • Before querying via system-of-record, load cargo-storage to get the DDL (exact table name).
  • 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.
  • Load cargo-billing to understand credit consumption for any of the above.

Skill details

cargo-orchestration

The execution hub. Execute actions, run workflows, chat with AI agents, query your data warehouse, and fetch segment records.

Key commands:

# Single actions (no workflow needed)
cargo-ai orchestration action execute --action '{"kind":"tool","toolUuid":"<uuid>","config":{}}' --data '{...}'
cargo-ai orchestration action execute-batch --action '{"kind":"connector","integrationSlug":"...","actionSlug":"...","config":{}}' --records '[{...},{...}]'

# Workflows (chain multiple actions)
cargo-ai orchestration run create --workflow-uuid <uuid> --data '{...}'
cargo-ai orchestration run create --data '{...}' --nodes '[...]'
cargo-ai orchestration batch create --workflow-uuid <uuid> --data '{"kind":"segment","segmentUuid":"..."}'

# AI agents
cargo-ai ai message create --chat-uuid <uuid> --parts '[{"type":"text","text":"..."}]'

# Data
cargo-ai system-of-record client query "SELECT * FROM <table> LIMIT 10"
cargo-ai segmentation segment fetch --model-uuid <uuid> --filter '{"conjonction":"and","groups":[]}'

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.
  • Filter JSON uses conjonction (not conjunction) — breaks silently if misspelled.
  • Always get DDL before querying the system-of-record: cargo-ai storage model get-ddl <model-uuid>.
  • All operations are async — poll or pass --wait-until-finished. See Async polling.

References: cargo-orchestration/SKILL.md


cargo-analytics

Measurement and export. Use to download run results, export segment data, and monitor error rates and success metrics.

Key commands:

cargo-ai orchestration run get-metrics --workflow-uuid <uuid>
cargo-ai orchestration run download --workflow-uuid <uuid> --is-finished
cargo-ai orchestration run count --workflow-uuid <uuid> --statuses error
cargo-ai segmentation segment download --model-uuid <uuid> --filter '{"conjonction":"and","groups":[]}'

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. Use to track credit consumption per workflow, connector, or agent, check subscription status, and view invoices.

Key commands:

cargo-ai billing usage get-metrics --from <YYYY-MM-DD> --to <YYYY-MM-DD>
cargo-ai billing usage get-metrics --from <date> --to <date> --group-by workflow_uuid
cargo-ai billing subscription get
cargo-ai billing subscription get-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. Use to inspect models, create or update columns, navigate datasets, and understand your workspace's data structure.

Key commands:

cargo-ai storage model list
cargo-ai storage model get-ddl <model-uuid>   # always run before SoR queries
cargo-ai storage column list --model-uuid <uuid>
cargo-ai storage relationship set --from-model-uuid <uuid> --to-model-uuid <uuid>

Critical rules:

  • Always run model get-ddl before querying via system-of-record — it contains the exact table name (e.g. datasets_default.models_companies).
  • 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. Use to authenticate external services, discover what actions they support, and get the connectorUuid and actionSlug values needed for workflow node graphs.

Key commands:

cargo-ai connection connector list
cargo-ai connection integration list
cargo-ai connection integration get <slug>          # third-party actions (HubSpot, Salesforce, etc.)
cargo-ai connection native-integration get          # built-in Cargo actions only (NOT third-party)

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. Use to create and configure agents, upload documents for retrieval-augmented generation (RAG), and connect MCP servers.

For using agents (sending messages, multi-turn chat, polling), use cargo-orchestration.

Key commands:

cargo-ai ai agent list
cargo-ai ai agent create --name "Lead Researcher" --language-model-slug gpt-4o --temperature 0.3
cargo-ai ai file upload --file-path ./knowledge-base.pdf
cargo-ai ai mcp-server create --name "Internal Tools" --url "https://..."
cargo-ai ai memory list --agent-uuid <uuid>

See cargo-ai/SKILL.md for model and temperature guidance by use case.

References: cargo-ai/SKILL.md


cargo-workspace-management

Workspace administration. Use to 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.

Key commands:

cargo-ai whoami
cargo-ai workspace user create --user-email [email protected] --role-slug <slug>
cargo-ai workspace token create --name "CI/CD pipeline"
cargo-ai workspace folder create --name "Q1 Campaigns" --emoji-slug "rocket" --kind "play"
cargo-ai workspace report create --title "<summary>" --description "<details>"

Critical rules:

  • Most commands require a token with admin access.
  • workspace 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 workspace 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
Runcargo-ai orchestration run get <uuid>2sstatus is success, error, or cancelled
Batchcargo-ai orchestration batch get <uuid>5sstatus is success, error, or cancelled
Agent messagecargo-ai ai message get <uuid>2sstatus 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

Most cargo-orchestration operations require UUIDs from other skills. This table maps which skill produces each UUID and which commands consume it.

