# Simulation Implementation Phases Status: implementation plan for `specs/simulation/simulation.md`. The full simulation architecture is intentionally broad. This document breaks it into phases that can be implemented and reviewed incrementally. ## Phase 1: Control Surface And Observability Goal: start the normal app in simulation mode and inspect/drive the TUI through an external WebSocket driver. This phase proves the core shape without swapping every foundational layer yet. Implementation checklist: - [x] Add `OPENCODE_DRIVE=` activation in V1/full-TUI startup. - [x] Add simulation trace service with in-memory append-only records. - [x] Add OpenTUI UI state extraction for screen, focus, elements, and generated actions. - [x] Add OpenTUI UI action execution for typing, keys, enter, arrows, focus, and click. - [x] Add reusable JSON-RPC WebSocket server at the manifest's UI endpoint. - [x] Add `simulation.handshake` protocol, role, identity, version, and capability negotiation to both control endpoints. - [x] Expose `ui.state`, `ui.action`, `ui.render`. - [x] Expose `trace.list`, `trace.clear`, `trace.export`. - [x] Wire visible V1/full-TUI renderer path through the same action protocol. - [ ] Verify a local driver can inspect state and execute a real TUI input. Scope: - Add `OPENCODE_DRIVE=` activation. - Start a TUI-owned JSON-RPC WebSocket server at the manifest's UI endpoint. - Expose `ui.state`, `ui.action`, `ui.render`. - Use the old simulation action model: type text, press keys, press enter, arrows, focus, click. - Support fake OpenTUI renderer and visible renderer through the same action protocol. - Add in-memory append-only trace with `trace.list`, `trace.clear`, `trace.export`. - Record UI observations, generated actions, executed actions, errors, and render/stabilization events. Done when: - `OPENCODE_DRIVE= bun run dev` starts the normal app and UI drive server. - A local driver can connect to the WebSocket. - The driver can inspect current screen/elements/actions. - The driver can execute real TUI inputs. - The trace shows observations and actions. Out of scope: - Backend layer replacement. - Model-based runner. - Generated plugin config. - Deterministic replay tests. ## Phase 2: Foundational Simulation Layers Goal: make the app safe and controlled by swapping the lowest layers, not app logic. Implementation checklist: - [x] Add `packages/simulation/src/backend` as the home for backend simulation layer replacements, exported from `backend/index.ts` as `simulationReplacements`; `@opencode-ai/simulation` is private/non-published and depends on logic/framework packages (`core`, `llm`, `effect`, OpenTUI), while `server` and `tui` consume it. - [x] Wire simulation replacements through the server's `makeRoutes` via `Layer.unwrap` + dynamic `import("@opencode-ai/simulation/backend")` gated on `OPENCODE_SIMULATE`, so the simulation module is never loaded eagerly and `makeRoutes` stays synchronous. - [x] Implement in-memory `FileSystem.FileSystem` (`simulation/filesystem.ts`) replacing the `NodeFileSystem` platform node. Backed by a flat path map; implements the operations the app uses (stat, access, chmod, realPath, read/write file, make/read directory, remove, rename, copy, copyFile, temp dirs, read-only open handles); unused operations die with a clear defect; `watch` fails as unsupported. - [x] Root the fake filesystem at `process.cwd()` at layer-build time. The anchor is a real, empty host directory the runner creates and cds into. - [x] Deny host filesystem escapes loudly: content/mutation operations outside the root fail with `PermissionDenied` simulation errors. Probe operations (`stat`/`access`/`exists`) report `NotFound` outside the root so walk-up loops (project discovery, `findUp`, `globUp`) terminate naturally. - [x] Add `SimulationFSUtil` replacement (`simulation/fs-util.ts`): wraps the real `FSUtil` layer and reroutes `readDirectoryEntries`, `glob`, and `globUp` — which bypass the injected `FileSystem` via node `fs/promises` and the `glob` package — through the simulated filesystem. - [x] Fix `LayerNode.hoist` conflict detection to compare node implementations instead of object identity; replacement rewriting produces dependency-rewritten copies of the same node, which previously false-positived as "conflicting implementations". - [x] Add snapshot seeding from `OPENCODE_SIMULATE_STATE`: `files/` contents of the snapshot directory are read from the host once at layer-build time and seeded into the in-memory tree joined onto the anchor root. - [x] Verify end to end: `opencode serve` boots with `OPENCODE_SIMULATE=1` + `OPENCODE_SIMULATE_STATE` + path/DB env seams (`OPENCODE_CONFIG_DIR`, `OPENCODE_TEST_HOME`, `OPENCODE_DB=:memory:`); `fs.list`/`fs.read` observe only seeded in-memory files; the anchor directory on the host remains empty after the run. - [ ] Create the anchor directory + `chdir` + env seam setup automatically in CLI startup when simulation mode is enabled (currently set manually by the runner; a full run needs `OPENCODE_SIMULATE_STATE`, `OPENCODE_CONFIG_DIR`, `OPENCODE_TEST_HOME`, `OPENCODE_DB=:memory:`, and `XDG_*_HOME` pointed into the anchor, plus Bun's `--preload=@opentui/solid/preload` when launched outside `packages/cli`). - [ ] Assert the anchor directory is still empty at the end of the run (KV/log/flock still write through real XDG paths; they are contained in the anchor by the env seams but not yet in-memory). - [x] Add run-local simulated network (`packages/simulation/src/backend/network.ts`): replaces the `httpClient` platform node, resolves outbound HTTP against routes supplied at acquisition, denies unknown destinations loudly, and keeps an isolated bounded request log timestamped through Effect `Clock` (design: `simulated-network-llm.md`). - [x] Add a simulated model provider behind the OpenAI route (`simulated-provider.ts` + `openai.ts`): real provider requests call `SimulatedProvider.Service.stream`; the Drive adapter streams response events back as schema-checked OpenAI Chat SSE consumed by the real protocol pipeline. - [x] Scope the backend Drive control WebSocket, pending provider invocations, queues, and request fibers to `SimulatedProvider.layerDrive`. JSON-RPC remains at the named manifest's backend endpoint: `llm.attach` replays pending invocations; `llm.chunk`, `llm.finish`, `llm.disconnect`, and `llm.pending` control them; `llm.request` reports provider-native requests. - [x] Scope the frontend Drive control WebSocket, request queue, renderer, and optional recording timeline to the TUI Effect scope. Server shutdown and request interruption precede renderer destruction; timeline finalization runs last and remains explicitly finishable through `ui.recording.finish`. - [x] Decode Drive manifests through Effect `Config`, `FileSystem`, and `Schema`, with typed config, not-found, read, and decode failures. - [x] Answer `https://models.dev/api.json` with an empty catalog in the simulated network; providers come from seeded config (`opencode.json` in the snapshot defines an openai-compatible provider with a dummy `apiKey`, which passes the catalog availability gate and resolves onto the real openai-chat route). - [x] Fix `buildLocationServiceMap` to apply replacements when compiling hoisted global nodes; platform-node replacements (filesystem, httpClient) were silently ignored inside hoisted globals. - [x] Verify end to end headless (real route stack in-process + backend control WS: prompt -> `llm.request` -> driver chunks -> assistant message contains driver text; script: `packages/server/script/e2e-sim.ts`) and through the TUI (fake renderer, both sockets: type + submit via TUI WS, answer `llm.request` via backend WS, assistant reply rendered on screen; script: `packages/tui/script/sim-llm-driver.ts`). - [ ] Add simulated process registry (shell via `just-bash`, minimal fake `git`, deny unsupported spawns). - [ ] Trace filesystem, process, and simulated provider activity (network requests are traced in the backend network log ring buffer; provider trace records still need adding on the backend control server). Scope: - Wire simulation replacements through `AppNodeBuilder.build(...)` and `AppNodeBuilderV1.build(...)`. - Create a real, empty anchor directory (`mkdtemp`) and `process.chdir` into it before any command resolves its working directory; skip creation when the runner already spawned the app inside an anchor. - Root the in-memory filesystem at `process.cwd()` (the anchor). No cwd monkey-patching: cwd, `$PWD`, and `path.resolve()` stay truthful. - Add snapshot loading from `OPENCODE_SIMULATE_STATE`: read the snapshot directory once at startup and seed the in-memory filesystem (snapshot `files/` paths joined onto the anchor root), config, env, and optional LLM/network state from it. - Route config/data/state/cache/temp paths into the simulated space using existing env seams (`OPENCODE_CONFIG_DIR`, `OPENCODE_TEST_HOME`, `OPENCODE_DB=:memory:`), set before `packages/core/src/global.ts` import-time path setup runs. - Deny host filesystem escapes loudly (paths outside the anchor root fail with typed simulation errors). - Assert the anchor directory on the host is still empty at the end of the run; anything written there means a code path bypassed the simulated filesystem. - Add simulated network registry and deny unknown