CLI Reference — `agentlaunch` v1.2.9

Full command reference for the AgentLaunch CLI (28 commands). Scaffold, deploy, tokenize, and trade AI agent tokens from the terminal.

Install globally:

npm install -g agentlaunch

Verify:

agentlaunch --version
# 1.2.8

agentlaunch --help

Configuration

The CLI stores its configuration in ~/.agentlaunch/config.json (mode 0600 — owner read/write only). This file holds your API key and an optional custom base URL.

`agentlaunch config set-key <apiKey>`

Store your Agentverse API key locally.

agentlaunch config set-key av-xxxxxxxxxxxxxxxx
# API key saved to ~/.agentlaunch/config.json
# Key: av-xxxxxx... (masked)

Get your key at: https://agentverse.ai/profile/api-keys

`agentlaunch config show`

Print the current configuration with the API key masked.

agentlaunch config show
# Current configuration:
#   API Key:  av-xxxxxx... (masked)
#   Base URL: https://agent-launch.ai/api (production default, from .env)
#   Config:   ~/.agentlaunch/config.json

`agentlaunch config set-url <url>`

Override the API base URL. Useful for self-hosted instances or staging environments.

agentlaunch config set-url https://staging.agent-launch.ai/api
# Base URL set to: https://staging.agent-launch.ai/api

Reset to the production URL (the default):

agentlaunch config set-url https://agent-launch.ai/api

Or switch to dev:

agentlaunch config set-url https://launchpad-backend-dev-1056182620041.us-central1.run.app

Flags: None.

Config file location: ~/.agentlaunch/config.json

{
  "apiKey": "av-xxxxxxxxxxxxxxxx",
  "baseUrl": "https://agent-launch.ai/api"
}

Environment URL Configuration

The CLI defaults to production (https://agent-launch.ai/api). You can switch environments in two ways:

Option 1: Environment variable

Set AGENT_LAUNCH_ENV=dev to use the dev backend automatically:

export AGENT_LAUNCH_ENV=dev
agentlaunch list   # Uses dev backend

Variable	Production (default)	Dev
`AGENT_LAUNCH_API_URL`	`https://agent-launch.ai/api`	`https://launchpad-backend-dev-1056182620041.us-central1.run.app`
`AGENT_LAUNCH_FRONTEND_URL`	`https://agent-launch.ai`	`https://launchpad-frontend-dev-1056182620041.us-central1.run.app`

Option 2: Direct override

Set AGENT_LAUNCH_API_URL directly to point at any backend:

export AGENT_LAUNCH_API_URL=https://my-custom-backend.example.com
agentlaunch list   # Uses custom backend

Priority order: AGENT_LAUNCH_API_URL > config set-url > AGENT_LAUNCH_ENV > production default.

Authentication

`agentlaunch auth wallet`

Authenticate with a wallet private key to obtain an Agentverse API key programmatically.

# ZERO-TO-HERO: Generate a new wallet + API key (saves both to .env)
agentlaunch auth wallet --generate

# Use WALLET_PRIVATE_KEY from .env or environment
agentlaunch auth wallet

# Explicit private key (caution: visible in shell history!)
agentlaunch auth wallet --private-key 0x...

# Save API key to .env automatically
agentlaunch auth wallet --save

# JSON output
agentlaunch auth wallet --json

Flags:

Flag	Description	Default
`--generate`	Generate a new wallet (saves both WALLET_PRIVATE_KEY and API key)	false
`--private-key <key>`	Hex-encoded private key (prefer `WALLET_PRIVATE_KEY` env var)	from env
`--save`	Save the API key to `.env` file in current directory	false
`--json`	Output raw JSON	false

Zero-to-hero flow:

The --generate flag creates everything you need from scratch:

Generates a new random wallet using ethers.Wallet.createRandom()
Authenticates with Agentverse to get an API key
Saves both WALLET_PRIVATE_KEY and AGENTVERSE_API_KEY to .env
You're ready to deploy agents immediately!

