cargo-context

Original：🇺🇸 English

Translated

Inspect and edit the workspace's git-backed context repository (the GTM knowledge base of markdown/MDX files) and its runtime sandbox using the Cargo CLI. Use when the user wants to browse/read/write/edit context files, run a command in the sandbox, or inspect the context knowledge graph.

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Sourcegetcargohq/cargo-skills

Added on2026-06-16

NPX Install

npx skill4agent add getcargohq/cargo-skills cargo-context

SKILL.md Content

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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
. 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-ai workspaceManagement file upload
) instead. For RAG file attachments to agents, use
cargo-ai
(
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 knowledge graph.

Prerequisites

See

../cargo/references/prerequisites.md

for install, login (

--oauth

--token

), JSON output conventions, and error shapes. Verify the session with

cargo-ai whoami

before running any of the commands below —

runtime write

and

runtime edit

push commits to the workspace's context repo, so confirming

workspace.name

first is non-negotiable.

Discover the context first

Before editing anything, see what's in the context repo:

bash

cargo-ai context runtime browse                 # list entries at the runtime sandbox root
cargo-ai context graph get                      # full knowledge graph derived from the repo's md/mdx files

Quick reference

bash

# Runtime sandbox (checked-out copy of the context repo)
cargo-ai context runtime browse [--path <path>]
cargo-ai context runtime read --path <path> [--start-line <n>] [--end-line <n>]
cargo-ai context runtime write --path <path> --content <content> [--commit-message <message>]
cargo-ai context runtime edit --path <path> --old-string <old> --new-string <new> [--commit-message <message>]
cargo-ai context runtime execute --command <command> [--args <json>]

# Knowledge graph
cargo-ai context graph get

Runtime sandbox

The runtime sandbox is a checked-out, executable copy of the context repository. It's the surface you use to read and modify context files, and to run commands against them.

Two important behaviors to remember:

write
and
edit
push to the default branch of the context repo. They are not local-only.
execute
does not push. Changes made to files by a shell command run via
```
execute
```
stay in the sandbox and are discarded — use
```
execute
```
for builds, tests, or inspection, not for committing edits.

Uploaded content files are available read-only under
.files/
. The workspace's

content file

uploads (PDFs, CSVs, text — see

cargo-content

) appear in the sandbox under a

.files/

directory, so a command run via

execute

(or

read

browse

) can consume them — e.g.

cargo-ai context runtime execute --command ls --args '["-1",".files"]'

. It sits outside the committed context tree: the sandbox's auto-commit skips it, so nothing under

.files/

is ever pushed to the context repo, and you can't add or change content files from here (use

cargo-ai content file …

instead).

Because writes push immediately, confirm the target workspace before the first
write
/
edit
:

bash

cargo-ai whoami   # → workspace.uuid, workspace.name

Read the workspace name back to the user. If the session is for a specific client, make sure

workspace.name

matches before authoring anything — there is no dry-run mode. If

workspace.name

is generic or ambiguous (e.g. "Main", "Test", a person's name, an internal codename), don't guess — ask the user for the company name and canonical domain (

example.com

) and confirm both before the first write. If you logged in without pinning a workspace, re-run

cargo-ai login --oauth --workspace-uuid <uuid>

(or

--token <workspace-scoped-token>

for non-interactive use).

Edits derived from sales-call analysis should be applied one at a time with human review, not batched. Looping an agent over many calls tends to overweight the loudest signal and miss nuance — see

references/examples/lifecycle.md

for the call-refresh playbook.

Browse and read

bash

# List entries at the root of the runtime sandbox
cargo-ai context runtime browse

# List entries under a subpath (e.g. a domain folder like persona/ or play/)
cargo-ai context runtime browse --path persona

# Read a full file
cargo-ai context runtime read --path persona/vp-sales-mid-market.md

# Read only a line range (1-indexed, inclusive on both ends)
cargo-ai context runtime read --path play/inbound-trial-to-paid.md --start-line 1 --end-line 40

Write a new file

write

creates (or overwrites) a file and pushes a commit to the default branch.

