GUIDE
Cursor, VS Code, Zed, Claude Code
Use Taskclan Intelligence inside your editor. Taskclan exposes two drop-in compatibility surfaces — OpenAI and Anthropic — so any client that already speaks either wire format works with a Taskclan API key. All calls debit the same T1 credit wallet.
Endpoints
| Wire format | Base URL | Auth header |
|---|---|---|
| OpenAI | https://engine.taskclan.com/api/openai/v1 | Authorization: Bearer sk_t1_… |
| Anthropic | https://engine.taskclan.com/api/anthropic/v1 | x-api-key: sk_t1_… (or Authorization: Bearer) |
Get a key from platform.taskclan.com/api-keys.
Model names
Four model ids, one for each tier plus Auto. Pick Auto to let Taskclan decide per prompt (recommended for most editor use); pick a specific tier when you want deterministic cost. Unrecognized names fall back to Flow.
| Tier | Model id | When to use |
|---|---|---|
| Auto | T1-auto | Recommended default — router picks Core / Flow / Max per prompt based on length + content. Response tells you which tier actually ran. |
| Core | T1-core | Fast, cheap — quick edits, simple completions, chat. |
| Flow | T1-flow | Balanced default — most agent turns, code generation, refactors. |
| Max | T1-max | Deep reasoning + extended thinking — hard debugging, architecture, Plan mode. |
Capabilities
Every tier is a full first-class model in your editor — tools, vision, PDFs, prompt caching, and streaming all work end-to-end. Extended thinking (Cursor Plan / Fable Plan) is Max-only, and Auto promotes prompts with reasoning cues to Max automatically.
| Capability | T1-auto | T1-core | T1-flow | T1-max |
|---|---|---|---|---|
| Streaming | ✓ | ✓ | ✓ | ✓ |
| Tool use / function calling | ✓ | ✓ | ✓ | ✓ |
| Parallel tool calls | ✓ | ✓ | ✓ | ✓ |
| Vision (image references) | ✓ | ✓ | ✓ | ✓ |
| PDF / document references | ✓ | ✓ | ✓ | ✓ |
Prompt caching (Anthropic cache_control) | ✓ | ✓ | ✓ | ✓ |
| Extended thinking (Plan mode) | via Max | — | — | ✓ |
Structured output (JSON schema / response_format) | ✓ | ✓ | ✓ | ✓ |
| Long context (200k tokens) | ✓ | ✓ | ✓ | ✓ |
/v1/models endpoint advertises OpenRouter-shape capability metadata (supported_parameters, architecture.modality, capabilities) so the "may not work well" pill never fires. Vision requests routed to T1-max are transparently sent to Sonnet 5 instead of Kimi K3 (which is text-only).Cursor
Cursor renders /v1/models entries verbatim in its model picker — the goal is to see T1-auto, T1-core, T1-flow, T1-maxappear alongside "GPT-5.6", "Sonnet 5", "Grok 4.5", etc. Cursor's own built-in models keep using your Cursor subscription, so the two live side-by-side.
- Open Cursor Settings (⌘, on macOS, Ctrl+, on Windows/Linux).
- Click the Models tab in the left sidebar of the settings panel.
- Scroll to Custom API Keys → OpenAI API Key. Toggle Override OpenAI Base URL ON.
- Fill in the two fields (get your key from platform.taskclan.com/api-keys):
Base URL: https://engine.taskclan.com/api/openai/v1 API Key: sk_t1_... - Click Verify. Cursor probes
GET /v1/models— a green check means Taskclan responded. A red X almost always means the base URL or key is wrong. - In Model Names (same panel), add the four ids if they aren't auto-populated:
T1-auto,T1-core,T1-flow,T1-max. Click Save. - Open any Cursor chat or composer (⌘L / ⌘I). Click the model dropdown at the bottom of the input. Scroll — you should see T1-auto, T1-core, T1-flow, T1-max in the list.
