The adapter layer is OD's most load-bearing design decision. We delegate the **entire agent loop** — model calls, tool use, context management, permission handling, resume, cancel — to the user's existing code agent CLI. OD's job is to detect it, feed it a skill + prompt + working directory, and stream its output back to the web UI.
> **Thesis:** The code agent space has already converged on a few strong implementations (Claude Code, Codex, Devin for Terminal, Cursor Agent, Gemini CLI, OpenCode, OpenClaw, Qoder CLI). Reimplementing another one is worse than just talking to all of them.
Run all adapters' `detect()` in parallel on daemon start, then cache results in `~/.open-design/agents.json` with a 24h TTL. Re-detect on daemon `SIGHUP`.
1.**PATH scan.**`which <binary>` for each known executable name. Fast (<10ms).
2.**Config-dir probe.** Check for `~/.claude/`, `~/.codex/`, `~/.cursor/`, etc. This catches cases where the CLI was installed via npm global into a shell-specific PATH.
If both signals agree, detection is confident. If only one signal fires, we mark `authState: "missing"` and prompt the user to run the CLI's auth flow.
Agent scans its own `~/.<agent>/skills/` on launch. We symlink OD's skill into that dir (see [`skills-protocol.md`](skills-protocol.md) §3) and let the agent pick it up natively. Zero prompt overhead.
- **Works for:** Claude Code. Codex (version-dependent). OpenCode.
### 4.2 Prompt injection (fallback)
We read the skill's `SKILL.md` body + any `references/*.md` files it has, concatenate them into the system prompt, and copy `assets/` files into the cwd. The agent has no concept of "skills" but has the instructions.
- **Works for:** everyone. Default for API fallback, Cursor Agent, Gemini CLI.
- **Cost:** more tokens per run. Mitigation: prune `references/` to the files the skill body actually mentions.
### 4.3 File-placed workflow (hybrid)
For agents that support `AGENTS.md` / `.cursorrules` / similar project-level instruction files (Cursor Agent, OpenCode), we write a project-scoped instruction file in the artifact cwd before running the agent. The agent picks it up automatically.
- **Works for:** Cursor Agent (`.cursorrules`), some OpenCode configurations.
The adapter declares which strategy to use via `capabilities().nativeSkillLoading` and a private `skillInjectionStrategy` field.
- Tool use: we register `Read/Write/Edit` as tools, implement them in the daemon against the artifact cwd, and run the loop ourselves. This is the one place OD does own the loop — because the user has no agent at all. Keep it as dumb as possible.
- **Why ship this at all?** Topology C requires it (no daemon available in a pure-Vercel deploy). Also, users trying OD for the first time without a CLI installed still get a working experience.
- Install/update: macOS/Linux/WSL users can install with `curl -fsSL https://cli.devin.ai/install.sh | bash`; run `devin update` for existing installs.
- Version requirement: requires a Devin CLI build with the `devin acp` subcommand (verified with `devin 2026.5.1-1`). Check with `devin acp --help`; if the subcommand is missing, update or reinstall Devin for Terminal.
- Streaming: Agent Client Protocol JSON-RPC over stdio, handled by the daemon's shared `acp-json-rpc` transport.
- Skill loading: Devin supports `.devin/skills/` and `~/.config/devin/skills/`; OD's current daemon also prompt-injects the selected skill body into the composed prompt, so no per-project skill install is required for generation.
- Surgical edits: Devin's own edit/write tools handle targeted changes.
- Permission: `--permission-mode dangerous` avoids headless approval prompts in the web UI; `--respect-workspace-trust false` ensures Devin doesn't block on trust prompts for newly created project dirs. Org/team-level policies still apply inside Devin.
- Invocation: `cursor-agent --workspace <dir> "<prompt>"` (rough; verify with CLI docs at implementation time).
- Streaming: yes, JSON lines.
- Skill loading: no native skill concept. We write a `.cursorrules` file into the artifact dir before running. The rules file contains the skill's SKILL.md body (minus front-matter).
- Surgical edits: Cursor's inline edit tool is strong; map our `refine` call to its edit protocol.
- **Gotcha:** Cursor Agent operates on workspaces, not single files. Constrain the workspace to the artifact dir to prevent over-broad changes.
- Invocation: `copilot -p "<prompt>" --allow-all-tools --output-format json --add-dir <skills> --add-dir <design-systems>`. `--allow-all-tools` is mandatory in non-interactive mode — without it the CLI blocks waiting for human approval on every tool call. Unlike Codex (where `exec` is a dedicated headless subcommand with auto-approve baked in) or Claude Code (which inherits its permission policy from `~/.claude/settings.json`), Copilot's `-p` mode always prompts unless this flag is passed explicitly. `--add-dir` (repeatable) widens the path-level sandbox so Copilot can read skill seeds and design-system specs that live outside the project cwd.
- Streaming: `--output-format json` emits JSONL with the same expressive shape as Claude Code's stream-json (`assistant.reasoning_delta`, `assistant.message_delta`, `tool.execution_start/complete`, `result`). `apps/daemon/src/copilot-stream.ts` maps these onto the same UI events as `claude-stream.ts`.