Security notes:

Using --private-key exposes the key in shell history — prefer WALLET_PRIVATE_KEY env var
Private keys are never logged or displayed
The resulting API key is also saved to ~/.agentlaunch/config.json

Dependencies: All required crypto dependencies (@cosmjs/crypto, bech32, ethers) are bundled with the CLI - no manual installation needed.

Example output:

  Authenticating with wallet...
  Cosmos Address: fetch1abc123...
  Requesting challenge...
  Signing challenge...
  Exchanging for API key...

==================================================
AUTHENTICATION SUCCESSFUL
==================================================
Cosmos Address: fetch1abc123...
API Key:        av-xxxxxx... (masked)
Expires:        2026-05-03 (30 days)
Saved to:       ~/.agentlaunch/config.json
                .env (current directory)
==================================================

You can now use all agentlaunch commands.

`agentlaunch auth status`

Check if the current API key is valid.

agentlaunch auth status
agentlaunch auth status --json

Flags:

Flag	Description	Default
`--json`	Output raw JSON	false

Example output:

  Checking API key...

----------------------------------------
API KEY STATUS
----------------------------------------
  Configured: Yes
  Valid:      Yes
  Key:        av-xxxxxx... (masked)
----------------------------------------

`agentlaunch [name]` — default command

Create an agent, deploy it to Agentverse, and open Claude Code.

npx agentlaunch                           # Interactive — prompts for name, description, API key
npx agentlaunch my-bot                    # Create agent named "my-bot" (deploys by default)
npx agentlaunch my-bot --local            # Scaffold only, no deploy
npx agentlaunch my-bot --template research --local  # Scaffold with specific template

Flags:

Flag	Description	Default
`--local`	Scaffold only, don't deploy to Agentverse	false (deploys by default)
`--template <t>`	chat-memory, swarm-starter, custom, research, trading-bot, data-analyzer, price-monitor, gifter	chat-memory
`--json`	Output only JSON	false

Default template: chat-memory — includes LLM integration and conversation memory out of the box.

Example output:

Creating agent: my-bot
Template: chat-memory (LLM + conversation memory)
Directory: /home/user/my-bot
  Created: agent.py
  Created: README.md
  Created: .env.example

Deploying to Agentverse...
  Agent Address: agent1q...
  Status: compiled

Opening Claude Code...

`agentlaunch create`

Interactive agent creation with a 6-step value-building workflow. Launches Claude Code to guide you through building, deploying, and tokenizing an agent.

agentlaunch create [options]

Flags:

Flag	Type	Default	Description
`--name <name>`	string	prompted	Agent name
`--ticker <ticker>`	string	auto-generated	Token ticker (e.g. MYAG)
`--template <template>`	string	`custom`	Template: `swarm-starter`, `custom`, `research`, `trading-bot`, `data-analyzer`, `price-monitor`, `gifter`
`--description <desc>`	string	`""`	Token description (max 500 chars)
`--chain <chainId>`	string	`97`	Chain: 97 (BSC Testnet) or 56 (BSC Mainnet)
`--deploy`	boolean	false	Deploy to Agentverse after scaffolding
`--tokenize`	boolean	false	Create token record after deploy
`--mode <mode>`	string	`single`	Build mode: `quick` (single), `swarm` (multi-agent)
`--preset <preset>`	string	--	Preset: `writer`, `social`, `community`, `analytics`, `outreach`, `ads`, `strategy`
`--json`	boolean	false	Machine-readable JSON output

Auto-Ticker Logic

If --ticker is not provided, a ticker is auto-generated from the agent name:

Name	Generated Ticker	Rule
`"Price Oracle"`	`PRICE`	First word is 3-6 chars, use it
`"DataFeed"`	`DATAFE`	Single word, first 6 chars
`"AI Research Assistant"`	`ARA`	Multiple words, use initials

6-Step Workflow

When create launches Claude Code, it guides you through:

