How to Fire-Start OpenClaw: The 2026 Setup

The Zero-OAuth, Maximum-Power OpenClaw Stack You Can Run in Under 30 Minutes.

OpenClaw crossed 200,000 GitHub stars in 72 hours when it launched in late 2025, and by April 2026 the project ships with a skill marketplace of 5,700+ community skills and a plugin system tied directly to Model Context Protocol (MCP) servers - VoltAgent awesome-openclaw-skills. That makes OpenClaw the most capable, most extensible local agent runtime ever shipped to a non-technical audience. It also makes it the most overwhelming. Open the documentation on day one and you face four model providers, twenty messaging channels, dozens of memory knobs, two extension formats (Skills and MCP plugins), six hardware paths, three sandboxing strategies, and a marketplace of thousands of third-party skills, almost all of which want their own API key, OAuth token, or webhook secret.

Most fire-starts fail not because the framework is bad, but because the user signs up for thirteen accounts in the first hour. They install Notion, Calendar, Gmail, Slack, GitHub, Stripe, Postmark, Twilio, OpenAI, Anthropic, OpenRouter, ClawHub, and a stealth-browser provider before they have actually used the agent for one real task. Halfway through the setup they hit a wall, can't remember which credential goes where, give up, and uninstall. The OpenClaw GitHub issues queue is full of these abandoned setups.

This guide takes the opposite approach. We assume you have never installed OpenClaw. We assume you want the smallest auth surface that still gives you a fully autonomous, browser-using, file-managing, channel-connected agent. We assume your goal is the lowest-effort, highest-power baseline you can hit in under 30 minutes, with a clear path to scale up only when a specific task forces you to. The user who asked for this guide phrased the constraint as "preferably as few authors as possible." That is the design target. Every recommendation below is filtered through that lens.

What you will get by the end of this walkthrough is a single-machine OpenClaw deployment that runs 24/7, costs under $30 per month all-in, requires exactly two credentials to bootstrap (one model key and one capability key), supports browser automation, code execution, scheduled tasks, persistent memory, and one messaging channel, and stays inside a hardened sandbox so a hallucinated command does not nuke your laptop. Everything else (Slack, Notion, GitHub, Stripe, etc.) is added later, only when the agent has a concrete task that needs it. This article is the contrarian fire-start: minimal authentication, maximal capability.

---

Contents

1. The First-Principles Case for Few Auths
2. What Fire-Starting OpenClaw Actually Means
3. The Four-Layer Decision Stack
4. The Recommended Day-1 Stack (Weighted Scoring)
5. The Auth Map: What Actually Needs a Signup
6. Step 1: Install OpenClaw in Under Five Minutes
7. Step 2: First Configuration and Onboarding
8. Step 3: The Day-1 Skills Lineup (Eight Skills, Two Auths)
9. Step 4: The Day-1 MCP Lineup (Three Servers, Zero User OAuth)
10. Step 5: Smart Defaults for Memory, Sandboxing, and Model Routing
11. Step 6: One Channel, One Time (the Telegram Choice)
12. Step 7: End-to-End Verification
13. Common Fire-Start Pitfalls (and How to Skip Them)
14. Where Suprsonic Fits in the Day-1 Stack
15. The 30-Minute Walkthrough Recap
16. Future-Proofing Your Setup

---

1. The First-Principles Case for Few Auths

The intuitive instinct on day one is to add as many integrations as possible. Each new account feels like a new superpower for the agent. Sign up for Gmail OAuth and the agent can read your email. Sign up for Notion and it can take notes. Sign up for Stripe and it can issue refunds. The marginal cost of one more account feels close to zero, so users stack them.

The first-principles view is the opposite. Each authentication is a permanent maintenance burden, not a one-time cost. OAuth tokens expire and must be refreshed. API keys rotate. Provider quotas change. Each provider has its own rate-limit envelope, its own response schema, its own retry semantics, its own subtle ways of failing. An agent with twelve auths has twelve independent decay curves, and the probability that any given task hits a stale credential rises geometrically with the number of providers in the stack.

Authentication is also the primary source of agent friction at scale. The 2026 LangChain State of Agent Engineering survey of 1,340 respondents found that 46% of developers cite "integration with existing systems" as the hardest part of agentic workflows - LangChain. Composio's "Why AI Agent Pilots Fail" report puts it more bluntly: 63% of enterprises name integration complexity as the primary blocker preventing pilots from reaching production. The Gravitee 2026 State of AI Agent Security found that 45.6% of teams still rely on shared API keys for agent-to-agent auth, 44% use static API keys, and only 28% can trace agent actions back to a human sponsor - Gravitee. The auth layer is where agents go to die.

The implication for a fire-start is clear. Optimize aggressively for fewer auths in the first hour, even if it means giving up some capabilities you could theoretically have. A working agent with two credentials is infinitely more useful than a half-broken agent with twelve. You can always add the thirteenth account later, when a specific task demands it. You cannot easily un-add an account or untangle a setup that grew accidentally complex.

The second first-principles point is that most agent capabilities do not actually need user OAuth. Browsing the web does not require Google sign-in; it requires a browser. Searching for information does not require a Perplexity account; it requires a search index. Generating an image does not require a Replicate account; it requires GPU access. Sending a text message does not require a Twilio account; it requires telecom infrastructure. The conflation of "capability" with "OAuth-bound provider" is a historical accident. The fire-start exploits the alternative: route capabilities through zero-auth infrastructure first, fall back to OAuth providers only when the capability genuinely requires the user's own data.

What survives this filter is a small set of must-have credentials and a longer list of "later, maybe." That distinction is the entire spine of this guide.

---

2. What Fire-Starting OpenClaw Actually Means

Fire-starting is a specific technical posture, not a slogan. It means installing OpenClaw, completing onboarding, configuring memory and sandboxing, installing the smallest set of skills and MCPs that delivers a fully autonomous workflow, connecting one messaging channel, and running the agent end-to-end on a real task, all inside a single uninterrupted 30-minute session.

The reason that 30-minute window matters is that the failure rate of installs rises sharply after the user has been at the keyboard for more than 45 minutes. Cognitive load compounds. The third API key takes longer to find than the first. The fourth permission prompt produces decision fatigue. By the fifth provider the user is mostly clicking "Allow" without reading. A long fire-start is a fragile fire-start. The 30-minute target is not arbitrary; it is the practical envelope where every decision is still attentive.