UUIDProduced byConsumed by
workflowUuidorchestration play list / tool listrun create, batch create, run get-metrics, run download
modelUuidstorage model listsegment fetch, segment download, system-of-record query (via DDL)
segmentUuidsegmentation segment listbatch create --data '{"kind":"segment",...}'
agentUuidai agent listai chat create, node graph (kind: "agent")
connectorUuidconnection connector listNode graph (kind: "connector"), billing usage --connector-uuid
actionSlugconnection integration get <slug> (third-party) or connection native-integration get (built-in)Node graph (kind: "connector" or kind: "native")
releaseUuidorchestration batch get → .releaseUuidorchestration release get, batch download
batchUuidorchestration batch createbatch get, batch download, run get-metrics --batch-uuid
folderUuidworkspace folder listplay list --folder-uuid, tool list --folder-uuid
roleSlugworkspace role listworkspace user create --role-slug

Standard discovery sequence before running a workflow:

# 1. Confirm identity
cargo-ai whoami

# 2. Find the tool or play to run
cargo-ai orchestration tool list
cargo-ai orchestration play list

# 3. Find the model and get its DDL (if querying via SoR)
cargo-ai storage model list
cargo-ai storage model get-ddl <model-uuid>

# 4. Find connectors needed by the workflow nodes
cargo-ai connection connector list

# 5. Find agents used in workflow nodes
cargo-ai ai agent list

# 6. Find the segment to process (for plays / batch with segment data)
cargo-ai segmentation segment list
Retrieve in the UI

Each resource has a dedicated page in the Cargo app. Use these URL patterns to cross-reference a UUID returned by the CLI with the UI, or to extract a UUID from a URL the user pastes.

ResourceURL pattern
Playapp.getcargo.io/workspaces/<WORKSPACE_UUID>/plays/<PLAY_UUID>
Toolapp.getcargo.io/workspaces/<WORKSPACE_UUID>/tools/<TOOL_UUID>
Agentapp.getcargo.io/workspaces/<WORKSPACE_UUID>/agents/<AGENT_UUID>
Modelapp.getcargo.io/workspaces/<WORKSPACE_UUID>/models/<MODEL_UUID>

The workspace UUID is returned by cargo-ai whoami under workspace.uuid.


End-to-end use cases

1. Enrich a single company (simplest path)

Skills needed: cargo-orchestration

1. orchestration action execute            → run a connector action on one record
   --action '{"kind":"connector","integrationSlug":"clearbit","actionSlug":"company_enrich","config":{}}'
   --data '{"domain":"acme.com"}' --wait-until-finished
2. Enrich a list of companies and push to CRM

Skills needed: cargo-storage, cargo-connection, cargo-orchestration, cargo-analytics

1. storage model get-ddl                   → get exact table name
2. connection connector list               → get enrichment + CRM connector UUIDs
3. connection integration get <slug>       → discover third-party action slugs (e.g. HubSpot, Clearbit)
4. orchestration tool list                 → find the enrichment tool
5. orchestration batch create      → run on a segment of companies
6. orchestration batch get         → poll until status is terminal
7. analytics run download          → export results
3. Score leads with AI and update the model

Skills needed: cargo-ai, cargo-orchestration, cargo-billing

1. ai agent list                   → find or create the scoring agent
2. ai agent create                 → configure instructions, model, temperature 0.0
3. orchestration play list         → find the scoring play
4. orchestration batch create      → trigger on a segment of new leads
5. orchestration batch get         → poll until status is terminal
6. billing usage get-metrics       → check credit consumption
4. Build a custom enrichment workflow from scratch

Skills needed: cargo-connection, cargo-orchestration

1. connection connector list               → get connector UUID
2. connection integration get <slug>       → get actionSlug for the third-party service
3. orchestration node validate --nodes     → validate graph before running
4. orchestration run create --nodes        → run with custom node graph
5. orchestration run get                   → poll to terminal state
5. Monitor workflow health and alert on errors

Skills needed: cargo-orchestration, cargo-analytics

1. orchestration tool list / play list    → discover workflowUuid
2. analytics run count --statuses error   → count errors in period
3. analytics run get-metrics              → get success/error rate breakdown
4. analytics run download --statuses error → download failed runs for inspection
6. Bootstrap a fresh workspace

Skills needed: cargo-workspace-management, cargo-storage, cargo-connection, cargo-ai

1. workspace token create --name <label>   → create a dedicated, named API token
2. workspace role list             → discover available roles
3. workspace user create           → invite team members
4. storage model create            → create Companies and Contacts models
5. storage column create           → add columns (name, domain, employee_count, etc.)
6. storage relationship set        → link Contacts → Companies
7. connection connector create     → connect enrichment and CRM integrations
8. ai agent create                 → configure an AI agent for research or scoring
9. workspace folder create         → organize plays and tools into folders
7. Export and analyze segment data

Skills needed: cargo-storage, cargo-analytics

1. storage model list              → get modelUuid
2. analytics segment download      → export with filter and sort
   --filter '{"conjonction":"and","groups":[
     {"conjonction":"and","conditions":[
       {"kind":"string","columnSlug":"country","operator":"is","values":["US"]}
     ]}
   ]}'
   --sort '[{"columnSlug":"created_at","kind":"desc"}]'

Common gotchas

GotchaDetail
conjonction spellingFilter JSON uses conjonction (not conjunction). This is intentional. A typo here fails silently — no records returned.
run create vs batch createrun create only works with tool workflows. Using a play's workflowUuid returns playNotCompatible.
--model-uuid vs --segment-uuidsegment fetch and segment download require --model-uuid. Get it from segment list → .modelUuid.
DDL before SQLNever guess table names. Always run model get-ddl <uuid> first. Table names look like datasets_default.models_companies.
Token shown onceAPI token values are only returned at creation. Store immediately. workspace token create requires --name (no more --from-user).
Invoice amounts in centssubscription get-invoices returns amount in cents. Divide by 100.
Plays vs toolsPlay = reacts to data changes (segment-driven). Tool = triggered on demand (manual, API, cron).
Batch data kindsPlay workflows accept: segment, change, filter, recordIds. Tool workflows accept: file, records.
Third-party connector rate limitsOnly kind: "connector" nodes (Clearbit, HubSpot, etc.) have rate limits — native nodes do not. Errors grow silently as the batch runs. Start at 1 record, then 50, then 500 before full-scale. Add retry with backoff to connector nodes.

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