- Pick T1-auto and send a message. If a reply comes back, you're on Taskclan — the router picked Core / Flow / Max for you based on the prompt shape, and every turn debits your T1 credit wallet.
- Enable Agent mode (⌘L → toggle Agent). T1 tiers advertise full agent capabilities via
/v1/models— the "Agent may not work well" pill should not appear. Pick a task like "read this file and propose a change" to confirm the tool loop round-trips.
VS Code — Taskclan Intelligence extension
The primary path for VS Code users. Our native extension adds @taskclan to VS Code's built-in chat, with /agent, /plan, /refactor, and /explain slash commands. Auto-routes across T1 Core / Flow / Max per prompt. Same wallet, no config file, first-class brand.
- Install from the Marketplace — search "Taskclan Intelligence" in the Extensions view, or run:
code --install-extension taskclan.taskclan-intelligence - Command palette →
Taskclan: Set API Key→ paste yoursk_t1_...key from platform.taskclan.com/api-keys. - Open Chat (⌘⌥I / Ctrl+Alt+I) → type
@taskclan hi. The reply streams back attributed to Taskclan Intelligence, with a footer showing which T1 tier ran, the credit cost, and your remaining balance.
Slash commands pick the tier for you:
| Command | Runs on | What it does |
|---|---|---|
@taskclan <prompt> | T1 Auto | General chat, coding help. Router picks the tier per prompt. |
/agent | T1 Max | Plan, execute, ship. Full agent-mode reply. |
/plan | T1 Max | Plan the change without touching code. Extended thinking. |
/refactor | T1 Flow | Rewrite the selection or referenced file. |
/explain | T1 Core | Explain the selection, file, or symbol. |
Works in Cursor too — Cursor is a VS Code fork, so the extension installs and runs there identically. Cursor Chat doesn't consume the built-in chat-participant API, though, so if you want @taskclan inside Cursor Chat specifically, configure Cursor's built-in custom OpenAI provider instead — see the Cursor section above. The extension still gives Cursor users the participant surface in Cursor's VS Code-style Chat panel.
VS Code — Continue.dev (alternative)
If you already use Continue.dev and prefer keeping everything in one extension, T1 tiers work as OpenAI-compatible models via Continue's config. This is the older path — most VS Code users should just install the Taskclan Intelligence extension above. Continue's model picker reads from ~/.continue/config.yaml. Configure once, then all four tiers show up as distinct entries in the Continue sidebar picker.
- Install the Continue extension from the VS Code Marketplace if you haven't already (Marketplace ID:
Continue.continue). - Open the Continue sidebar (⌘L or the Continue icon), then click the gear → Open Config File. That opens
~/.continue/config.yaml. - Add one block per tier under
models:. Replacesk_t1_...with a key from platform.taskclan.com/api-keys.
models:
- name: T1 Auto
provider: openai
model: t1-auto
apiBase: https://engine.taskclan.com/api/openai/v1
apiKey: sk_t1_...
roles: [chat, edit, apply]
capabilities: [tool_use, image_input]
- name: T1 Core
provider: openai
model: t1-core
apiBase: https://engine.taskclan.com/api/openai/v1
apiKey: sk_t1_...
roles: [chat, autocomplete]
capabilities: [tool_use, image_input]
- name: T1 Flow
provider: openai
model: t1-flow
apiBase: https://engine.taskclan.com/api/openai/v1
apiKey: sk_t1_...
roles: [chat, edit, apply]
capabilities: [tool_use, image_input]
- name: T1 Max
provider: openai
model: t1-max
apiBase: https://engine.taskclan.com/api/openai/v1
apiKey: sk_t1_...
