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cargo-context

Read and write the workspace GTM knowledge base — the git-backed repository of markdown describing ICPs, personas, plays, proof points, objections, competitors, and signals — plus its runtime sandbox and typed knowledge graph. Triggers: "document our ICP", "write up this persona", "what is our positioning", "add a battlecard", "capture this objection", "what do we know about <segment>", "update our context", "what is in the context repo", "who do we sell to". Skip when: discovering who actually buys from you by analyzing won/lost data — that is cargo-gtm (this skill writes the conclusion down, it does not derive it); storing structured records rather than prose — use cargo-storage; attaching documents to an agent for RAG — use cargo-content.

OpenClaw

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Rank

Safety

Downloads

1.4k

Updated

Oct 10, 2026

Version

1.3.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.4K downloads reported by the source. Last updated 10/10/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 10, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 10, 2026
Adoption signal: 1.4K downloadsadoption · observed Oct 10, 2026
Latest release: 1.3.0release · observed Sep 2, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s178dcd9wkfn0a2fqrygmt3jzn87j9e1:cargo-context

Install using `clawhub skill install s178dcd9wkfn0a2fqrygmt3jzn87j9e1:cargo-context` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/cargo-ai/cargo-context before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-cargo-ai-cargo-context/snapshot"

Documentation

CLAWHUB

147,932 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: cargo-context
description: "Read and write the workspace GTM knowledge base — the git-backed repository of markdown describing ICPs, personas, plays, proof points, objections, competitors, and signals — plus its runtime sandbox and typed knowledge graph. Triggers: \"document our ICP\", \"write up this persona\", \"what is our positioning\", \"add a battlecard\", \"capture this objection\", \"what do we know about <segment>\", \"update our context\", \"what is in the context repo\", \"who do we sell to\". Skip when: discovering who actually buys from you by analyzing won/lost data — that is cargo-gtm (this skill writes the conclusion down, it does not derive it); storing structured records rather than prose — use cargo-storage; attaching documents to an agent for RAG — use cargo-content."
version: "1.3.0"
compatibility: Requires @cargo-ai/cli (npm). Sign in or create an account with `cargo-ai login --email` (emailed code, no browser), `--oauth`, or an API token
homepage: https://github.com/getcargohq/cargo-skills
metadata:
  author: getcargo
  openclaw:
    requires:
      bins:
        - cargo-ai
    install:
      - kind: node
        package: "@cargo-ai/cli@latest"
        bins:
          - cargo-ai
    homepage: https://github.com/getcargohq/cargo-skills
---

# 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`/`edit` are pushed to the default branch; `execute` runs 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`](https://github.com/getcargohq/cargo-workspaces). Read its `README.md` to understand the domain layout and file conventions before writing new entries.
> For uploading runtime-independent files (CSVs, PDFs) used in batch runs, use [`cargo-workspace-management`](../cargo-workspace-management/SKILL.md) (`cargo-ai workspaceManagement file upload`) instead.
> For RAG file attachments to agents, use [`cargo-ai`](../cargo-ai/SKILL.md) (`cargo-ai content file upload`).

> See `references/conventions.md` for the full context repo structure and per-domain templates.
> See `references/response-shapes.md` for the JSON shapes returned by each `cargo-ai context` command.
> See `references/troubleshooting.md` for common errors and how to fix them.
> See `references/examples/authoring.md` for end-to-end add / edit / delete recipes.
> See `references/examples/lifecycle.md` for the bootstrap + refresh-from-calls playbook.
> See `references/examples/graph-queries.md` for inspecting the know

_meta.json

{
  "ownerId": "kn7by8t6yt9yghbxtxz6hv0bts87k6bq",
  "slug": "cargo-context",
  "version": "1.3.0",
  "publishedAt": 1788392474742
}

references/conventions.md

# Context repo conventions

The conventions below are inherited from the canonical context repository [`getcargohq/cargo-workspaces`](https://github.com/getcargohq/cargo-workspaces). When in doubt, read its `README.md` and the `_template.md` file in the relevant domain.