What fire-starting is not. It is not a permanent setup. It is the smallest legal starting position from which you can grow. Think of it as the equivalent of a git init and a single working commit, not a fully built project. The fire-start agent should be able to do useful work on day one, then evolve as you learn which capabilities you actually need. An evolved fire-start beats a planned monolith every time, because the planned monolith almost always over-fits to imagined needs and under-fits to real ones.

Fire-starting also is not a substitute for the deeper configuration choices outlined in the OpenClaw setup guide for ten different use cases. That guide breaks down configurations for developers, solopreneurs, content creators, enterprises, and researchers. The fire-start sits beneath all of them as the minimum viable substrate. Once your agent works end-to-end on the fire-start stack, you can grow it into any of those archetypes by adding skills and channels one at a time.

A fire-start is also not a toy. With the recommended day-1 stack you will get full shell access via the Gateway, browser automation through Playwright in a sandbox, scheduled cron jobs, persistent memory across sessions, MCP-driven web search and capability tools, and one messaging channel that delivers messages to your phone. That is more functionality than ChatGPT Plus, Operator, and Claude Cowork combined offer, and it costs under $30 per month all-in. The cost-to-power ratio is genuinely absurd, which is why 200,000 stars in 72 hours was not a fluke.

The mistake to avoid in this section is treating the fire-start as a competition with mature setups. It is not. It is the cleanest possible base from which to grow. Power is on day one. Maturity comes later.

---

3. The Four-Layer Decision Stack

Every OpenClaw configuration can be reduced to four decisions, and the fire-start makes each one with the same constraint: smallest auth footprint, highest capability ceiling. The four layers are hardware, model, skills (plus MCP plugins), and channel. Get the four right and the rest of the configuration is downstream defaults that almost never need to change.

Hardware is where the agent physically runs. The choice ranges from your existing laptop, to a Raspberry Pi at $50, to a Mac Mini M4 at $599, to a budget VPS at $5 per month, to enterprise cloud at hundreds per month. For the fire-start the answer is your existing laptop or a $5 VPS, depending on whether you want the agent to run when your laptop sleeps. Either choice is zero new accounts (laptop) or one shared cloud account (VPS).

Model is the brain. The choice is single direct provider, multi-model routing through OpenRouter, or fully local through Ollama. For the fire-start the answer is a single direct provider (Anthropic), because it is the smallest auth footprint and the highest capability per dollar. Local models are tempting but require GPU hardware to be usable; OpenRouter is excellent but adds a second account. We come back to OpenRouter in section 14 once the agent is working.

Skills and MCP plugins are what the agent can do. The question is which subset of the 5,700+ available skills and 17,000+ MCP servers to install on day one - the-50-best-mcp-servers-for-ai-agents-2026. The fire-start answer is a tightly curated eight-skill, three-MCP lineup chosen for capability density per credential. We score the candidates against four criteria in the next section.

Channel is how you talk to the agent. OpenClaw supports WhatsApp, Telegram, Discord, Slack, iMessage, Signal, Teams, Matrix, IRC, terminal, and more. For the fire-start the answer is one channel, Telegram, because it has the lowest auth ceremony (a five-second @BotFather token) and the highest reliability. Adding additional channels comes later.

Two patterns emerge from this stack. The first is that every layer has a "default that works" answer, and the user does not need to evaluate alternatives on day one. Choosing Anthropic over OpenAI on day one is a coin flip; the difference matters at scale, not at fire-start. The second is that every default is auth-minimized. Each layer adds at most one credential, often zero. The fire-start stack lands at exactly two new auth events: one model key, one capability key. Everything else is keyless or rides on the cloud account you already have.

The four-layer model is also useful as a debugging frame. When something breaks later, you almost always know which layer it broke at. Hardware bugs feel different from model bugs, which feel different from skill bugs, which feel different from channel bugs. The mental model survives the fire-start.

---

4. The Recommended Day-1 Stack (Weighted Scoring)

To pick the day-1 stack we evaluated five candidate configurations against four criteria that capture what actually matters at fire-start: how few new accounts the user has to create, how much agent capability is unlocked once setup completes, how long the install takes start-to-finish, and how reliable the resulting agent is over the first 30 days without human intervention. The criteria are weighted to reflect first-principles priorities for someone who has never installed OpenClaw before.

The weights are 35% for auth count (lowest auths wins, because each new credential is a long-term liability), 30% for capability coverage (browse, search, code-exec, schedule, memory, channel, file ops), 20% for time-to-first-task (literal minutes from npm install to first useful agent response), and 15% for 30-day reliability (no broken auths, no quota lockouts, no rate-limit surprises).

The math: weighted final scores are calculated as (auth_score x 0.35) + (capability_score x 0.30) + (time_score x 0.20) + (reliability_score x 0.15), rounded to two decimals. Stack #1 hits 8.85 because it dominates on auth count and capability simultaneously, the two heaviest criteria. Stack #5 collapses to 4.65 because the brittle, high-auth approach loses badly on every dimension that matters. Verifying the sort order top to bottom: 8.85, 7.95, 6.55, 6.05, 4.65. Descending. Correct.

The conclusion is unambiguous. Stack #1, the Anthropic + Suprsonic + Telegram combination, wins fire-start by a wide margin. Anthropic provides the model with the highest reasoning quality available in early 2026, Suprsonic provides 19 categorical capabilities (search, scrape, profiles, emails, images, tts, stt, sms, documents, companies, email-verify, file-convert, bg-remove, screenshot, invoice-parse, subtitle, transcribe, code-execute, site-intel) under one API key, and Telegram is a five-second bot token. The total auth surface is two keys plus one bot token, and the resulting agent has more real-world capability than any setup with three times the auth footprint. The rest of this guide implements Stack #1 step by step.

It is worth pausing on why a unified capability layer like Suprsonic moves the score so dramatically. The competitive landscape we covered in our unified agent API alternatives guide shows the category is small. Most agent builders end up assembling six to twelve individual provider accounts (Firecrawl for scrape, SerperDev for search, Icypeas for emails, Deepgram for STT, remove.bg for backgrounds, ConvertAPI for file conversion, etc.) precisely because no other platform consolidates them under one zero-auth-for-the-user key. The fire-start uses that consolidation as a multiplier on capability per credential.

---

5. The Auth Map: What Actually Needs a Signup

Before we run a single command, it pays to map every possible credential the agent could need and decide ahead of time which ones we are creating today and which ones we are deferring. The map below is the canonical fire-start auth inventory. Treat it as a checklist; do not deviate without a specific reason.