- Skill loading: prompt injection only. Github Copilot's tool catalog includes a `skill` tool — native format worth reverse-engineering later.
- Surgical edits: dedicated `edit` tool.
- Detection assumes Copilot is already authenticated, via one of: `copilot login` (subcommand, OAuth device flow), the interactive `/login` slash command inside `copilot` with no args.
- Invocation: `qodercli -p --output-format stream-json --permission-mode bypass_permissions --cwd <dir> [--model <id>] --add-dir <absolute-skills-dir> --add-dir <absolute-design-systems-dir>`, with the composed prompt delivered over stdin. Print mode exits after the turn, which fits the daemon's one-request chat lifecycle. Qoder is currently text-only in OD; `_imagePaths` are intentionally ignored because Qoder CLI does not expose a supported multimodal flag for this adapter path yet.
- Streaming: `--output-format stream-json` emits JSONL records such as `system/init`, `assistant`, and `result`. `apps/daemon/src/qoder-stream.ts` maps assistant content blocks to text deltas, maps assistant errors without text to typed error events, and preserves result usage, model usage, cost, duration, stop reason, and unknown records as raw events.
- Models: ships fallback hints for `default`, `lite`, `efficient`, `auto`, `performance`, and `ultimate`. Selecting `default` omits `--model` so Qoder's own CLI configuration remains authoritative.
- Skills: prompt injection only in v1. `--add-dir` is repeatable so Qoder can read absolute skill and design-system roots that live outside the active project cwd; the daemon does not forward relative extra directory entries.
- Permission: `--permission-mode bypass_permissions` avoids headless approval prompts in the web UI. Users should treat this as the same trust posture as running Qoder directly with that flag in the selected project directory.
- **Gotcha:** Detection only proves `qodercli --version` can run. Qoder authentication and account scope remain owned by Qoder CLI, with credentials read from Qoder's `~/.qoder/config.json`; the daemon surfaces stderr/stdout failures from the spawned run instead of running login or editing Qoder config.
- Invocation: `pi --mode rpc [--model <id>] [--thinking <level>] [--append-system-prompt <dir> …]`, with the composed prompt delivered over stdin via JSON-RPC. The daemon sends a `prompt` command (optionally with `images` for multimodal input) and pi streams back typed events until `agent_end`. Pi's RPC process stays alive after `agent_end` (designed for multi-prompt sessions); the daemon closes stdin and SIGTERMs after a grace period since `/api/chat` is single-shot.
- Streaming: `pi-rpc` JSON-RPC over stdio. Events include `agent_start`, `turn_start/end`, `message_update` (text deltas, thinking deltas, tool calls), `tool_execution_start/end`, `compaction_start`, `auto_retry_start/end`, `extension_error`. `apps/daemon/src/pi-rpc.ts` maps these onto the same UI event set as `claude-stream.js` / `copilot-stream.js` / `acp.js`. Error events from `extension_error` and exhausted `auto_retry_end` are routed through `sendAgentEvent` so the daemon's empty-output guard and `agentStreamError` flag apply (same path as qoder-stream-json and json-event-stream after issue #691).
- Models: dynamic — `pi --list-models` prints a TSV table to stderr that the daemon parses into provider/model picker entries. Fallback hints for the most common providers/models are shipped for when the list command times out.
- Images: pi's RPC `prompt` command supports an `images` field (base64-encoded `ImageContent` objects). The daemon reads validated `imagePaths` at session attach time and includes them in the prompt command. Unreadable images are skipped rather than failing the run.
- Skills: prompt injection in v1. `extraAllowedDirs` (skill seed and design-system directories) are forwarded as `--append-system-prompt` repeatable flags so the agent knows these directories exist and can Read files inside them. pi doesn't have an `--add-dir` sandbox flag — it uses OS cwd — so system-prompt hints are the only available mechanism. **Important:**`--append-system-prompt` only hints paths in the system prompt; it does not grant sandbox or filesystem access. pi's Read tool can normally open absolute paths outside cwd, but when absolute reads fail (sandboxed environments, restricted permissions), the reliable fallback is to stage copies of the needed files into the project cwd before the run. No stronger pi flag exists for this purpose today.
- Thinking: the daemon exposes pi's `--thinking` levels (`off`, `minimal`, `low`, `medium`, `high`, `xhigh`) in the Settings model picker.
- Extension UI: auto-resolved. pi's RPC protocol can request user dialogs (`select`, `confirm`, `input`, `editor`) and fire-and-forget notifications (`setStatus`, `setWidget`, `notify`, `setTitle`, `set_editor_text`). Dialog methods are auto-approved (confirm → true, select → first option) and fire-and-forget methods are silently consumed because the web UI has no surface for them.
- **Gotcha:** pi's RPC `prompt` response is asynchronous — `success: true` only means the prompt was accepted, not that the agent finished. Agent failures after acceptance surface through the normal event stream (`extension_error`, `auto_retry_end` with `success: false`) and the empty-output guard.