## Domains

| Domain | Purpose |
|---|---|
| `global/` | Company-level context: mission, voice, positioning, narrative, pricing |
| `icp/` | Ideal Customer Profile segments |
| `persona/` | Buyer personas (roles inside an ICP) |
| `jtbd/` | Jobs-to-be-done framings |
| `alternative/` | Competitors, substitutes, status quo |
| `client/` | Customer profiles, case studies, reference accounts |
| `insight/` | Market insights and observations |
| `medium/` | Channel playbooks (email, LinkedIn, cold call, etc.) |
| `objection/` | Objections + responses + proof |
| `play/` | GTM plays (signal → audience → channel → sequence → outcome) |
| `proof/` | Atomic proof points (metrics, quotes, case data) |
| `signal/` | Buying signals and intent triggers |

## File conventions

- **Filename:** `kebab-case.md` (e.g. `vp-sales-mid-market.md`). Use ASCII letters, digits, and hyphens only.
- **Frontmatter:** YAML with `title` and `description` on every `.md`/`.mdx` file. This is a **strong convention, not enforced** — a write with missing, empty, or malformed frontmatter is still committed; it just indexes poorly. The graph reads `title` (fallback: filename) and `summary` (fallback: first paragraph), **not** `description`. See [Source references and the knowledge graph](#source-references-and-the-knowledge-graph).
- **Cross-references:** `domain/slug` form, **no `.md` extension** (e.g. `persona/vp-sales-mid-market`). To register as a graph **edge**, a reference must appear as a wikilink, a markdown link, or a frontmatter `references:` entry (see below) — a bare `domain/slug` or file path in plain prose is not parsed.
- **Templates:** each domain ships an `_template.md`. Read it (`cargo-ai context runtime read --path <domain>/_template.md`) before authoring a new entry. `_template.*` files are excluded from the graph — never reference them.
- **Bidirectional links:** keep cross-refs symmetric when it makes sense — a `play` that targets a `persona` should appear in the persona's `Preferred channels` or `How we land` sections when relevant.

## Source references and the knowledge graph

The graph is built from **every `.md`, `.mdx`, `.yaml`, and `.yml` file** in the repo (any folder; only `.git/` is excluded). Each file becomes a node. **Edges are created only from these three forms** — everything else is invisible to the graph:

1. **Frontmatter `references:` list** (preferred for source citations — keeps prose clean, and the edge carries a `frontmatter` origin):

   ```yaml
   ---
   title: AgoraPulse expansion thesis
   description: Why the AgoraPulse account is ready for a multi-thread expansion play.
   references:
     - outputs/sales-notes/2026-06-05-agorapulse-build-session-1-outcomes.md
   -

references/examples/authoring.md

# Authoring examples

End-to-end recipes for adding, editing, and removing entries in the context repo. All examples assume you're authenticated (`cargo-ai whoami` works) and that the workspace already has a context repository configured.

> **Lead with frontmatter.** Every `.md`/`.mdx` write below starts with a YAML block carrying `title` and `description`. This is a strong convention, **not enforced** — a file with missing or malformed frontmatter is still committed, it just indexes poorly (the graph falls back to the filename for `title` and the first paragraph for the summary). To cite a source file so it shows up as a **graph edge**, list it in frontmatter `references:` (or use a markdown link / wikilink) — a bare path in prose creates no edge. See `../conventions.md` for the full linking rules.

## Discover before writing

```bash
# 1. What domains exist?
cargo-ai context runtime browse

# 2. What's already in the target domain? (avoid duplicates)
cargo-ai context runtime browse --path persona

# 3. What's the shape of an entry in this domain?
cargo-ai context runtime read --path persona/_template.md
```

## Add a persona

```bash
cargo-ai context runtime write \
  --path persona/head-of-revops.md \
  --content "$(cat <<'EOF'
---
title: Head of RevOps
description: Owns the GTM tech stack, data quality, and pipeline reporting at a 200–2,000-person B2B SaaS.
---

## Role

- Title: Head of RevOps / Director of RevOps
- Seniority: Director / VP
- Function: Revenue Operations
- Reports to: CRO or COO

## KPIs

- Pipeline velocity, forecast accuracy, data freshness, CRM hygiene, lead-to-opp conversion

## Pains

- Stale enrichment, broken CRM workflows, slow rep ramp because the data model is brittle
- Stitching together 6 point tools that don't talk to each other
- Manual segment refreshes for plays

## Motivations

- One source of truth across SDR, AE, CS
- Replace fragile Zapier chains with durable workflows
- Get out of the way of the frontline

## Day-to-day

Ops standup, reviewing failed syncs, building a new segment for an outbound play, fielding rep requests, and weekly forecast prep with the CRO.