Begin every

.md

.mdx

file with a YAML frontmatter block setting

title

and

description

. Frontmatter is not validated — a file with missing, empty, or malformed frontmatter is still written and committed; it just indexes poorly in the graph (a missing

title

falls back to the filename, the node summary to the first paragraph).

write

can still fail for other reasons —

repositoryNotFound

syncConflict

syncFailed

failedToWrite

, or

deniedPath

(e.g. writing under

.files/

); see

references/response-shapes.md

bash

cargo-ai context runtime write \
  --path persona/vp-sales-mid-market.md \
  --content "$(cat <<'EOF'
---
title: VP of Sales, mid-market
description: Owns pipeline, quota, and rep productivity at a 200–2,000-person company.
---

## Role
- Title: VP of Sales
- Seniority: Executive
- Function: Revenue
- Reports to: CRO or CEO

## KPIs
- New ARR, win rate, pipeline coverage, rep ramp time

## Pains
- Pipeline gaps, slow ramp, low rep activity, forecasting drift

## Motivations
- Hit the number, build a repeatable motion, get visibility

## Day-to-day
Forecast calls, deal reviews, pipeline reviews, 1:1s with frontline managers.

## Preferred channels
- medium/linkedin-outbound
- medium/exec-warm-intro

## Common objections
- objection/we-already-have-an-ai-sdr

## How we land
Lead with pipeline-coverage math, not features.
EOF
)" \
  --commit-message "Add VP of Sales mid-market persona"

Edit an existing file

edit

replaces a single exact substring.

--old-string

must occur exactly once in the file; pass an empty

--new-string

to delete the match.

edit

does not validate frontmatter — an edit that strips or empties

title

description

still applies, so keep the block intact to keep the node discoverable.

edit

can fail for other reasons, though:

stringNotFound

stringNotUnique

(the

--old-string

match),

fileNotFound

noOp

(new string equals old),

syncConflict

syncFailed

failedToEdit

, or

deniedPath

bash

# Replace one specific sentence
cargo-ai context runtime edit \
  --path global/positioning.md \
  --old-string "We help RevOps automate workflows." \
  --new-string "We help RevOps run AI-native GTM motions." \
  --commit-message "Refresh positioning one-liner"

# Delete a line (pass empty --new-string)
cargo-ai context runtime edit \
  --path persona/vp-sales-mid-market.md \
  --old-string "\n- Outdated stat: 4.2x pipeline\n" \
  --new-string ""

For larger restructures, prefer

write

(full-file overwrite) over many sequential

edit

calls.

Execute a command in the sandbox

execute

runs a shell command in the sandbox. Useful for inspecting structure or running checks; changes are not pushed.

bash

# Find every file that cross-references a specific slug
cargo-ai context runtime execute \
  --command grep \
  --args '["-r","-l","persona/vp-sales-mid-market","."]'

# Count entries per domain
cargo-ai context runtime execute --command ls --args '["-1","persona"]'

# Run a one-shot script (no quotes/escaping needed inside --command beyond JSON for args)
cargo-ai context runtime execute --command pwd

--args

is a JSON array of string arguments. Omit it for a no-arg command.

Context repository structure and conventions

The Cargo context repo is a typed knowledge base. The canonical example — and the source of the conventions below — is

getcargohq/cargo-workspaces

; read its

README.md

and

_template.md

files in each domain before writing new entries. For the full domain reference, see