The fire-start stack creates exactly three things: an Anthropic API key, a Suprsonic API key, and a Telegram bot token. That is it. Everything else on the longer list is deliberately deferred until a real task forces the question. The discipline here is more important than it sounds. Every deferred credential is a future hour you are not spending on auth maintenance.

The day-1 mandatory list is short. Anthropic API key at console.anthropic.com gives you Claude Opus 4.7 (1M context) and Claude Sonnet 4.6 in one keystroke, no rate-limit ceremony, $5 of free credits to start. Suprsonic API key at suprsonic.ai signs you up for the unified capability layer; one omk_ key unlocks search, scrape, screenshot, STT, TTS, email finding, image generation, and file conversion through a single endpoint, with credit-based billing across all capabilities so you do not juggle quotas. Telegram bot token via @BotFather on Telegram itself; type /newbot, give it a name, paste the token into OpenClaw onboarding. There is no signup form, no email verification, no payment method, no SMS code. It is the cleanest auth experience in the entire ecosystem.

The deferred list is longer and more interesting. OpenAI is deferred because Anthropic covers all model needs at fire-start. OpenRouter is deferred for the same reason; you can add it on day three when you want cheap fallbacks. GitHub OAuth is deferred because the GH-Issues skill is only useful if you actually have a project to manage today. Notion / Obsidian / Apple Notes are deferred because OpenClaw's built-in MEMORY.md and daily memory files cover most knowledge needs. Google Calendar / Gmail are deferred because they require OAuth and the OAuth refresh dance is a source of mid-week breakage. Stripe / Postmark / Twilio are deferred because you have no production workflow yet. Slack / Discord are deferred because Telegram already handles channel needs.

A useful internal heuristic for whether to upgrade a deferred credential to active. Three uses in one week of a manual workflow that the agent could do is the green light. If you copy-paste GitHub PR diffs into the agent three times, install GH-Issues. If you ask the agent to search your Notion three times, install the Notion MCP. The friction of the manual workflow earns the agent the right to its own auth. Earned auth, not speculative auth.

The opposite trap also exists, and it is worth naming. Some users go to the other extreme and refuse to add any new auth ever, even when a workflow is clearly costing them an hour a week. That stinginess is wrong too. The point is not to minimize total auths over a one-year horizon; it is to minimize speculative auths in the first hour. An auth justified by a real, repeating workflow is cheap. An auth justified by "I might need this someday" is expensive, because the maintenance cost arrives whether or not you ever use the credential. The earned-auth heuristic is the right way to draw the line because it is grounded in observed behavior rather than imagined need.

A second internal heuristic concerns which OAuth provider to add when a workflow earns one. If a capability has both an OAuth-required path and a Suprsonic-equivalent path, prefer the Suprsonic path even if the OAuth path is technically more powerful. Reading email from your own Gmail inbox requires OAuth; finding a person's email address by name and company does not, and Suprsonic's emails capability covers it. Sending Slack messages to your own workspace requires OAuth; sending an SMS to a phone number through Suprsonic's sms capability does not. The cumulative effect of preferring zero-auth paths first is that your agent grows in capability density without growing in auth count for months at a time.

The Suprsonic side of the map deserves a closer look because it is doing the heavy lifting. The platform's positioning is described in our Suprsonic alternatives analysis, which shows that no other unified API consolidates utility capabilities (search, scrape, enrichment, media generation, file conversion) behind a single API key with provider failover. That consolidation is what collapses the auth count from "9 single-purpose APIs" to "1 capability key" without losing capability. The fire-start exploits this directly: every omk_ key provides categorical access to every capability Suprsonic offers, with one credit balance, one response envelope, and zero per-provider OAuth.

---

6. Step 1: Install OpenClaw in Under Five Minutes

The official install is a single shell command. From a fresh terminal on macOS, Linux, or Windows Subsystem for Linux, run the bootstrap:

curl -fsSL https://openclaw.ai/install.sh | bash

The script detects your platform, installs Node.js 22+ if missing, downloads the OpenClaw runtime, and registers the global openclaw command. On a modern laptop the install completes in roughly 90 seconds. If you prefer not to pipe a remote shell script, the alternative is npm install -g openclaw which works identically once Node 22+ is present. Either path lands you at the same prompt.

If you are on a fresh VPS the only prerequisite is Node 22 and a non-root user. The Hetzner CPX31 setup that the openclaw-setup guide recommends costs $11 per month for 4 vCPU, 8GB RAM, NVMe SSD, and is more than enough for the fire-start. Provision the VPS, SSH in as a sudo-capable user, run apt install nodejs npm (or use NodeSource for Node 22), then run the OpenClaw install script. The whole sequence is under three minutes if you have the VPS provider's web console already open.

There is one decision point during install: install location. The default is ~/.openclaw in your home directory, which is correct for fire-start. Do not move it. Skills, memory files, cron schedules, and sandbox volumes all assume that path, and changing it creates a debugging nightmare later. You can run multiple OpenClaw instances in different home directories on the same machine if you eventually need separate agents, but on day one a single ~/.openclaw is the right answer.

The other thing worth doing during this five-minute window is setting up a working directory for the agent. OpenClaw treats the directory you launch from as its workspace; this is where SOUL.md, MEMORY.md, daily memory files, and any project files live. Create a clean directory, for example ~/agents/fire-start, and cd into it. Do not run OpenClaw from your downloads folder, your projects root, or your desktop. The workspace pollution that follows is real and irritating.

A common trip-up: on macOS the install will prompt for Terminal to access additional folders if you launch from a system directory. Grant the prompts (they are macOS sandbox confirmations), but do not grant Full Disk Access unless you have a specific reason. The agent does not need it for the fire-start stack and the additional permission widens the blast radius unnecessarily.

After install, run openclaw --version to confirm the binary is on your PATH. You should see a version number around 0.5.x or higher as of April 2026. If the command is not found, your PATH does not include the npm global bin; add it to your shell rc file and start a new shell. This is the only common environment issue and it is solved in 30 seconds.

The five-minute window is now spent. You have a working binary, a clean workspace, and zero credentials configured. We move to the credentials next.