external network by default. - Add scriptable LLM boundary. - Add simulated process registry: - shell through `just-bash` against the simulated filesystem. - minimal fake `git` support for discovery/status paths. - deny unsupported process spawns. - Add simulation-gated backend control routes, proxied only through the frontend WebSocket. - Expose backend methods through the frontend server: filesystem seed/write, network register, LLM enqueue, backend snapshot. - Trace filesystem, network, LLM, process, and backend control activity. Done when: - Unknown network fails with a simulation error. - Host filesystem escape fails with a simulation error. - The anchor directory on the host is empty after a run. - The app boots from a snapshot directory via `OPENCODE_SIMULATE_STATE` and observes the seeded project files, config, and env through normal app paths. - A driver can seed a project filesystem. - A driver can enqueue an LLM script and submit a prompt through the TUI. - The real session/tool path consumes the scripted LLM behavior. - Shell commands use `just-bash`; unsupported process spawns fail. - Trace contains backend activity and snapshots. Out of scope: - Model-based generation. - Generated plugin config state. - Shrinking. ## Phase 3: Generated Config And Model-Based Runner Goal: explore different app states using generated commands and plugin-provided config state. Scope: - Add generated simulation plugins as the primary config-state generation mechanism. - Support generated plugin domains for: - agents and defaults. - provider/model availability. - tool definitions and scripted tool behavior. - MCP-like capabilities or endpoints. - permission policies. - instructions/system-context-like inputs where supported. - workspace/project adapters where supported. - Add runner commands to generate, enable, disable, and inspect generated plugin state. - Build a custom external model-based runner, not `fast-check` yet. - Runner command shape: precondition, execute, model update, postcondition. - Runner model tracks only high-level observational state: screen category, prompt availability, sessions, files, queued LLM scripts, generated plugins, backend status, idle expectation. - Generate valid command sequences from model state and current `ui.state.actions`. - Record seed, command distribution, precondition rejections, generated plugin/config domain coverage, UI action coverage, and backend event coverage. Done when: - A seeded runner can generate a short valid exploration. - The runner can generate plugin-provided config state without generating large arbitrary config files. - The app loads and observes generated plugin state through normal plugin/config paths. - The runner can type and submit prompts through the TUI using generated actions. - Basic properties run after commands: no crash, no unknown network, no host FS escape, coherent stabilized state. - Trace export includes enough state to replay the generated run later. Out of scope: - Shrinking. - Coverage-guided mutation corpus. - Differential testing. - CI randomized runs. ## Phase 4: Replay, Promotion, And Campaigns Goal: turn exploratory simulation into durable tests and prepare for larger campaigns. Scope: - Add replay from exported trace. - Add deterministic replay test generation from successful or failing traces. - Add stronger trace schema validation. - Add property families beyond no-crash: - durable prompt admission is not lost. - no duplicated visible message IDs. - no orphan tool results. - queue/steer semantics hold at stabilization boundaries. - interrupt/resume does not duplicate promoted inputs. - Add corpus storage for interesting traces. - Add simple coverage/novelty scoring over UI states, backend event types, tool outcomes, generated config domains, and errors. - Add long-running campaign mode outside normal CI. Done when: - A trace from Phase 3 can be replayed deterministically. - A trace can be promoted to a normal test fixture. - Campaign runs can collect interesting traces without committing randomized tests to CI. - Failures produce a compact reproduction command and trace export. Out of scope: - Full shrinking. - Deterministic scheduler/clock control. - Parallel campaigns. - Differential testing across app versions. ## Later Work - Shrinking failed traces. - Coverage-guided mutation of structured traces. - `fast-check` integration if the custom runner becomes too limited. - Differential testing across versions, renderers, storage modes, or scheduler policies. - Deterministic clock/random/scheduler control. - Parallel isolated workers. - Model-generated properties with validity/soundness/coverage scoring.