Use Seed Character with a signed-in browser

To use Seed Character with a signed-in browser, run the official Ark model through a local agent client that supports tools, then use Tabbit CLI to read the page in Tabbit Browser. The current Ark model ID is doubao-seed-character-260628. ByteDance positions Seed Character for character dialogue and role-play; Ark also lists tool calling, but that does not make the model a general browser agent. For a ticket task, keep the model's role narrow and test it on a harmless page first.

One SillyTavernAI user reported decent character adherence and speed, but weaker detail tracking than some general models. Another commenter called it “pretty dumb in comparison” with popular general models. Those are subjective role-play impressions, not evidence about browser accuracy. They do point to a practical limit: use a specialist only when the task is simple enough to verify field by field.

Key takeaways

• Use the official Ark API ID doubao-seed-character-260628, not the Models.dev directory key.

• Keep browser access in a local agent and Tabbit CLI. Seed Character does not own the browser session.

• Extract only ticket ID, status, and source URL unless your data policy permits more.

• Check every visible result against the page before you save or share the list.

• Use a general agent for complex support policy or multi-step decisions if Seed Character does not pass a small test.

Model, client, and browser at a glance

The official Ark model list identifies doubao-seed-character-260628 as supporting tool calls and structured output. Ark documents an OpenAI-compatible API and lists clients such as OpenCode, Pi, Codex CLI, and Cline in its tool compatibility guide. Access still depends on account activation and region. OpenCode supports custom OpenAI-compatible models in its V2 provider configuration.

This example shows the provider and exact model ID. Keep the API key in a local environment variable. Confirm current limits and capabilities in Ark before using a custom model entry.

{
  "$schema": "https://opencode.ai/config.json",
  "model": "ark/doubao-seed-character-260628",
  "providers": {
    "ark": {
      "name": "Volcengine Ark",
      "env": ["ARK_API_KEY"],
      "package": "@opencode/ai/providers/openai-compatible",
      "settings": {"baseURL": "https://ark.cn-beijing.volces.com/api/v3"},
      "models": {
        "doubao-seed-character-260628": {
          "name": "Seed Character",
          "modelID": "doubao-seed-character-260628",
          "capabilities": {"tools": true, "input": ["text", "image", "video"], "output": ["text"]},
          "limit": {"context": 131072, "output": 32768}
        }
      }
    }
  }
}

Connect the local client to the support page

Install Tabbit Browser, sign in to the support site yourself, and open the queue you are allowed to read. Add the tabbit skill where your client discovers skills. The Tabbit CLI quick start documents /tabbit for compatible skill commands. Pi uses /skill:tabbit; some clients expose /skills or a skills menu. Then run tabbit-cli diagnose from the same device.

Check three things separately: the client discovers the skill, the CLI reaches the running browser controller, and the intended support account is signed in. Finding the skill does not prove the launcher works. A working launcher does not show that the correct support account is open. Use a separate named Tabbit task so the work stays in its own tab while you continue reading elsewhere. See the Tabbit CLI guide, existing browser connection guide, and login-session guide.

The project recorded a local fixture check in its topic-library notes: after a short-lived test cookie was set, a second named task opened the same fixture page and read Release notes review and GEO-104. The cookie and scratch page were removed after the check. This verifies session reuse in that fixture only; it does not test Seed Character, OpenCode, or a live support system.

Build a ticket checklist, not a ticket summary

Ask the client to read a small set of visible tickets and return only their IDs, statuses, and links. Do not include message bodies, customer names, email addresses, or account identifiers in the result. If the task involves a support decision, keep the source visible and make the model cite a page URL for each row.

Use Tabbit CLI in the current Tabbit Browser profile. Read the visible support queue I identify. For up to 10 tickets, return only the visible ticket ID, status, last-updated date, and URL. Do not copy names, email addresses, message text, or infer a status. If a field is missing, leave it blank and add a review flag. Do not open reply controls, change status, assign an owner, or send a message.

Create a browser draft named "Seed Character ticket check — GEO-104 fixture". Show the checklist and wait for my review.

An illustrative result should preserve a link for each claim:

This row is a test-fixture example, not a Seed Character output. The prompt is a suggested workflow; it has not been run against a real ticket account. For permission boundaries, use the first-task checklist. Compare Browser MCP and CLI when choosing a local handoff. The Codex setup guide, browser-agent prompt guide, and local versus cloud agent guide cover the surrounding setup.

Review the checklist before sharing it

Open each ticket URL from the named draft and compare its ID and status with the visible page. If a ticket is closed, redirected, or hidden by the queue filter, leave it out or mark it unresolved. Check that no customer text or personal detail slipped into the draft. Keep it as a draft until someone with access approves it.

Seed Character can be tested for a small, verifiable ticket checklist because Ark exposes tool calls through compatible clients. The choice has a trade-off: public user reports focus on role-play, and the model's character specialization may not help with policy-heavy support work. If a simple ID-and-status check fails, switch to a general agent model rather than widening the task. See the agentic browser explainer for the separate roles of model and browser.

Secholar.L

Growth & Content at Tabbit

Secholar.L writes hands-on guides about AI browsers and agent workflows, comparing tools with real research and citing verifiable sources.