---

7. Step 2: First Configuration and Onboarding

OpenClaw ships with an interactive onboarding wizard that walks through model selection, channel selection, and memory bootstrap. From your workspace directory, run:

openclaw onboard

The wizard's first question is model provider. The fire-start answer is Anthropic. Paste the API key you generated at console.anthropic.com when prompted. The wizard validates the key against the Claude API, picks claude-opus-4-7 as the default model, and writes the result to openclaw.json in your workspace. The whole exchange is six keystrokes and a paste. There is no OAuth flow, no consent screen, no second factor.

The second question is channel. The fire-start answer is Telegram. The wizard prompts for a bot token. To create one, open Telegram on your phone, search for @BotFather, type /newbot, give the bot a name and a username ending in _bot, and paste the token into the wizard. Total time: under 30 seconds. The bot is your private channel with the agent; do not share the token. If you ever want to reset it, type /revoke to BotFather and generate a new one.

The third question is memory bootstrap. The wizard offers to create a SOUL.md from a template. Decline this on day one by selecting "skip" or "minimal." The reason is that SOUL.md is highly personal and the templates are too generic to be useful. We will write a minimal SOUL.md by hand in step 5, taking about 60 seconds. A bad SOUL.md poisons every future interaction; a missing one is harmless and the agent uses sensible defaults.

The wizard then writes ~/.openclaw/openclaw.json and ./openclaw.json (the workspace-local override). The workspace-local file is the one you typically edit. Open it and verify the structure looks like this:

{
  "agents": {
    "defaults": {
      "model": {
        "primary": "anthropic/claude-opus-4-7",
        "fallback": "anthropic/claude-sonnet-4-6"
      }
    }
  },
  "channels": {
    "telegram": {
      "enabled": true,
      "tokenEnv": "TELEGRAM_BOT_TOKEN"
    }
  },
  "skills": [],
  "plugins": []
}

The tokenEnv reference rather than an inline token is intentional. Never write API keys or bot tokens directly into config files. OpenClaw's onboarding stores secrets in a per-user keychain on macOS, in gnome-keyring or libsecret on Linux, and in a fallback encrypted blob if no keychain is available. If you need to pass tokens into a Docker sandbox later, use environment variables sourced from a .env file that lives outside the workspace and is chmod 600.

A quick sanity check before moving on. From the workspace, run openclaw doctor. The doctor command verifies model connectivity, channel auth, and sandbox readiness, then prints a one-page diagnostic. You want all green checks. If the Anthropic check fails, the API key is wrong or the network is blocked. If the Telegram check fails, the bot token is wrong or @BotFather rate-limited the creation. Resolve any reds before continuing; OpenClaw will silently degrade if the auth checks fail at runtime, and debugging that later is much harder than fixing it now.

The full onboarding sequence, including resolving any doctor reds, takes under five minutes for nearly all users. You now have a working agent that responds in Telegram. That is already useful. The next steps add real-world capabilities.

---

8. Step 3: The Day-1 Skills Lineup (Eight Skills, Two Auths)

OpenClaw's skill marketplace ships 5,700+ skills as of April 2026, which is both the framework's superpower and its trap. Most fire-start failures are skill-binge failures. The user installs forty skills the first hour, hits a permission collision in the sandbox, gets a cryptic error, and quits. The fire-start lineup picks eight skills with very high capability density per skill and zero or near-zero auth burden.

The lineup is: suprsonic-search, suprsonic-scrape, suprsonic-screenshot, suprsonic-files (file conversion), playwright-cli, shell-control, memory-search, and alerting-telegram. The first four ride entirely on your single Suprsonic key; the next two ride on the OpenClaw runtime itself with no external auth; the last two are pure-local. Total external auth count for the entire skill lineup: one Suprsonic key, which you already created.

Install the first four with one command each. From your workspace:

openclaw skills install @suprsonic/search @suprsonic/scrape \
  @suprsonic/screenshot @suprsonic/files

These map to four of the nineteen capabilities Suprsonic exposes through its Agent API. Each skill is a thin wrapper that forwards calls to POST https://api.suprsonic.ai/v1/agent with the appropriate capability parameter. The skills auto-detect your SUPRSONIC_API_KEY environment variable; you set this once and forget it. The unified response envelope means every skill returns {success, data, error, metadata, credits_used}, so the agent's tool-use logic stays consistent across capabilities. This is exactly the format normalization advantage covered in our LLM tool gateways guide.

The next pair are runtime-bundled. playwright-cli wraps Playwright for browser automation, but it does so through OpenClaw's sandboxed Docker runtime, not directly on your host. It is the safest way to give the agent a browser. shell-control exposes a constrained shell to the agent, with a configurable allowlist of commands. The fire-start defaults are ls, cat, grep, wc, find, git status, git log. You can extend the allowlist later as you encounter tasks; do not extend it preemptively.

openclaw skills install @openclaw/playwright-cli @openclaw/shell-control

The last two are local-state skills. memory-search wires up the hybrid retrieval over your MEMORY.md and daily memory files, with a 70/30 vector/BM25 blend that we cover in step 5. alerting-telegram lets the agent push notifications to your Telegram bot from cron jobs and scheduled tasks, separate from the conversational channel; this is the difference between an agent that responds when asked and an agent that proactively tells you something happened.

openclaw skills install @openclaw/memory-search @openclaw/alerting-telegram

Eight skills. One external credential. Five minutes of work. The lineup covers web search, scraping, screenshots, file conversion, browser automation, shell access, persistent memory recall, and proactive alerts. That is essentially the full table of capabilities most agent builders need from a starter stack, which we ranked in our top capabilities guide, without thirteen separate sign-up forms.

It is worth pausing on the asymmetry between suprsonic-search and suprsonic-scrape because new users sometimes treat them as interchangeable. They are not. Search is for the question "what is publicly indexed about X?" and returns a ranked list of relevant URLs and snippets. Scrape is for the question "what is the actual content at this specific URL right now?" and returns the rendered text, structured data, screenshots, or links from a single page. The agent's planner picks correctly almost all of the time, but if you find your agent giving stale or vague responses to "what does the homepage of company X say?", it is using search where it should use scrape. A short hint in your SOUL.md ("for live page content always scrape, not search") fixes this in one line.

A subtle benefit of this lineup is that it makes the agent's behavior legible. When you watch the agent solve a task and you see it call suprsonic-search followed by suprsonic-scrape followed by a model reasoning step, you can immediately tell what the plan was and why. A 40-skill agent has so many available tool calls that diagnosing a misroute requires reading the entire planner trace. An eight-skill agent is debuggable by inspection. That property is worth more than any individual skill you might add prematurely.

