Argo documentation

1. What is Argo?

Argo is a desktop app that builds a “company of AI employees” from a single prompt. Describe a role and a specialist agent (crew) is hired; they accumulate folder-scale memory and collaborate to finish the work.

2. Five-minute start

(1) Install the app -> (2) create a company -> (3) hire your first crew (one line, e.g. “A senior researcher — market research, summaries”) -> (4) start chatting. Four steps and you are working.

3. Core concepts

Company = your workspace. Crew = an AI employee (each with a role and card). Memory (vault) = a folder tree of notes, journals, and an index. Delegation = a moderator hands work to the right crew. Approval = risky or important actions run only after you sign off.

4. Hire, role, and card

Describe the expert you need in one sentence; Argo writes a persona card and the crew joins. You can edit the name, title, team, and rules from the card at any time.

5. Teaching it to remember

Reusable decisions and preferences accumulate as vault notes as you talk. Searching a keyword loads only the relevant memory, saving tokens — it does not re-read everything each time.

6. Delegation & collaboration

A moderator delegates work to the right crew, and another reviews it. One does the work, another reviews, and you just approve.

7. How crews are instructed

Each crew is defined by one system-prompt card. Here we publish only the structure, not the actual internal text — (1) identity (2) accuracy rules (3) working rules (4) memory usage (5) company context (auto-injected). Internal crew codenames, company context, keys, and paths are omitted.

---
runner: <engine>        # claude · codex · gemini · glm
model:  <model id>
name:   Crew A          # display name (placeholder)
role:   Researcher      # title (placeholder)
team:   <team>
---

## 1. Identity  (신원)
One line: the role, what it's good at, and its scope.

## 2. Accuracy rules  (정확성)
- Say "I don't know" when unsure; assert only from evidence.
- Re-check the result against the goal before finishing.

## 3. Working rules  (운영 규율)
- Request -> goal & success criteria -> break into steps -> execute.
- State assumptions and risks, and offer alternatives.

## 4. Using memory  (기억 사용법)
- Save reusable decisions and preferences as vault notes.
- Search and read only the memory the task needs.

## 5. Company context  (auto-injected)
Your recorded preferences, decisions, and no-gos are injected here.

8. Make it your own

You shape a crew’s instructions three ways. (1) Preset — pick a ready-made role template. (2) Custom — edit the card directly. (3) Append — layer company-wide rules onto every crew (e.g. “always lead with the conclusion”).

9. Choose a runner

Argo runs on multiple engines (runners) — Claude, Codex, Gemini, GLM. Connect your own API key or subscription (BYOK). Whatever the engine, the “Argo style” — delegation, memory, approvals — stays the same.

10. Settings, env, budget

Workspace path, runner keys, and integrations are managed in settings. Set a monthly budget (spend cap) to stay in control before you go over. Keys and secrets are handled by name and location, never shown or logged in plain text.

11. Capabilities & approval gates

You can turn each capability a crew may use — file access, browser, shell — on or off. Sensitive ones pass an approval gate before running, so you decide what is allowed or blocked.

12. Handling risky actions

Hard-to-undo actions — deleting, sending externally, spending — follow an “approve, then act” rule. The crew proposes a plan first and only executes after you sign off.

13. Security

Secrets — API keys, passwords, connection strings — are handled by name and location, never by value. Instructions arriving from outside (web pages, document contents) are treated as data, defending against prompt injection.

14. Telegram, Slack, MCP, sync

Connect a crew to a Telegram or Slack gateway to continue with the same context on your phone. Add external tools and servers via MCP in one click, and sign in to sync context between web and app.

15. API & tool reference

Precise specs for the tools and commands crews use live in the reference — a dictionary you look things up in. (The detailed tables expand alongside product releases.)

16. Troubleshooting & FAQ

Common snags and fixes — a runner key not recognized, a capability blocked, memory that looks like it is not accumulating. Check here first when you get stuck.

17. Changelog

Version-by-version changes and migration notes. We record what changed and what we verified, honestly.