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daemon-backend-cursor

Nested daemon-cli-backends reference for the Cursor daemon backend's flag surface. Read this only when a daemon task needs Cursor-specific CLI flags (model selection, output/tooling switches): it routes you to the installed CLI's live help via shell and shows how to translate that help into the generic `backend_options` mechanism. It is not a flag catalog.

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Lingtai-AI/lingtai-kernel
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7 de agosto de 2026 a las 07:21
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SKILL.md
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name
daemon-backend-cursor
description
Nested daemon-cli-backends reference for the Cursor daemon backend's flag surface. Read this only when a daemon task needs Cursor-specific CLI flags (model selection, output/tooling switches): it routes you to the installed CLI's live help via shell and shows how to translate that help into the generic `backend_options` mechanism. It is not a flag catalog.
version
0.3.0
last_changed_at
2026-08-07T00:00:00.000Z
related_files
["src/lingtai/tools/daemon/manual/reference/cli-backends/SKILL.md"]
maintenance
Tracks the Cursor daemon backend flag-discovery topic it documents; update when that integration changes.
# Cursor Daemon Backend — Flag Discovery Entrypoint The installed CLI's own help is the authority for Cursor Agent flags; this page is only the entrypoint. Conversion rules live in the parent [`reference/cli-backends/SKILL.md`](../../../SKILL.md). ## Discover flags from the installed CLI 1. Run `agent --version` and `agent --help` in bash. The daemon spawns root `agent` directly (the root binary is `agent`; older docs said `cursor-agent`) — `agent -p --force --output-format stream-json <prompt>` — so root help is authoritative (keychain errors happen before help on some builds). 2. Translate what you found into `backend_options` with the parent's generic conversion rules (nothing Cursor-specific is added). ## Example: model selection via the generic route `backend_options` keys become long flags, inserted after the harness-owned flags and before the task prompt: ```jsonc { "backend": "cursor", "tasks": [{ "task": "Implement and validate the change.", "tools": [], "backend_options": { "model": "opus" } }] } // argv: --model opus ``` The flag and model vocabulary belong to the installed CLI — LingTai does not validate, enumerate, or simulate them. Confirm `--model` and its accepted values in your installed `agent --help` before relying on this; an unknown flag or value is the CLI's error, not the daemon's. ## Source-pinned stream-json usage For installed `agent-cli@2026.05.28-a70ca7c`, accept usage only from `type=result`, `subtype=success`, `is_error=false` with all four non-negative integer fields: `inputTokens`, `outputTokens`, `cacheReadTokens`, `cacheWriteTokens`. `inputTokens` is already net; UI-only `cli_tokens` adds read + write as cached, preserves raw usage, ignores invalid/all-zero blocks, and counts duplicate terminal results once. Join model only from a preceding matching `system/init` by `session_id`; provider stays unknown because this source emits no provider identity (do not infer it from `apiKeySource`, model, backend, credentials, or environment). This is version-pinned, not a cross-release claim. ## Subscription & auth Cursor account/subscription (keychain login); LingTai does not inject credentials — the CLI must be signed in. Official docs: https://docs.cursor.com/agent ## Harness boundary Cursor declares no reserved-flag list at validation, so nothing is refused beyond generic key/value safety rules. Still, do not re-set harness-owned surfaces: `-p` (non-interactive print mode), `--force` (allows file modifications in print mode), `--output-format stream-json` (one JSON event per stdout line — the daemon's progress/result parser and the session-id capture depend on it), and `--resume` (owned by `ask` follow-ups, which replay the captured session id). Session and completion: the first session-id-shaped stream event is stored as `cursor_session_id`; `ask` resumes with `agent -p --force --resume <cursor_session_id> --output-format stream-json <message>` (one follow-up in flight per session). Per-run MCP injection is not wired for this backend yet, so no `finish` contract: success comes from the stream's final result event and the process exit code. `backend_options` is honored only at `emanate` time; `ask` follow-ups reuse the session without re-passing it.
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