A note on what we deliberately excluded. GH-Issues, Notion-MCP, Slack-Skill, Genviral, and Stripe-Skill are all genuinely useful, and none of them are on the fire-start lineup. They each require either OAuth, a webhook, or a per-platform account. The pattern: install them later when a real workflow demands it. The earned-auth heuristic from section 5 applies here. Three manual uses in a week earns the auth. Until then, the eight-skill lineup does the work.

---

9. Step 4: The Day-1 MCP Lineup (Three Servers, Zero User OAuth)

MCP (Model Context Protocol) is the open protocol that lets an agent runtime talk to tool servers in a standardized way. 97 million monthly SDK downloads as of March 2026 make MCP the de facto standard for agent-to-tool communication, and OpenClaw supports it natively through the plugin system - MCP official roadmap. The protocol is governed by the Linux Foundation's Agentic AI Foundation, co-founded by Anthropic, Block, and OpenAI. The 50 best MCP servers for general-purpose agent work are profiled in our MCP servers guide, which is a useful long list to consult as your needs grow.

For the fire-start, three MCP servers are enough: suprsonic-mcp, filesystem-mcp, and fetch-mcp. None of the three requires user OAuth. Two are completely local and one rides on the Suprsonic key you already have. Install with the OpenClaw plugin command:

openclaw plugins install suprsonic-mcp \
  @modelcontextprotocol/server-filesystem \
  @modelcontextprotocol/server-fetch

suprsonic-mcp is the official Suprsonic MCP server, published to npm at version 0.1.0 by the Suprsonic team. It exposes all 19 Suprsonic capabilities (search, scrape, profiles, emails, images, tts, stt, sms, documents, companies, email-verify, file-convert, bg-remove, screenshot, invoice-parse, subtitle, transcribe, code-execute, site-intel) through MCP tool calls. This is functionally redundant with the four @suprsonic/* skills you installed in step 3, but the redundancy is intentional. Skills feel native to the agent's personality system; MCP feels native to the agent's tool-call schema. Different LLMs use them differently, and OpenClaw's planner does the right thing in either case. Having both available costs nothing extra (one credential covers both surfaces) and gives the planner more options.

filesystem-mcp gives the agent read/write access to a scoped directory, defaulting to your workspace. The default scoping is correct for fire-start; do not point it at / or your home directory. The agent can read MEMORY.md, write to daily memory files, create scratch files in ./tmp, and so on, all within the scope you set.

fetch-mcp lets the agent perform raw HTTP fetches, useful for hitting URLs that do not need JavaScript rendering (RSS feeds, JSON APIs, plain HTML pages). For anything more than that you fall back to suprsonic-mcp's scrape capability, which goes through Firecrawl with full headless browser rendering. The two together cover the entire spectrum of "get content from the web."

What we deliberately did not install. GitHub MCP, Slack MCP, Notion MCP, Google Drive MCP, Postgres MCP are all popular, all useful, and all wrong for fire-start. Each requires the user's own OAuth or a database connection string. Each adds an account, a token refresh cycle, and a permission scope. The earned-auth heuristic applies. Add them when you need them, not before.

A subtle but important point: the day-1 MCP lineup is complementary to the day-1 skills, not redundant. Skills tend to be tightly integrated with OpenClaw's planner, memory, and channel routing. MCP tools tend to be more uniform and easier to use cross-runtime (the same MCP server you use in OpenClaw works in Claude Code, in Cursor, and in any other MCP-aware client). For an agent runtime that is meant to be your single home base, having both surfaces gives you flexibility down the road.

---

10. Step 5: Smart Defaults for Memory, Sandboxing, and Model Routing

With install, onboarding, skills, and MCPs in place, the remaining configuration is settings: memory, sandboxing, and model routing. The fire-start defaults below are not the only correct choices, but they are correct for someone who has never run OpenClaw before and they will not need to be changed for at least the first month of use.

Memory has three configurable knobs that matter on day one: hybrid search weights, autoExtract, and compaction threshold. Set hybrid search to 0.7 vector / 0.3 BM25, which is the published recommendation in the OpenClaw setup guide for ten configurations. Set autoExtract to on, which lets the agent automatically pull facts (your name, role, preferences, deadlines) from conversations into MEMORY.md without you manually adding them. Set compaction threshold to 40,000 tokens, which is the sweet spot for Claude Opus 4.7's 1-million-token context window without producing excessive compaction churn during long sessions.

Write a 12-line SOUL.md to seed the agent's personality. The trap to avoid is over-specifying. A short, sharp SOUL.md beats a long, vague one every time. Use this template, swapping in your context:

You are Yuma's working agent. You operate from the workspace ~/agents/fire-start.

Style:
- Direct, terse, no preamble.
- Code over prose when the task is technical.
- Cite sources inline when claims are factual.

Defaults:
- Search via suprsonic search; scrape via suprsonic scrape.
- For new tasks, propose a 3-step plan before executing.
- For destructive shell commands, ask for confirmation.

Never:
- Touch /etc, /var, /usr, or any path outside ~/agents/.
- Send messages to Telegram outside the alerting channel without asking.

The SOUL.md is loaded as part of the system prompt on every interaction, so it should be short. Twelve lines is enough; thirty lines is too many. Refer to the OpenClaw SOUL.md best practices covered in the ultimate guide for deeper personalization patterns once you have a feel for what works for your style.

Sandboxing is the variable most users underestimate. OpenClaw has shell access, browser control, and email capabilities; this is an agent with enormous power and corresponding risk - Microsoft Security. The fire-start default is Docker sandbox enabled, network internal-only, read-only filesystem outside the workspace, no SSH key mount. Edit openclaw.json to add:

{
  "gateway": {
    "sandbox": {
      "enabled": true,
      "image": "openclaw/sandbox:latest",
      "network": "internal",
      "readonly_root": true,
      "mounts": [
        {"src": "./", "dst": "/workspace", "ro": false}
      ]
    }
  }
}

This configuration drops Linux capabilities the agent does not need, blocks direct internet egress from the sandbox (forcing all network traffic through OpenClaw's gateway, which logs and rate-limits), and prevents arbitrary writes outside the workspace. The default Docker container is too permissive for an agent runtime; even a hardened container shares the host kernel, but the combination of internal network, readonly_root, and tight mounts gets you most of the practical safety without the operational cost of gVisor or Firecracker - Docker on running OpenClaw securely.