Understand the Vision -- What problem does the agent solve? Who pays? What is the defensible moat?
Build the Agent Logic -- Read agent.py and propose real code changes using available packages (AI, Data, Web, Blockchain, Storage)
Deploy -- Use deploy_to_agentverse MCP tool or npx agentlaunch deploy
Make It Beautiful -- Write README.md, description, optimize with npx agentlaunch optimize
Tokenize -- Choose ticker, explain bonding curves, create token with handoff link
Share & Next Steps -- Provide links (Agentverse page, trade page, handoff link), suggest next actions

Mode Behavior

Mode	Behavior
`quick` / `single`	Single agent, no preset selection
`swarm`	Multi-agent, shows preset picker (writer, social, community, analytics, outreach, ads, strategy)

Swarm presets:

#	Preset	Description	Price
1	Writer	Content creation	0.01 FET/call
2	Social	Twitter/X posting	0.005 FET/call
3	Community	Telegram management	0.002 FET/call
4	Analytics	Engagement tracking	0.005 FET/call
5	Outreach	Partnership emails	0.01 FET/call
6	Ads	Ad campaigns	0.01 FET/call
7	Strategy	Campaign coordination	0.02 FET/call

`agentlaunch scaffold <name>`

Generate an agent project from a template in a new directory <name>.

Creates three files:

agent.py — Ready-to-run uagents code with security, caching, and revenue layers
README.md — Quick-start instructions
.env.example — Required environment variables

agentlaunch scaffold MyResearchBot
agentlaunch scaffold AlphaTrader --type trading
agentlaunch scaffold DataFeed --type data

Flags:

Flag	Description	Values	Default
`--type <type>`	Agent type — controls domain, rate limits, and business logic scaffold	`faucet`, `research`, `trading`, `data`	`research`

Agent types:

Type	Domain	Free requests/day	Rate limit
`faucet`	Token distribution	5	10/min
`research`	Q&A and data retrieval	10	20/min
`trading`	Market strategies	20	30/min
`data`	Structured data feeds	50	60/min

Example output:

Scaffolding Research agent: MyResearchBot
Directory: /home/user/my-research-bot
  Created: agent.py
  Created: README.md
  Created: .env.example

Done! Next steps:

  cd my-research-bot
  cp .env.example .env
  # Edit .env and agent.py
  agentlaunch deploy

`agentlaunch deploy`

Deploy an agent.py file to Agentverse hosted agents.

Steps performed:

Create agent record on Agentverse
Upload Python source code
Store AGENTVERSE_API_KEY and AGENTLAUNCH_API_KEY as Agentverse secrets
Start the agent
Poll until compiled (up to 60 seconds)

Requires: API key set via agentlaunch config set-key

# Deploy agent.py from the current directory
agentlaunch deploy

# Deploy a specific file with a custom name
agentlaunch deploy --file ./my_agent/agent.py --name "Alpha Research Bot"

Flags:

Flag	Description	Default
`--file <path>`	Path to the Python agent file	`./agent.py`
`--name <name>`	Display name on Agentverse (max 64 chars)	`"AgentLaunch Agent"`

The deploy command auto-detects README.md and agentlaunch.config.json next to the agent file and uploads them as metadata to improve the agent's Agentverse ranking.

Example output:

Deploying: /home/user/my-research-bot/agent.py
Agent name: My Research Bot
README:     auto-detected
Description: auto-detected

[1/5] Creating agent on Agentverse...
[2/5] Uploading code...
[3/5] Setting secrets...
[4/5] Starting agent...
[5/5] Waiting for compilation...