references/conventions.md

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
```
).
Frontmatter: start every
```
.md
```
/
```
.mdx
```
file with YAML frontmatter setting
```
title
```
and
```
description
```
. This is a strong convention, not enforced — a write with missing, empty, or malformed frontmatter is still created and committed; it just indexes poorly. The graph reads
```
title
```
(fallback: filename) and
```
summary
```
(fallback: the file's first paragraph); it does not read
```
description
```
, so add a
```
summary:
```
if you want to control the node summary. See Source references and graph edges.
Cross-references: use the
```
domain/slug
```
form, no
.md
extension (e.g.
```
persona/vp-sales-mid-market
```
). To register as a graph edge a reference must use one of the three link forms below — a bare
```
domain/slug
```
(or file path) in plain prose creates no edge.
Templates: each domain ships an
```
_template.md
```
. Read it (
```
cargo-ai context runtime read --path persona/_template.md
```
) before authoring a new entry.
```
_template.*
```
files are excluded from the graph — never reference them.

Source references and graph edges

The knowledge graph is built from every

.md

.mdx

.yaml

, and

.yml

file in the repo (any folder; only

.git/

is excluded). Each file is a node, but edges are created only from three forms — anything else is invisible to the graph:

Frontmatter
references:
list (preferred for source citations — keeps prose clean):

yaml

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

A Markdown link in the body — standard
```
[label]
```
followed immediately by
```
(path)
```
syntax, where the target is the file path, e.g. an anchor linking to
```
outputs/sales-notes/2026-06-05-agorapulse-build-session-1-outcomes.md
```
.

Wikilinks in the body (extension optional):

[[outputs/sales-notes/2026-06-05-agorapulse-build-session-1-outcomes]]

Key constraints:

Never cite a source as a bare path in prose (e.g. a
```
Source:
```
line that just mentions
```
outputs/sales-notes/foo.md
```
as text) — it is not parsed and creates no edge.
Prefer root-relative paths (resolved from the repo root first, then relative to the citing file) so links work regardless of where the document lives.
Extensions are optional — the resolver auto-tries
```
.md
```
,
```
.mdx
```
,
```
.yaml
```
,
```
.yml
```
in that order. Including the extension is fine.
The target must exist or the edge is broken (a dead link in the graph UI). Verify with
```
runtime browse
```
before citing.
For docs with a Source/Evidence section, cite the files in frontmatter
```
references:
```
; use inline markdown links when the citation needs surrounding prose. Full rules:
```
references/conventions.md
```
.

Workflow: add a new entry

Confirm the target domain and copy its template:

bash

cargo-ai context runtime read --path persona/_template.md

```
write
```
a new file at
```
<domain>/<slug>.md
```
with
```
title
```
+
```
description
```
and the body sections filled in.
Add cross-refs (
```
domain/slug
```
) where useful — keep them bidirectional when it makes sense.
Rebuild the knowledge graph to verify the new entry and its links:
bash
```
cargo-ai context graph get
```

For full per-domain templates and worked examples, see

references/conventions.md

and

references/examples/authoring.md

Workflow: bootstrap and refresh

To stand up a new workspace's context repo from scratch, or to refresh an existing one on a cadence, follow the two-phase lifecycle in

references/examples/lifecycle.md

Bootstrap (one-time): seed
```
global/
```
,
```
persona/
```
,
```
client/
```
,
```
proof/
```
,
```
objection/
```
,
```
signal/
```
from public sources, then open a fresh agent session against the seeded repo. For the prescriptive, automatable version (domain in → files out, idempotent, with credit budget), use
```
references/examples/bootstrap-from-domain.md
```
.
Refresh (every 2–4 weeks): pull the last ~3 months of sales-call transcripts → analyze one at a time, human-in-the-loop → apply a repetition threshold before promoting any claim to context → validate by generating sequence permutations → diff the graph before/after and retire stale entries.

The repetition threshold (how many calls a claim must appear in before it lands in context) is documented in

references/conventions.md

Knowledge graph

context graph get

builds (or loads from cache) the knowledge graph over every markdown/MDX file in the context repo. Use it to:

Audit cross-references between domains (e.g. find personas that link to plays with no proof attached).
Discover what already exists before writing a new entry (avoid duplicates).
Power downstream agents that need the typed structure of the workspace's context.

bash

cargo-ai context graph get

The response includes the parsed frontmatter and outbound

domain/slug

references for each node — pipe it through

jq

to slice it. See

references/examples/graph-queries.md

for ready-to-run queries.

Help

Every command supports

--help

bash

cargo-ai context --help
cargo-ai context runtime browse --help
cargo-ai context runtime read --help
cargo-ai context runtime write --help
cargo-ai context runtime edit --help
cargo-ai context runtime execute --help
cargo-ai context graph get --help

cargo-context

NPX Install

Tags

SKILL.md Content

Cargo CLI — Context

Prerequisites

Discover the context first

Quick reference

Runtime sandbox

Browse and read

Write a new file

Edit an existing file

Execute a command in the sandbox

Context repository structure and conventions

Domains

File conventions

Source references and graph edges

Workflow: add a new entry

Workflow: bootstrap and refresh

Knowledge graph

Help