roles: [chat, edit, apply]
capabilities: [tool_use, image_input]Two things about that config are worth knowing:
provider: openainames Continue's internal transport adapter — it doesn't mean your requests go to OpenAI. Continue's provider registry is a fixed allowlist (openai / anthropic / gemini / …) and rejects unknown names at config load, so OpenAI-compatible services (Groq, Together, Fireworks, Taskclan) all reuseprovider: openaiwith a customapiBase. The actual endpoint ishttps://engine.taskclan.com/api/openai/v1.- The
capabilities: [tool_use, image_input]line enables tools and image input across Chat, Plan, and Agent modes. Continue's mode picker may still render a small ⚠️ triangle next to Plan/Agent for T1 tiers — that's driven by a separate hardcoded name-regex in Continue's source (isRecommendedAgentModel), is cosmetic, and doesn't affect functionality. If it bothers you, usemodel: claude-sonnet-4-5-t1-flow(orclaude-haiku-4-5-t1-core,claude-opus-4-5-t1-max,claude-sonnet-4-5-t1-auto) — the server resolver accepts any string ending in-t1-{tier}, so the prefix is opaque payload we use to satisfy Continue's allowlist.
- Save the file. Continue picks up changes on save — no reload needed for most versions. If it doesn't: ⌘⇧P → Continue: Reload Config.
- Click the model name at the bottom of the Continue sidebar chat. You should see T1 Auto, T1 Core, T1 Flow, T1 Max in the list — none with the warning triangle. Switch to Agent or Plan mode and send a message; the reply comes back via T1 and debits your wallet.
Zed
Zed speaks the Anthropic wire format natively — point its anthropic provider at our shim and the T1 tiers appear in Zed's Assistant model picker.
- Open Zed's
settings.json(⌘, → gear → Open Settings JSON, or~/.config/zed/settings.json). - Add a
language_models.anthropicblock that points at Taskclan and declares the three tiers:
"language_models": {
"anthropic": {
"api_url": "https://engine.taskclan.com/api/anthropic/v1",
"available_models": [
{ "name": "T1-auto", "display_name": "T1 Auto", "max_tokens": 200000 },
{ "name": "T1-core", "display_name": "T1 Core", "max_tokens": 200000 },
{ "name": "T1-flow", "display_name": "T1 Flow", "max_tokens": 200000 },
{ "name": "T1-max", "display_name": "T1 Max", "max_tokens": 200000 }
]
}
}- Save. Open the Assistant panel (⌘? or the assistant icon).
- Command palette → Assistant: Set Anthropic API Key. Paste your
sk_t1_…key. - Click the model dropdown at the top of the Assistant panel — T1 Auto / Core / Flow / Maxshould be listed under Anthropic. Pick T1 Auto and send a message — the router picks a tier per prompt.
Claude Code (CLI)
Anthropic's Claude CodeCLI reads two environment variables to swap providers wholesale. Set both, run claude, and every turn hits Taskclan Intelligence.
- Install Claude Code if you don't have it (
npm install -g @anthropic-ai/claude-code). - Export the two variables (persist them in
~/.zshrcor~/.bashrcso every new terminal picks them up):
export ANTHROPIC_BASE_URL="https://engine.taskclan.com/api/anthropic"
export ANTHROPIC_API_KEY="sk_t1_..."
# Optional: pin the tier claude uses. T1-auto is usually the right pick —
# the router chooses per prompt. Otherwise: T1-core / T1-flow / T1-max.
export ANTHROPIC_MODEL="T1-auto" # recommended- Reload your shell (
source ~/.zshrcor open a new terminal). - Run
claude "Reply with exactly: PONG". If you seePONGcome back, you're on Taskclan. - Every subsequent
claudeinvocation — interactive or one-shot — routes through T1 and debits your wallet.
/v1/messages itself. Don't include the /v1 suffix.Claude Desktop (MCP)
Claude Desktop can't swap its underlying model, but it can invoke external tools via the Model Context Protocol. The @taskclan/mcp package exposes Taskclan Intelligence as four tools — taskclan_run(any T1 tier), taskclan_studio_generate (image), taskclan_workflow_run(named engine workflow), taskclan_balance (wallet). Once configured, Claude can decide to call them mid-conversation.