==================================================
DEPLOYMENT SUCCESSFUL
==================================================
Agent Address: agent1qf8xfhsc8hg4g5l0nhtj5hxxkyd46c64qxvpa3g3ha9rjmezq3s6xw9y7g
Wallet:        0x1234abcd...
Status:        Running & Compiled

--------------------------------------------------
AGENT OPTIMIZATION CHECKLIST
--------------------------------------------------
  [x] Chat Protocol
  [x] README
  [x] Short Description
  [ ] Avatar — Upload in Agentverse dashboard:
        https://agentverse.ai/agents/details/agent1qf8...
  [x] Active Status
  [ ] Handle — Set a custom @handle (max 20 chars):
        https://agentverse.ai/agents/details/agent1qf8...
  [ ] 3+ Interactions — Run the Response QA Agent 3+ times:
        https://agentverse.ai/agents/details/agent1qf8...

  Score: 4/7 ranking factors addressed

Next — tokenize your agent:
  agentlaunch tokenize --agent agent1qf8... --name "My Research Bot" --symbol MRB

`agentlaunch optimize <address>`

Update metadata on an already-deployed Agentverse agent to improve its ranking score.

Agentverse ranks agents by 7 factors. The deploy command handles 4 automatically (Chat Protocol, README, Short Description, Active Status). Use optimize to add or update metadata on agents that are already deployed.

Auto-detects README.md in the current directory if --readme is not specified.

# Auto-detect README.md in current directory
agentlaunch optimize agent1qf8xfhsc8hg4g5l0nhtj...

# Specify all fields
agentlaunch optimize agent1qf8xfhsc8hg4g5l0nhtj... \
  --readme ./README.md \
  --description "On-demand research reports powered by AI" \
  --avatar https://example.com/avatar.png

Flags:

Flag	Description	Default
`--readme <path>`	Path to README.md file	auto-detects `./README.md`
`--description <text>`	Short description (max 200 chars)	-
`--avatar <url>`	Public URL for avatar image	-
`--json`	Output only JSON	false

Example output:

Optimizing agent: agent1qf8xfhsc8hg4g5l0nhtj...
  Updating: README
  Updating: Short Description

Updated 2 field(s): readme, short_description

--------------------------------------------------
AGENT OPTIMIZATION CHECKLIST
--------------------------------------------------
  [x] Chat Protocol
  [x] README
  [x] Short Description
  [ ] Avatar — Upload in Agentverse dashboard:
        https://agentverse.ai/agents/details/agent1qf8...
  [x] Active Status
  [ ] Handle — Set a custom @handle (max 20 chars):
        https://agentverse.ai/agents/details/agent1qf8...
  [ ] 3+ Interactions — Run the Response QA Agent 3+ times:
        https://agentverse.ai/agents/details/agent1qf8...

  Score: 4/7 ranking factors addressed

`agentlaunch tokenize`

Create a pending token record on AgentLaunch and receive a handoff link for on-chain deployment.

The human who receives the handoff link opens it in a browser, connects their wallet, approves 120 FET, and deploys — all without the agent holding a private key.

Requires: API key set via agentlaunch config set-key

agentlaunch tokenize \
  --agent agent1qf8xfhsc8hg4g5l0nhtj5hxxkyd46c64qxvpa3g3ha9rjmezq3s6xw9y7g \
  --name "My Research Bot" \
  --symbol MRB \
  --description "Delivers on-demand research reports." \
  --chain 97

Flags:

Flag	Required	Description
`--agent <address>`	Yes	Agentverse agent address (must start with `agent1q`)
`--name <name>`	Yes	Token name (max 32 characters)
`--symbol <symbol>`	Yes	Ticker symbol (2-11 characters, auto-uppercased)
`--description <desc>`	No	Token description (max 500 characters)
`--image <url>`	No	URL to a token logo image
`--chain <chainId>`	No	`97` (BSC testnet) or `56` (BSC mainnet) — default: `97`

API endpoint: POST /agents/tokenize

Example output:

Tokenizing agent: agent1qf8xfhsc8hg4g5l0nhtj5hxxkyd46c64qxvpa3g3ha9rjmezq3s6xw9y7g
  Name:   My Research Bot
  Symbol: MRB
  Chain:  BSC testnet (97)

==================================================
TOKEN RECORD CREATED
==================================================
Token ID:   42
Status:     pending_deployment

Handoff link (share with a human to deploy on-chain):
  https://agent-launch.ai/deploy/42

Platform fee to deploy: 120 FET (read from contract at deploy time)
Trading fee: 2% -> 100% to protocol treasury

`agentlaunch list`

List tokens on AgentLaunch in a formatted table.