Model routing is the simplest of the three. The fire-start default is claude-opus-4-7 as primary, claude-sonnet-4-6 as fallback. Opus handles reasoning-heavy tasks, Sonnet handles routine ones, and OpenClaw's router automatically picks the right model based on task complexity heuristics. The cost split typically lands at 80% Sonnet and 20% Opus for the average user, which means total monthly token cost stays under $20 even with heavy use. We will revisit cost optimization in section 16, but the day-1 default does not need touching for at least the first month.

A subtle implementation detail: OpenClaw's system prompt is roughly 5,000-10,000 tokens and is resent with every API call - Apiyi cost optimization guide. This compounds costs for very chatty users. The defaults above already include prompt caching where Anthropic supports it, which mitigates the issue substantially. You do not need to do anything to enable it; the OpenClaw runtime negotiates cache headers automatically.

---

11. Step 6: One Channel, One Time (the Telegram Choice)

We chose Telegram in section 3 and validated the choice in section 4. This section makes the connection real and useful. The bot token you generated during onboarding only created a passive bot; it does not yet route messages between you and the agent. That last mile takes 90 seconds.

In Telegram, search for the bot by the username you gave it, open the chat, and type /start. The bot replies with an acknowledgment. From the OpenClaw workspace, run openclaw channel attach telegram and confirm the prompt. The Gateway now polls Telegram for incoming messages and routes them into the agent's session store. Test it: send "hello" from Telegram and watch for a reply. If it works, you are connected. If not, run openclaw doctor and look for the Telegram channel red.

The reason we chose Telegram over WhatsApp for fire-start is twofold. First, Telegram's Bot API is formal, stable, and free. WhatsApp's Baileys-based integration is a reverse-engineered Web protocol that occasionally breaks when WhatsApp updates client builds, and getting an official WhatsApp Business API account is a multi-week process involving Meta business verification. Telegram is five seconds. Second, Telegram supports rich-text formatting, file attachments, voice notes, and message threading without any additional account work, which means the agent's full output range is usable from day one. WhatsApp's formatting is more limited and the file size caps are stricter. The comparison of OpenClaw channels in the ultimate guide goes deeper on this trade-off.

A note on multi-channel. OpenClaw supports running multiple channels at once with unified context, meaning a conversation started on Telegram can continue on Discord without losing thread - Lumadock multi-channel tutorial. This is genuinely useful, but it is a day-30 enhancement, not a day-1 one. Adding Discord, Slack, or iMessage in the first hour is exactly the kind of skill-binge failure mode we discussed in section 8. Master one channel before adding a second. The cognitive cost of keeping the agent's behavior consistent across channels rises quickly, and unified-context bugs are hard to debug if you do not yet have a feel for normal single-channel behavior.

The other reason to stick with one channel for at least the first week is that alerting-telegram is now wired into your cron jobs and proactive workflows. If you add a second channel before learning what proactive volume looks like, you will end up with the agent pinging you on three apps at once and you will mute one or all of them. Single-channel fire-start lets the agent's proactive cadence settle into your attention budget at a sustainable rate.

---

12. Step 7: End-to-End Verification

The agent is installed, onboarded, skilled, plugged in, and channel-connected. Before declaring fire-start complete, run a short verification sequence that exercises every layer. The point is to catch silent breakage now rather than at 11pm on Tuesday when you actually need the agent to work.

Run these four tasks from Telegram, in order, and watch what comes back. The full sequence takes three to four minutes.

Task 1: pure model. Send "Summarize the difference between OAuth and API key authentication in two sentences." This exercises only the model layer. You should get a clean two-sentence response. If it fails, your Anthropic key or model routing is broken.

Task 2: Suprsonic search. Send "Search for the current price of one bitcoin and cite the source." This exercises the suprsonic-search skill. You should get a response with a current price and a source URL. If it fails, your Suprsonic key is wrong or the suprsonic-search skill did not install correctly. Check openclaw skills list and confirm the four @suprsonic/* skills are present.

Task 3: browser automation. Send "Take a screenshot of o-mega.ai and tell me what the headline says." This exercises playwright-cli inside the sandbox. You should get back a screenshot description. The first time this runs, the Docker sandbox image pulls, which adds 30-60 seconds. After that it is fast. If the sandbox fails to start, check Docker is running (docker ps) and that your user can run Docker without sudo.

Task 4: cron and alerting. From the workspace, run openclaw cron add --every 5m --name "fire-start-test" --command "echo $(date) > ./test.log". Wait six minutes. The agent should ping you on Telegram saying the cron ran, and test.log in the workspace should have a timestamp. This exercises the cron system, the alerting-telegram skill, and the shell-control skill simultaneously. Once verified, run openclaw cron remove fire-start-test to clean up.

If all four pass, the fire-start is real. You now have a working agent. Spend the rest of your first day asking the agent to actually do something useful: research a topic, draft a blog post, watch a website for changes, summarize your inbox if you have a working IMAP setup, transcribe a voice note, generate an image. The agent's capability surface is broad enough that the first useful task usually surfaces within an hour of normal use.

If any of the four fail, fix that one before moving on. The most common failures are Docker not running (task 3) and Suprsonic key environment variable not exported into the agent's shell (task 2). Both are 30-second fixes if you know what to check.

---

13. Common Fire-Start Pitfalls (and How to Skip Them)

Most users hit at least one of the following pitfalls during fire-start, and most pitfalls cost an hour or more to debug. Naming them in advance lets you skip the entire class.

Pitfall 1: skill bingeing. The user installs forty skills the first hour because each one looks useful. Memory bloat and permission collisions follow. The fix is the eight-skill lineup in section 8 and the earned-auth heuristic in section 5. Resist the dopamine of the marketplace.

Pitfall 2: editing the system prompt structure. The user opens SOUL.md, IDENTITY.md, USER.md, CLAUDE.md, and TOOLS.md and tries to refactor them into a single file. Don't. The five-file structure is intentional and the OpenClaw runtime relies on the order. Edit SOUL.md, leave the rest at defaults until you understand why each file exists.

Pitfall 3: disabling the sandbox to "make it work faster." The user sees the Docker startup latency, decides it is annoying, and disables the sandbox. The agent now has direct shell access on the host. This is the highest-blast-radius mistake in OpenClaw. Microsoft Security explicitly recommends treating OpenClaw as untrusted code execution with persistent credentials, which means the sandbox is non-negotiable - Microsoft on running OpenClaw safely. Live with the 30-second startup; it is the cheapest insurance you will buy this year.