## Preferred channels

_Cross-ref `medium/...`._

- medium/peer-community-slack
- medium/founder-led-linkedin

## Common objections

_Cross-ref `objection/...`._

- objection/we-already-have-clay
- objection/we-built-this-in-house

## How we land

Lead with the stack-replacement angle: "one durable workflow runtime that replaces enrichment + scoring + sync." Show, don't tell — run a workflow live against their domain on the demo call.
EOF
)" \
  --commit-message "Add Head of RevOps persona"
```

## Add a play with cross-refs

```bash
cargo-ai context runtime write \
  --path play/funding-triggered-outbound.md \
  --content "$(cat <<'EOF'
---
title: Funding-triggered outbound
description: Reach out to companies within 14 days of a Series A–C raise with a hiring-and-stack angle.
---

## Hypothesis

Companies hit a stack-and-headcount inflection r

references/examples/bootstrap-from-domain.md

# Bootstrap workspace context from a domain

The prescriptive, automatable version of Phase 1 of [`lifecycle.md`](lifecycle.md). Use this when the user wants to **seed an empty (or thin) context repo from public data**, starting from nothing more than their company's domain. The recipe enriches the company via aiArk + builtwith + enrichCrm + theirStack, scrapes public sources in parallel sub-agents, and writes one file per atomic concept through `cargo-ai context runtime write` — skipping any domain that already has content.

Output: a populated `global/`, `icp/`, `persona/`, `client/`, `proof/`, `signal/` (and where evidence supports it, `alternative/`, `objection/`, `insight/`) — enough that a fresh agent session can hold a coherent conversation about the company. Phase 2 (call-driven refinement) is deliberately out of scope here — see the "What this recipe does NOT do" section.

**Trigger phrases:**
- *"Set up my workspace context from acme.com."*
- *"Bootstrap the context repo — my domain is acme.com."*
- *"Fill in the ICP and personas from our website."*
- *"My workspace is empty, just use our domain to populate everything."*

## What this recipe exercises

- `cargo-ai context runtime browse` / `graph get` for the idempotency check.
- Domain-keyed enrichments (`aiArk.enrichCompany`, `builtwith.getDomainSummary`, `enrichCrm.getFunding`) for the factual spine.
- Parallel sub-agents for public-source scraping (website, careers, blog, news, review sites).
- The driving agent's native LLM to synthesize each digest into typed markdown matching the per-domain template (no `cargo-ai orchestration action execute` double-hop — that pattern is for workflow node graphs, not for an agent already in the loop).
- `cargo-ai context runtime write` to commit one file per concept.

## Required inputs

Before executing, the agent needs:
1. **`domain`** (required) — canonical domain (`acme.com`), no protocol, no path.
2. **`companyName`** (optional) — falls back to whatever `aiArk.enrichCompany` returns for the domain.
3. **`depth`** (optional, default `standard`) — `minimal` (global + 1 icp + 2 personas), `standard` (full domain coverage), `deep` (also scrapes G2/Capterra/Reddit/HN for objections + alternatives).

If `domain` is missing, ask **once** and stop. Don't guess from the user's email — workspace domain and user email often diverge.

## Recipe

### Step 1 — Confirm the target workspace

Each Cargo workspace maps to one company. `runtime write` pushes immediately. Wrong workspace = polluted repo for someone else.

```bash
cargo-ai whoami
# → user.email, workspace.uuid, workspace.name
```

Read back `workspace.name` to the user and confirm it matches the company the `domain` belongs to. **Stop and ask** if the name is generic (`"Main"`, `"Test"`, a person's name, an internal codename) — workspace names are user-set and frequently don't match the customer-facing brand.

**Non-interactive mode** (server-side trigger from signup, scheduled job, etc.): skip

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