Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/getcargohq/cargo-skillsnpx agentmods add skills/getcargohq/cargo-skills/cargo-orchestrationWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/getcargohq/cargo-skills/cargo-orchestration)<a href="https://agentmods.dev/skills/getcargohq/cargo-skills/cargo-orchestration"><img src="https://agentmods.dev/badge/skills/getcargohq/cargo-skills/cargo-orchestration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/getcargohq/cargo-skills/cargo-orchestration"><img src="https://agentmods.dev/badge/skills/getcargohq/cargo-skills/cargo-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 114 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00205 | $0.09262 |
| Opus 5.5 | $0.00082 | $0.03705 |
| Sonnet 5.5 | $0.00041 | $0.01852 |
| Haiku 4.5 | $0.00020 | $0.00926 |
Grade A, and why
cargo-orchestration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 585 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cargo CLI — Orchestration
Runtime operations for the Cargo platform.
What do you want to run?
Need to run something?
├── Don't know the action yet → action list <keywords>
├── One action, one record → action execute
├── One action, many records → action execute-batch
├── Multiple actions chained
│ ├── One-off / ad-hoc → run create --nodes (one record)
│ │ batch create --nodes (many records)
│ └── Reusable workflow → build a tool, then run create --workflow-uuid
│ or batch create --workflow-uuid
├── Conversational AI agent → message create
└── Testing ONE node of a
workflow you're building → node execute (debug only — see below)
Fanning out across many records (
action execute-batch,batch create)? Sample first. Run 10–20 records, report the observed cost and hit-rate, then ask the user to approve the full enrollment — quoting the record count and the credit estimate. See Create a batch → the sample gate.
Every node execution costs 0.01 credits — 1 credit per 100 — whatever the node is.
branch,filter,switch,variablesand the rest carry no provider price, but they are not free: the charge is per execution, so a graph's cost has two terms,(provider cost × records) + (nodes × records ÷ 100). On step-heavy, action-light graphs the second term dominates. It shows up in no per-node field — notexecutions[].creditsUsedCount, notspans.execution_credits_used_count— only inbilling usage get-metrics --unit orchestration.executions. Quote both terms in the approval message (../cargo-gtm/references/cost-discipline.md§1).
Find the action before you hand-write the JSON.
cargo-ai orchestration action list <keywords>searches the integration catalog, Cargo native actions, workspace tools, and agents in one call — free, runs nothing — and each result carries a ready-to-pasteactionobject (withconnectorUuidalready filled in), the action's credit costs, and its autocomplete slugs. Narrow with--kind connector|native|tool|agent,--integration-slug <slug>,--limit(no default: omit it and every match comes back).unknown commandmeans the CLI predates it — refresh.
action execute, notnode execute, is the default for running something.node executeis a debug surface for a node that already lives in a workflow: it requires--workflow-uuid,--release-uuid,--node,--computed-configand--context(all five, enforced client-side), and it bills like any live call. If you just want an operation's output — enrich a domain, call a connector action, invoke a tool or agent — useaction execute/action execute-batchwith a small--action+--datapayload. Only reach fornode executewhen verifying one node's behavior before running the full graph.
Terminology: An orchestration tool is a saved on-demand workflow (listed via
tool list). An action is a single operation you execute without building a workflow — it can embed a saved orchestration tool (kind: "tool"), call a third-party connector (kind: "connector"), invoke an AI agent (kind: "agent"), or run a built-in platform operation (kind: "native").
Composing a node graph? Build it from dedicated actions + expressions, in this order:
- A dedicated action. Search first with
action list <keywords>(free): connector actions, native actions (agent,modelUpsert,branch,group…), tools.- An expression for the glue. It's inline JavaScript in the field that needs the value: reshaping, payloads, conditions, arrays.
- HTTP, only if step 1 found no action for that API.
- A
scriptnode, only if the logic can't fit in an expression.See
references/node-selection.md.
Show the graph, don't describe it. Before deploying a draft, and whenever the user asks what a workflow or play does, draw it:
cargo-ai orchestration node diagram --workflow-uuid <uuid> --format ascii --raw(free, runs nothing;--formatneeds CLI ≥ 1.0.56, the command itself ≥ 1.0.54). Routing, fallback edges, and which steps bill are what the user is actually approving, and prose flattens all three. Pick the format by where the output goes:asciirenders a picture a person can read in a terminal or a chat reply;mermaid(the default) is source code, correct only when you are pasting into a PR, a doc, or a page that renders it. Sources, the ASCII legend, cost marking, and the duplicate-slug footgun:references/node-diagram.md.
What ships with it
15 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/examples/actions.md 14 KB
- references/examples/agents.md 7.8 KB
- references/examples/plays.md 13 KB
- references/examples/queries.md 4.5 KB
- references/examples/segments.md 9.4 KB
- references/examples/templates.md 7.5 KB
- references/examples/tools.md 14 KB
- references/filter-syntax.md 9.6 KB
- references/node-diagram.md 11 KB
- references/node-selection.md 5.3 KB
- references/nodes.md 48 KB
- references/polling.md 7.1 KB
- references/response-shapes.md 16 KB
- references/troubleshooting.md 17 KB
- skill-metadata.json 2.1 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed · -6 tokens per session 854a47cf56cf
- 6d ago Changed · +7 lines 7b3b6e725624
- 12d ago Changed fa7a960955c9
- 13d ago Changed · +45 lines 45067616202e
- 19d ago Changed bf86fc288372
- 1mo ago Changed · +3 lines 68d15153c68a
- 1mo ago Changed 8f772c41d324
- 1mo ago Changed · +8 lines ea0531c31525
- 1mo ago Changed · -1 tokens per session d58dfecf199c
- 1mo ago First seen · 522 lines · 212 tokens per session scan A 76e79e356abf
cargo-orchestration is a skill published in the GitHub repository getcargohq/cargo-skills (21 stars, last pushed yesterday), licensed MIT. It adds 205 tokens to every session and 9,262 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
cargo-orchestration compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| cargo-orchestrationgetcargohq/cargo-skills | Skill | 21 | yesterday | MIT | A | 205 | Claude Code |
| everme-memoryEverMind-AI/EverMe | Skill | 74 | 2d ago | Apache-2.0 | A | 83 | Claude Code, Codex |
| memory-toolsEverMind-AI/EverMe | Skill | 74 | 2d ago | Apache-2.0 | A | 71 | Claude Code |
| everme-agent-skillEverMind-AI/EverMe | Skill | 74 | 2d ago | Apache-2.0 | A | 90 | Claude Code, Codex |
| memory-recallEverMind-AI/EverMe | Skill | 74 | 2d ago | Apache-2.0 | A | 30 | Claude Code |
| ai-sdrThe-Utopia-Studio/skills | Skill | 7 | 11d ago | Apache-2.0 | A | 102 | Claude Code |
| gtm-engineeringThe-Utopia-Studio/skills | Skill | 7 | 11d ago | Apache-2.0 | A | 107 | Claude Code |