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-contextWrote 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-context)<a href="https://agentmods.dev/skills/getcargohq/cargo-skills/cargo-context"><img src="https://agentmods.dev/badge/skills/getcargohq/cargo-skills/cargo-context/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-context"><img src="https://agentmods.dev/badge/skills/getcargohq/cargo-skills/cargo-context.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 44 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 | $0.00166 | $0.04190 |
| Opus 5 | $0.00083 | $0.02095 |
| Sonnet 5 | $0.00033 | $0.00838 |
| Haiku 4.5 | $0.00017 | $0.00419 |
Grade A, and why
cargo-context 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 5d 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.
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 — 304 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cargo CLI — Context
The context is a git-backed repository of typed markdown/MDX files that captures a workspace's GTM knowledge (company narrative, ICPs, personas, plays, proof, objections, etc.) and is read/written by both humans and agents. The cargo-ai context domain has two subdomains you'll use:
- runtime — browse, read, write, edit, and execute against the workspace's runtime sandbox (a checked-out copy of the context repo).
write/editare pushed to the default branch;executeruns are not pushed. - graph — build/load the knowledge graph derived from every markdown/MDX file in the context repo.
The canonical example of a context repository is
getcargohq/cargo-workspaces. Read itsREADME.mdto understand the domain layout and file conventions before writing new entries. For uploading runtime-independent files (CSVs, PDFs) used in batch runs, usecargo-workspace-management(cargo-ai workspaceManagement file upload) instead. For RAG file attachments to agents, usecargo-ai(cargo-ai content file upload).
See
references/conventions.mdfor the full context repo structure and per-domain templates. Seereferences/response-shapes.mdfor the JSON shapes returned by eachcargo-ai contextcommand. Seereferences/troubleshooting.mdfor common errors and how to fix them. Seereferences/examples/authoring.mdfor end-to-end add / edit / delete recipes. Seereferences/examples/lifecycle.mdfor the bootstrap + refresh-from-calls playbook. Seereferences/examples/graph-queries.mdfor inspecting the knowledge graph.
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
What ships with it
8 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/conventions.md 9.0 KB
- references/examples/authoring.md 8.3 KB
- references/examples/bootstrap-from-domain.md 12 KB
- references/examples/graph-queries.md 2.8 KB
- references/examples/lifecycle.md 6.0 KB
- references/response-shapes.md 4.8 KB
- references/troubleshooting.md 5.7 KB
- skill-metadata.json 1.3 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.
- 5d ago Changed 97c3fe987985
- 10d ago First seen · 304 lines · 166 tokens per session scan A acc197e1f370
cargo-context is a skill published in the GitHub repository getcargohq/cargo-skills (17 stars, last pushed 4d ago), licensed MIT. It adds 166 tokens to every session and 4,190 once invoked, about $0.0008 per session on Opus 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.
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