# Default: latest 10 tokens
agentlaunch list

# Top 20 by market cap, machine-readable JSON
agentlaunch list --limit 20 --sort market_cap --json

Flags:

Flag	Description	Default
`--limit <n>`	Number of tokens to show (1-100)	`10`
`--sort <by>`	Sort order: `trending`, `latest`, `market_cap`	`latest`
`--json`	Output raw JSON (machine-readable, suppresses table)	off

API endpoint: GET /tokens

Example output (table):

AgentLaunch Tokens  (sort: latest, limit: 10)

--------------------------------------------------------------
Name                  Symbol  Price (FET)   Progress  Status
--------------------------------------------------------------
Alpha Research Bot    ARB     0.000125 FET  33.3%     Active
My Trading Agent      MTA     0.000089 FET  12.1%     Active
DataFeed Pro          DFP     0.002341 FET  78.9%     Active
--------------------------------------------------------------

Showing 3 token(s). Use --limit to see more.

View on platform: https://agent-launch.ai

The platform URL comes from AGENT_LAUNCH_FRONTEND_URL in .env.

Example output (--json):

{
  "tokens": [
    {
      "id": 42,
      "name": "Alpha Research Bot",
      "symbol": "ARB",
      "price": "0.000125",
      "progress": 33.3,
      "status": "bonding"
    }
  ],
  "total": 3
}

`agentlaunch status <address>`

Fetch details for a specific token by its contract address.

agentlaunch status 0xF7e2F77f014a5ad3C121b1942968be33BA89e03c
agentlaunch status 0xF7e2F77f... --json

Flags:

Flag	Description	Default
`--json`	Output raw JSON (machine-readable)	off

API endpoint: GET /tokens/address/{address}

`agentlaunch buy <address>`

Execute a buy on a bonding curve token contract, or preview with --dry-run.

Requires: WALLET_PRIVATE_KEY env var (unless --dry-run)

agentlaunch buy <address> --amount <FET> [--slippage 5] [--chain 97] [--dry-run] [--json]

Flags:

Flag	Type	Required	Default	Description
`--amount <fet>`	string	Yes	--	Amount of FET to spend
`--slippage <percent>`	string	No	`5`	Slippage tolerance (0-100%)
`--chain <chainId>`	string	No	`97`	Chain: 97 (BSC Testnet), 56 (BSC Mainnet)
`--dry-run`	boolean	No	false	Preview trade without executing (no wallet needed)
`--json`	boolean	No	false	Machine-readable JSON output

API endpoint (dry-run): GET /tokens/calculate-buy

Example output (dry-run):

==================================================
BUY PREVIEW (dry run)
==================================================
Token:          0xF7e2F77f014a5ad3C121b1942968be33BA89e03c
Chain:          BSC Testnet
FET to spend:   10 FET
Tokens to receive: 125000.50
Price per token: 0.000080 FET
Price impact:   0.5%
Protocol fee:   0.20 FET (2% to treasury)
Net FET spent:  9.80 FET
Slippage:       5%
==================================================

Re-run without --dry-run to execute the trade.

Example output (executed):

==================================================
BUY EXECUTED
==================================================
Token:          0xF7e2F77f014a5ad3C121b1942968be33BA89e03c
Chain:          BSC Testnet
Tx Hash:        0xabc123...
Block:          12345678
FET spent:      10 FET
Tokens received: 125000.50
Protocol fee:   0.20 FET (2% to treasury)
Price impact:   0.5%
Approval Tx:    0xdef456...
==================================================

`agentlaunch sell <address>`

Execute a sell on a bonding curve token contract, or preview with --dry-run.