Pitfall 4: rotating API keys monthly out of paranoia. Some users rotate every credential on a fixed schedule. For fire-start, this is over-engineering. Anthropic and Suprsonic keys can be rotated on demand if you suspect a leak; otherwise leave them. The token-rotation churn introduces more breakage than it prevents at this scale.

Pitfall 5: scaling channels before mastering one. Adding Slack, Discord, and iMessage in week one means you do not learn the agent's proactive cadence in any single channel. Stay on Telegram for at least the first 14 days.

Pitfall 6: ignoring the doctor command. openclaw doctor is a one-page diagnostic that catches almost every fire-start regression. Run it after every config change. The 10-second cost catches an hour of debugging on average.

Pitfall 7: assuming local Ollama is "free." The user reads about Ollama and assumes local models are no-cost. They are not, on day one. Model downloads consume bandwidth and disk; useful local models require GPU; CPU-only inference on a 14B parameter model produces 30-second response times that destroy the agent feel. Local models are an excellent enhancement at week three, not a fire-start choice.

Pitfall 8: skipping openclaw cron add because cron looks intimidating. The cron system is the difference between an agent that responds when poked and an agent that proactively runs your day. Spend ten minutes adding three real cron jobs (morning briefing, end-of-day summary, weekly review) within the first week. Without them you have a glorified chatbot.

Pitfall 9: trying to template a SOUL.md from someone else's repo. GitHub is full of public SOUL.md files from people running OpenClaw. Most of them are highly personal and reflect the original author's tone, not yours. Importing one wholesale produces an agent that talks like a stranger, which is uncomfortable and quickly leads to either uninstalling or rewriting from scratch. Spend 60 seconds writing your own twelve lines. The agent's voice will fit your work much better, and you will know exactly which line to edit when you want to change a behavior.

Pitfall 10: confusing skills with MCP plugins. OpenClaw supports both extension formats and they sometimes overlap. Skills are tightly coupled to OpenClaw's planner and personality system; MCP plugins are protocol-standard tool calls portable across runtimes. Both are correct on day one for the eight-skill, three-MCP fire-start, and the planner picks whichever surface is more efficient for a given task. Where users get confused is when they try to debug a misbehaving capability and forget to check both lists. If a capability seems missing, run openclaw skills list and openclaw plugins list separately. They are different namespaces with different install paths.

The mental frame for all ten pitfalls is the same: fire-start is about discipline, not minimalism for its own sake. Every skipped step is a deferred task with a clear trigger that earns it back into the lineup. Discipline now, expansion later. The 30-minute target is not a stretch goal; it is what you should hit on a first attempt with the steps written out, and it is what you should be able to repeat in 15 minutes if you ever need to redo the install on a new laptop or VPS.

---

14. Where Suprsonic Fits in the Day-1 Stack

We have referenced Suprsonic throughout this guide because it is doing the heavy lifting on auth count without sacrificing capability. This section makes the role explicit so you can reason about it the way the agent does.

Suprsonic is a capability abstraction layer for AI agents. One API key, one unified response format, one bill, one credit balance covering search, scrape, screenshot, STT, TTS, profile finding, email finding, image generation, file conversion, and 10 other utility capabilities, with provider failover behind every endpoint. The platform's positioning is described in detail in our Suprsonic alternatives comparison, which shows why the unified-API category is small and what Suprsonic does that single-purpose providers and integration platforms do not.

The OpenClaw fire-start uses Suprsonic in exactly two ways. As skills, where the four @suprsonic/* packages appear in openclaw skills list and behave like any other skill. As an MCP server, where suprsonic-mcp exposes the same capabilities through the Model Context Protocol so the agent's planner can use them through the tool-call schema directly. The two surfaces are equivalent in capability and complementary in agent behavior.

The first-principles benefit is that the marginal cost of adding a Suprsonic capability is zero auth events. When Suprsonic ships a new capability (say, voice cloning, or document classification, or stock price feeds) it lights up immediately for every agent using the existing key. There is no new signup, no new token, no new response format to learn, no new rate-limit envelope to internalize. This is the compounding-value property covered in the unified API guide for AI agents. Each additional capability raises the agent's ceiling without raising its auth burden.

The boundary worth understanding is that Suprsonic is the capability layer, not the integration layer. If you want the agent to read your Gmail, take notes in Notion, post to your Slack, or push to your GitHub, those are user-OAuth integrations and Suprsonic does not (and should not) touch them. Tools like Composio, Nango, and Arcade live in that adjacent category, and the LLM tool gateways guide covers how to think about when each layer is needed. For fire-start, you do not need any integration-layer tool yet; you need capabilities, and Suprsonic covers them.

A platform like o-mega.ai sits adjacent to OpenClaw at a different abstraction level. Where OpenClaw is a single-machine, single-user agent runtime, o-mega.ai is a cloud-based AI workforce platform where you deploy multiple agents as a coordinated team, each with its own virtual browser, tools, and identity. The fire-start covered in this guide is the right starting point for personal use. If you eventually want to operate dozens of agents across a company with shared memory and unified controls, that is the migration path, and we cover it in our autonomous business operations guide. For day one, OpenClaw on a laptop with a Suprsonic key is enough.

This guide was written by Yuma Heymans (@yumahey), founder and CEO of o-mega.ai. His work on auth-minimized agent infrastructure across HeroHunt.ai and the broader O-mega ecosystem informs the fire-start framing throughout the article. He is based in San Francisco and writes regularly on agent architecture and the integration layer.

---

15. The 30-Minute Walkthrough Recap

A complete fire-start, end-to-end, in chronological order with rough time estimates per step. Print this section, run it, mark each box as you complete the step. The whole sequence reliably fits inside a 30-minute window for a user new to OpenClaw.

The diagram captures the entire fire-start architecture on one screen. Two keys and one bot token feed into the runtime. The runtime runs eight skills and three MCP servers, all of which inherit auth from the runtime layer. The user has zero direct auth events with any of the eight skills or three MCP servers; everything is mediated by the three credentials at the top. This is the auth-minimization principle made concrete.

The chart below shows why this matters. We measured "credential-events-to-capability ratio" across the five candidate stacks from section 4. Each stack delivers different capability coverage at different auth cost; the ratio captures how much capability you get per credential signed up for. Lower auth events per capability means the stack is more efficient at packaging power.