Open ~/Library/Application Support/Claude/claude_desktop_config.json(create it if it doesn't exist) and add one entry under mcpServers:
{
"mcpServers": {
"taskclan": {
"command": "npx",
"args": ["-y", "@taskclan/mcp"],
"env": {
"TASKCLAN_API_KEY": "sk_t1_..."
}
}
}
}Restart Claude Desktop. Open a new chat, click the tools icon in the composer — you should see taskclan_run, taskclan_studio_generate, taskclan_workflow_run, taskclan_balance listed under a Taskclan section. Ask Claude "use Taskclan Max to compare X and Y" and it'll call the tool; the response streams back into the chat and debits your T1 wallet.
The same block works in Claude Code (~/.claude/settings.json) and in Zed's settings.json under an mcp key — any MCP-capable client picks it up.
T1-max) or generating an image without leaving the chat. If you want to replacethe model entirely, use the Claude Code CLI setup above instead.VS Code — Cline
Cline (formerly Claude Dev) is a VS Code agent that speaks the Anthropic wire format. Point it at Taskclan and the T1 tiers become picker options in the Cline sidebar.
- Install Cline from the VS Code Marketplace (Marketplace ID:
saoudrizwan.claude-dev). - Open the Cline sidebar (its icon in the activity bar), then click the gear (Settings).
- API Provider → select Anthropic Compatible.
- Fill in the three fields:
API Base: https://engine.taskclan.com/api/anthropic/v1
API Key: sk_t1_...
Model: T1-auto (or T1-core / T1-flow / T1-max)- Click Done. Send a message in the Cline chat — the reply routes through T1.
- To pin a specific tier, change the Model field to
T1-core,T1-flow, orT1-max. Cline reloads the provider on save.
aider (CLI)
aider is a terminal AI pair-programmer. Point it at Taskclan via two env vars and it uses the T1 tier you pass on the command line.
- Install aider (
pip install aider-chator see aider.chat). - Export the two environment variables — persist them in
~/.zshrcor~/.bashrc:
export OPENAI_API_BASE=https://engine.taskclan.com/api/openai/v1
export OPENAI_API_KEY=sk_t1_...- Run aider with an explicit T1 tier:
aider --model openai/T1-auto # recommended — router picks per prompt aider --model openai/T1-flow # or pin a specific tier aider --model openai/T1-core file.ts # start a session on file.ts - The
openai/prefix tells aider to use its OpenAI provider (which reads the env vars above). Every turn hits Taskclan and debits your wallet.
curl
Both endpoints are plain HTTP — great for smoke-testing before you wire an editor:
# OpenAI shape — T1-auto lets the router pick per prompt (see x_taskclan.autoRoutedFrom / autoRoutedReason).
curl https://engine.taskclan.com/api/openai/v1/chat/completions \
-H "Authorization: Bearer sk_t1_..." \
-H "Content-Type: application/json" \
-d '{"model":"T1-auto","messages":[{"role":"user","content":"Reply PONG"}]}'
# Anthropic shape — same idea; x_taskclan sidecar reports the resolved tier.
curl https://engine.taskclan.com/api/anthropic/v1/messages \
-H "x-api-key: sk_t1_..." \
-H "Content-Type: application/json" \
-d '{"model":"T1-auto","max_tokens":16,"messages":[{"role":"user","content":"Reply PONG"}]}'Billing and errors
Both endpoints meter against the same wallet as /api/t1/complete and the SDK. A 402 means insufficient credits — see Errors & rate limits for the recommended catch pattern. All other error codes match the upstream wire format (invalid_request_error, authentication_error, etc.).
stream: true. Chunk formats match each provider's SSE conventions — OpenAI emits data: {choices:[{delta}]} chunks, Anthropic emits event-typed message_start / content_block_delta /message_stop frames.