Requires: WALLET_PRIVATE_KEY env var (unless --dry-run)

agentlaunch sell <address> --amount <tokens> [--chain 97] [--dry-run] [--json]

Flags:

Flag	Type	Required	Default	Description
`--amount <tokens>`	string	Yes	--	Amount of tokens to sell
`--chain <chainId>`	string	No	`97`	Chain: 97 (BSC Testnet), 56 (BSC Mainnet)
`--dry-run`	boolean	No	false	Preview trade without executing (no wallet needed)
`--json`	boolean	No	false	Machine-readable JSON output

API endpoint (dry-run): GET /tokens/calculate-sell

Example output (dry-run):

==================================================
SELL PREVIEW (dry run)
==================================================
Token:          0xF7e2F77f014a5ad3C121b1942968be33BA89e03c
Chain:          BSC Testnet
Tokens to sell: 50000
FET to receive: 3.92 FET
Price per token: 0.000080 FET
Price impact:   0.3%
Protocol fee:   0.08 FET (2% to treasury)
Net FET received: 3.84 FET
==================================================

Re-run without --dry-run to execute the trade.

Example output (executed):

==================================================
SELL EXECUTED
==================================================
Token:          0xF7e2F77f014a5ad3C121b1942968be33BA89e03c
Chain:          BSC Testnet
Tx Hash:        0xabc123...
Block:          12345678
Tokens sold:    50000
FET received:   3.92 FET
Protocol fee:   0.08 FET (2% to treasury)
Price impact:   0.3%
==================================================

Validation rules (both buy and sell):

Address must start with 0x and be at least 10 chars
Amount must be a positive number
Chain must be 97 or 56
Slippage must be 0-100 (buy only)

Common Workflows

Full workflow: create -> optimize -> tokenize

# 1. One command to create and deploy
npx agentlaunch my-bot

# 2. (Optional) Customize agent.py in the new directory
cd my-bot
# Edit agent.py with your business logic

# 3. (Optional) Update metadata for better ranking
npx agentlaunch optimize agent1q... --description "AI research reports on demand"

# 4. Tokenize (use agent address from deploy output)
npx agentlaunch tokenize \
  --agent agent1q... \
  --name "My Bot" \
  --symbol MBOT \
  --chain 97

# 5. Share the handoff link with a human to deploy on-chain

Full workflow: scaffold -> deploy -> tokenize

# 1. Configure API key once
agentlaunch config set-key av-xxxxxxxxxxxxxxxx

# 2. Create a new agent project
agentlaunch scaffold MyBot --type research
cd my-bot

# 3. Configure environment
cp .env.example .env
# Edit .env: set AGENTVERSE_API_KEY and any other variables

# 4. Customize agent.py with your business logic
# Edit MyBotBusiness.handle() in agent.py

# 5. Deploy to Agentverse
agentlaunch deploy --name "My Bot"

# 6. Tokenize (use agent address from deploy output)
agentlaunch tokenize \
  --agent agent1q... \
  --name "My Bot" \
  --symbol MBOT \
  --chain 97

# 7. Share the handoff link with a human to deploy on-chain

Monitor tokens in a script (JSON output)

# Get top 5 tokens by market cap, parse with jq
agentlaunch list --limit 5 --sort market_cap --json | jq '.tokens[].name'

# Save token list to a file
agentlaunch list --limit 100 --json > tokens.json

On-chain trading

# Preview a buy (no wallet needed)
agentlaunch buy 0xF7e2F77f... --amount 10 --dry-run

# Execute a buy (requires WALLET_PRIVATE_KEY env var)
export WALLET_PRIVATE_KEY=0xabc123...
agentlaunch buy 0xF7e2F77f... --amount 10 --slippage 5