The recommended stack delivers 6.3 capabilities per credential, which is roughly 5.7x more efficient than the brittle single-purpose API approach and 3.5x more efficient than the local-model setup that looks attractive on paper. The math holds because Suprsonic packages 19 capabilities behind one key, so even amortizing across the Anthropic key and the Telegram token, the average density per credential stays high. This is the structural reason the fire-start works.

The chronological recap, with target durations.

Minutes 0-5: install OpenClaw. Run curl -fsSL https://openclaw.ai/install.sh | bash, create a clean workspace at ~/agents/fire-start, run openclaw --version to verify the binary. Step described in section 6.

Minutes 5-10: onboarding. Run openclaw onboard, paste Anthropic API key, paste Telegram bot token created via @BotFather, decline SOUL.md template, run openclaw doctor and resolve any reds. Step described in section 7.

Minutes 10-17: skill installation. Run openclaw skills install with the eight-skill lineup from section 8: four @suprsonic/* skills, two @openclaw/* skills (playwright-cli, shell-control), two more @openclaw/* skills (memory-search, alerting-telegram). Verify with openclaw skills list.

Minutes 17-21: MCP installation. Run openclaw plugins install for suprsonic-mcp, filesystem-mcp, and fetch-mcp. Verify with openclaw plugins list. Step described in section 9.

Minutes 21-26: smart defaults. Edit openclaw.json to enable Docker sandbox with internal network and read-only root, write a 12-line SOUL.md, set hybrid memory weights to 0.7/0.3, set autoExtract on, set compaction threshold 40,000. Step described in section 10.

Minutes 26-30: end-to-end verification. Send the four test tasks from section 12 via Telegram, watch them complete. Add and immediately remove the test cron job. Mark fire-start complete.

If you finish in under 30 minutes, you have a working agent with two credentials, eight skills, three MCP servers, one sandboxed runtime, and one messaging channel. That is enough to do real work today. Everything else in OpenClaw is an enhancement, not a prerequisite.

---

16. Future-Proofing Your Setup

A fire-start that does not evolve becomes obsolete by week three. The point of starting small is that the small starting position has a clean expansion path, not that the small position is the final position. This section names the concrete expansion triggers and the path each one opens, so you do not have to figure out the next move under pressure.

Trigger: you copy-paste GitHub PRs into the agent three times in a week. The path is to install the GH-Issues skill, sign into GitHub OAuth, and add the openclaw-creating-the-ai-agent-workforce-ultimate-guide-2026 developer scenario configuration. The agent now reviews PRs autonomously. The auth cost is one OAuth flow, and the trigger justifies it.

Trigger: your monthly Anthropic bill exceeds $50. The path is to add OpenRouter for cost-mixing. Configure openrouter/openrouter/auto for routine queries and keep Anthropic Opus for reasoning-heavy tasks. The 80/15/5 model-tier split documented in the OpenClaw pricing guide typically reduces costs 40-60%. The auth cost is one new account, and at $50+ per month it pays for itself within a week.

Trigger: you start asking the agent to find people, parse invoices, transcribe meetings, or generate images. The path is already paid for. These are existing Suprsonic capabilities (profiles, invoice-parse, transcribe, images) that ride on the same key you already created. Just start using them in your prompts; the planner picks the right skill. No new auth events. This is the compounding-capability property of the unified-API layer in action.

Trigger: you want to operate the agent while traveling. The path is to migrate from your laptop to a $5-11 VPS, which the openclaw setup guide for ten configurations documents in detail. Hetzner CPX31 at $11 per month or Contabo VPS S at $4.99 per month both work. The migration is a directory copy and a pm2 restart; auth count does not change because the keychain ports cleanly. This is a Sunday afternoon project, not a weekend project.

Trigger: you find yourself asking the agent the same thing daily. The path is openclaw cron add to schedule the question and have the agent push the result via alerting-telegram. The Context Studios production setup runs 13 cron jobs, 78 custom MCP tools, and multiple skills in production, generating four-language blog posts, social engagement, inbox monitoring, branded image generation, and content pipelines fully autonomously - Context Studios. Your cron count will start at three and grow over months. Do not try to add 13 in week one; let the daily rhythm reveal the right ones.

Trigger: you want a second agent for a different domain. The path is to create a second workspace (~/agents/research, ~/agents/marketing, etc.) with its own openclaw.json, SOUL.md, and skill lineup. The Anthropic and Suprsonic keys are shared across workspaces; only the workspace-specific config differs. This is how a single user grows into a personal multi-agent setup, and the self-improving AI agents guide covers what changes when you start coordinating multiple agents on shared goals. Eventually you may outgrow single-machine setups entirely, at which point platforms like o-mega.ai provide the multi-agent workforce model in the cloud.

Trigger: a security or compliance review. The path is to swap the Docker sandbox for gVisor or Firecracker MicroVMs via Kata Containers, enable egress logging, and tighten the shell-control allowlist. The stealth browser alternatives guide covers the analogous question for browser automation in regulated environments. None of this is fire-start work; it is week-six work. But the fire-start architecture leaves all those upgrade points cleanly accessible.

Trigger: you want to ship something built on top of OpenClaw to other users. The path is to build a private skill or MCP server and publish it. The build your first MCP server guide is the right starting point; the API marketplaces guide covers distribution. The fire-start agent is your test environment for skills you build; it is well-suited because it is small, fast, and reproducible.

The closing observation is structural rather than tactical. OpenClaw's strength is that it is infrastructure, not a product. The fire-start gets you to the point where you have a working substrate; from there, the agent is whatever you grow it into. The auth-minimized fire-start is the right substrate because it minimizes regrets. You will rarely regret not signing up for an account; you will frequently regret signing up for too many. The few-auths discipline pays compounding dividends every week the agent is in use.

For users who eventually want a fully managed, multi-agent, cloud-based version of this same architecture, o-mega.ai offers an AI workforce platform with pre-designed agents, virtual browsers, monitoring dashboards, task scheduling, and human approval flows; it is the natural end-state for someone whose agent footprint has grown beyond a single machine. For users who plan to keep things personal and local, the fire-start in this guide is the foundation that scales as far as a single laptop or a single VPS can take it. Both paths start the same way: minimal auth, maximum capability, eight skills, three MCPs, one channel, thirty minutes.

This guide reflects the OpenClaw and Suprsonic landscape as of April 2026. Pricing, model availability, and skill lineups change frequently in this space, sometimes weekly, so verify current details before purchasing or signing up.