- Invocation: `deepseek exec --auto [--model <id>] "<prompt>"`. The `deepseek` dispatcher owns the `exec` / `--auto` subcommands and delegates to a sibling `deepseek-tui` runtime binary at exec time; upstream documents both binaries as required (the npm and cargo paths install them together). We only probe the dispatcher — `deepseek-tui` on its own doesn't accept this argv shape, so advertising it as a fallback would surface the agent as available but fail on the first chat run. A future revision could teach resolution + buildArgs which binary was selected and emit a verified `deepseek-tui` invocation, with a regression test exercising that path.
- Streaming: plain text deltas to stdout in non-`--json` mode (tool-call notifications go to stderr). Skipping `--json` is intentional — `deepseek exec --json` batches the entire run into one trailing summary object instead of streaming, which would freeze the chat UI until end-of-turn.
- Auto-approval: `--auto` enables agentic mode with the YOLO permission posture. The daemon runs every CLI without a TTY, so the interactive approval prompt would otherwise hang the run.
- Skills: prompt injection only in v1. DeepSeek TUI does walk `.agents/skills`, `skills`, `.opencode/skills`, `.claude/skills`, and `~/.deepseek/skills` first-wins, so a future revision can switch to file-placed skill loading the same way Claude Code does.
- Prompt delivery: positional argv (no stdin sentinel; clap declares `prompt: String` as a required field). This means very large composed prompts can hit Windows' ~32 KB `CreateProcess` limit; for typical chat prompts this is non-issue. Upstream support for a `-` stdin sentinel would let us flip this to `promptViaStdin: true` like the other adapters. To avoid surfacing oversized prompts as a generic `spawn ENAMETOOLONG` / `E2BIG`, the adapter declares `maxPromptArgBytes` (currently 30,000) and `/api/chat` enforces it through three complementary guards: a fast pre-bin-resolution `checkPromptArgvBudget` against the raw composed prompt bytes, a post-`buildArgs``checkWindowsCmdShimCommandLineBudget` that — when the resolved binary is a Windows `.cmd` / `.bat` shim — recomputes the would-be `cmd.exe /d /s /c "<inner>"` command line using the same per-arg quote-doubling the platform layer applies on Windows, and a sibling `checkWindowsDirectExeCommandLineBudget` that — when the resolved binary is a non-shim Windows install (e.g. a cargo-built `deepseek.exe`) — recomputes the same command line using libuv's `quote_cmd_arg` rules (every `"` becomes `\"`, backslashes adjacent to a quote are doubled). The two Windows guards are mutually exclusive on a given resolution: the cmd-shim guard owns `.cmd`/`.bat`, the direct-exe guard owns everything else. Together they catch quote-heavy prompts (code blocks, JSON-shaped skill seeds) that fit under the raw byte budget but expand past CreateProcess's 32_767-char `lpCommandLine` cap on either install path. All three guards emit the same actionable `AGENT_PROMPT_TOO_LARGE` SSE error telling the user to reduce skills/design-system context, shorten the conversation, or pick an adapter with stdin support, and all three are unit-tested (oversized + short-prompt branches, quote-heavy regressions for both Windows paths, and a mutual-exclusivity check) so the guards can't silently regress.
- Models: ships `deepseek-v4-pro` and `deepseek-v4-flash` as fallback hints (1M-token context windows, native thinking-mode streaming). Users can paste any other id (e.g. `nvidia-nim/deepseek-v4-pro`, `fireworks/deepseek-v4-flash`) via the Settings dialog's custom-model input.
- **Gotcha — auth state is not auto-detected.** DeepSeek TUI reads its API key from `~/.deepseek/config.toml` or `DEEPSEEK_API_KEY`. If the user hasn't run `deepseek auth set --provider deepseek` (or set the env var), the first run errors out with a non-actionable message. Detection currently only reports `available: true` based on the binary being on PATH; surface auth state via `deepseek doctor --json` in a follow-up.
- **Qoder CLI** runs with `--permission-mode bypass_permissions` for non-interactive web execution and is scoped by the daemon's cwd plus explicit absolute `--add-dir` entries.
- **API fallback** is the one case we own. We implement a whitelist: only `Read`, `Write`, `Edit` tools, all rooted at the artifact cwd. Network access is off.
The daemon never grants more authority to an agent than it had on its own. We don't run the agent in a privileged mode "for convenience."
Each adapter is a separate module so community contributions can add new ones without touching core daemon code.
## 12. Open questions
- **Nested agents.** What if Claude Code's agent itself spawns a subagent? We receive events from the outer process only. v1 policy: surface only top-level events; summarize subagent activity as "sub-task" placeholder.
- **Billing awareness.** Some agents bill per message, some per token. OD doesn't track cost in MVP; v1 adds an optional "usage" event from adapters that expose it.
- **Docker-contained agents.** Some users run Claude Code in a container. Adapter needs a "remote" mode — probably same interface but talks over SSH. Phase 2+.