# Preview a sell
agentlaunch sell 0xF7e2F77f... --amount 50000 --dry-run

# Execute a sell
agentlaunch sell 0xF7e2F77f... --amount 50000

Using production (default)

# Production is the default — configured via AGENT_LAUNCH_API_URL in .env
agentlaunch tokenize --agent agent1q... --name "Test Token" --symbol TEST --chain 97

Switching to dev environment

# Option 1: Environment variable
export AGENT_LAUNCH_ENV=dev
agentlaunch list

# Option 2: CLI config
agentlaunch config set-url https://launchpad-backend-dev-1056182620041.us-central1.run.app
agentlaunch tokenize --agent agent1q... --name "Test Token" --symbol TEST --chain 97

# Reset to production
agentlaunch config set-url https://agent-launch.ai/api

API Endpoints Used

These are the correct API paths used by the CLI (base URL: https://agent-launch.ai/api):

Command	Method	Path
`list`	`GET`	`/tokens`
`status`	`GET`	`/tokens/address/{address}`
`tokenize`	`POST`	`/agents/tokenize`
`buy --dry-run`	`GET`	`/tokens/calculate-buy`
`sell --dry-run`	`GET`	`/tokens/calculate-sell`
`auth wallet`	`POST`	`accounts.fetch.ai/v1/auth/login/wallet/*`
`auth status`	`GET`	`agentverse.ai/v1/hosting/agents`

Exit Codes

Code	Meaning
`0`	Success
`1`	Error (validation failure, API error, missing config, etc.)

All error messages are written to stderr. With --json flag, errors are written as {"error": "..."} to stdout.

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CLI Reference — `agentlaunch` v1.2.9

Configuration

`agentlaunch config set-key <apiKey>`

`agentlaunch config show`

`agentlaunch config set-url <url>`

Environment URL Configuration

Authentication

`agentlaunch auth wallet`

`agentlaunch auth status`

`agentlaunch [name]` — default command

`agentlaunch create`

Auto-Ticker Logic

6-Step Workflow

Mode Behavior

`agentlaunch scaffold <name>`

`agentlaunch deploy`

`agentlaunch optimize <address>`

`agentlaunch tokenize`

`agentlaunch list`

`agentlaunch status <address>`

`agentlaunch buy <address>`

`agentlaunch sell <address>`

Common Workflows

Full workflow: create -> optimize -> tokenize

Full workflow: scaffold -> deploy -> tokenize

Monitor tokens in a script (JSON output)

On-chain trading

Using production (default)

Switching to dev environment

API Endpoints Used

Exit Codes

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CLI Reference — agentlaunch v1.2.9

Configuration

agentlaunch config set-key <apiKey>

agentlaunch config show

agentlaunch config set-url <url>

Environment URL Configuration

Authentication

agentlaunch auth wallet

agentlaunch auth status

agentlaunch [name] — default command

agentlaunch create

Auto-Ticker Logic

6-Step Workflow

Mode Behavior

agentlaunch scaffold <name>

agentlaunch deploy

agentlaunch optimize <address>

agentlaunch tokenize

agentlaunch list

agentlaunch status <address>

agentlaunch buy <address>

agentlaunch sell <address>

Common Workflows

Full workflow: create -> optimize -> tokenize

Full workflow: scaffold -> deploy -> tokenize

Monitor tokens in a script (JSON output)

On-chain trading

Using production (default)

Switching to dev environment

API Endpoints Used

Exit Codes

CLI Reference — `agentlaunch` v1.2.9

`agentlaunch config set-key <apiKey>`

`agentlaunch config show`

`agentlaunch config set-url <url>`

`agentlaunch auth wallet`

`agentlaunch auth status`

`agentlaunch [name]` — default command

`agentlaunch create`

`agentlaunch scaffold <name>`

`agentlaunch deploy`

`agentlaunch optimize <address>`

`agentlaunch tokenize`

`agentlaunch list`

`agentlaunch status <address>`

`agentlaunch buy <address>`

`agentlaunch sell <address>`