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-aiWrote 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-ai)<a href="https://agentmods.dev/skills/getcargohq/cargo-skills/cargo-ai"><img src="https://agentmods.dev/badge/skills/getcargohq/cargo-skills/cargo-ai/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-ai"><img src="https://agentmods.dev/badge/skills/getcargohq/cargo-skills/cargo-ai.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, 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 Data Exfiltration · line 174 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium MCP Rug Pull · line 39 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 | $0.00169 | $0.04530 |
| Opus 5 | $0.00084 | $0.02265 |
| Sonnet 5 | $0.00034 | $0.00906 |
| Haiku 4.5 | $0.00017 | $0.00453 |
Grade A, and why
cargo-ai scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sS -X PUT "$CARGO_API_BASE/v1/ai/releases/draft/update" \ How it starts
The opening of the file, as written. The whole thing — 317 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cargo CLI — AI
Agent resource management: creating and configuring agents, attaching knowledge for retrieval-augmented generation (RAG), connecting MCP servers, and managing agent memories.
For using agents (sending messages, multi-turn chat, polling), use
cargo-orchestration. For uploading knowledge files and building knowledge libraries (thecontentdomain), usecargo-content. This skill covers how that knowledge attaches to an agent. For workspace administration — folders (used to organize agents and files), users, API tokens, roles, and submitting reports when the CLI fails — usecargo-workspace-management.
See
references/response-shapes.mdfor full JSON response structures. Seereferences/troubleshooting.mdfor common errors and how to fix them. Seereferences/examples/agents.mdfor agent CRUD and configuration examples. Seereferences/examples/mcp-servers.mdfor MCP server creation and management examples.
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 [email protected] # 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
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.
Discover resources first
cargo-ai ai agent list # all agents (uuid, name, description)
cargo-ai ai template list # all AI agent templates (slug, name)
cargo-ai ai mcp-server list # all MCP servers (uuid, name)
cargo-ai ai memory list --scope agent --agent-uuid <uuid> # agent memories
# Knowledge files & libraries live in the content domain — see cargo-content:
# cargo-ai content file list / cargo-ai content library list
What ships with it
6 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.
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.
- 7d ago Changed · +2 lines a85b2fc947df
- 11d ago First seen · 315 lines · 169 tokens per session scan A de5ef8b0a0f0
cargo-ai is a skill published in the GitHub repository getcargohq/cargo-skills (17 stars, last pushed today), licensed MIT. It adds 169 tokens to every session and 4,530 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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