Initial CodeCraft: web-based coding harness for AI models
Rust backend (axum/tokio): agent loop with streaming, tools (fs, bash, web_fetch, todo, ask_user, subagents, skills, craft snapshots/compare), permissions with modes and rules, Anthropic + OpenAI-compatible providers, MCP client (stdio/HTTP, elicitation), SQLite sessions, usage statistics, compaction, commented TOML config editable via toml_edit. React PWA: chat with live streaming, permission/question cards, modes (build/plan/craft), settings for providers/models/prices/MCP/permissions, raw config editor, statistics dashboard, i18n (en/de). Docker setup. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
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# =============================================================================
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# CodeCraft – configuration
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# =============================================================================
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#
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# This file is the single source of truth for the server. Everything here can
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# also be edited in the web UI (Settings). The UI edits this file in place and
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# keeps your comments and formatting intact.
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#
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# Location: $CODECRAFT_CONFIG, otherwise <data_dir>/config.toml (Docker: /data/config.toml)
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#
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# Secrets: any string value may reference environment variables with ${NAME},
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# e.g. api_key = "${ANTHROPIC_API_KEY}". Prefer this over literal keys – keys
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# entered in the UI are stored here in plain text.
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# =============================================================================
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[server]
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# Address the HTTP server listens on.
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bind = "0.0.0.0:8787"
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# Root directory the agents may work in. Sessions pick a project folder below it.
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# Docker: mount your projects here (see docker-compose.yml).
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workspace = "/workspace"
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# Where sessions (SQLite) and runtime state are stored.
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data_dir = "/data"
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# Access token for the web UI and API. Leave empty to disable auth (only do
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# this on localhost!). Recommended: auth_token = "${CODECRAFT_TOKEN}"
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auth_token = "${CODECRAFT_TOKEN}"
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# Default model for new sessions, as "<provider>/<model>".
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default_model = "anthropic/claude-sonnet-5-5"
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# Cheap/fast model for titles and history compaction. Falls back to default_model.
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small_model = "anthropic/claude-haiku-5-5"
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# Compact the conversation automatically when the context is this full (0.0–1.0).
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auto_compact_threshold = 0.85
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# Currency label for the cost statistics (prices below are in this currency).
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currency = "USD"
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# -----------------------------------------------------------------------------
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# Providers
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# -----------------------------------------------------------------------------
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# kind = "anthropic" → Anthropic Messages API (and compatible endpoints)
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# kind = "openai" → OpenAI-compatible /chat/completions (Gemini, opencode Go,
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# fal, OpenRouter, Ollama, vLLM, llama.cpp, LM Studio, ...)
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#
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# models: optional list. If empty, the model list is fetched from <base_url>/models.
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# Per-model options: context (tokens), max_output (tokens), reasoning (bool),
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# vision (bool, can read images), effort ("low" | "medium" | "high" | "xhigh" | "max").
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#
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# Prices (per 1M tokens, used for the statistics):
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# input_price, output_price, cache_read_price, cache_write_price
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# Cache prices default to input_price when omitted. Costs are stored per request,
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# so changing a price only affects future requests.
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#
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# Authentication: by default "Authorization: Bearer <api_key>" (openai) or
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# "x-api-key: <api_key>" (anthropic). Override with auth_header / auth_prefix.
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# Extra static headers: headers = { "X-Foo" = "bar" }
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# -----------------------------------------------------------------------------
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[providers.anthropic]
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kind = "anthropic"
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base_url = "https://api.anthropic.com/v1"
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api_key = "${ANTHROPIC_API_KEY}"
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# Current Claude models think adaptively; "effort" controls depth and cost.
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# Prices: Anthropic list prices in USD per 1M tokens (Nov 2026) – adjust if needed.
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models = [
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{ id = "claude-opus-5-5", context = 1000000, max_output = 64000, reasoning = true, vision = true, effort = "high",
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input_price = 4.0, output_price = 20.0, cache_read_price = 0.20, cache_write_price = 5.0 },
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{ id = "claude-sonnet-5-5", context = 1000000, max_output = 64000, reasoning = true, vision = true, effort = "medium",
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input_price = 2.0, output_price = 10.0, cache_read_price = 0.20, cache_write_price = 2.5 },
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{ id = "claude-haiku-5-5", context = 1000000, max_output = 32000, reasoning = true, vision = true, effort = "low",
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input_price = 0.10, output_price = 0.50, cache_read_price = 0.01, cache_write_price = 0.125 },
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]
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# Google Gemini through its OpenAI-compatible endpoint.
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[providers.gemini]
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kind = "openai"
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base_url = "https://generativelanguage.googleapis.com/v1beta/openai"
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api_key = "${GEMINI_API_KEY}"
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models = [] # discovered automatically
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enabled = false # set to true once GEMINI_API_KEY is available
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# opencode Go subscription (OpenAI-compatible endpoint for most models).
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# Current model list: https://opencode.ai/inference/go/v1/models
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[providers.opencode-go]
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kind = "openai"
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base_url = "https://opencode.ai/inference/go/openai/v1"
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api_key = "${OPENCODE_API_KEY}"
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models = []
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enabled = false
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# fal.ai – OpenRouter-backed LLM router. fal expects "Authorization: Key <FAL_KEY>".
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# NOTE: verify base_url against the fal docs for your account.
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[providers.fal]
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kind = "openai"
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base_url = "https://fal.run/openrouter/router/openai/v1"
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api_key = "${FAL_KEY}"
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auth_prefix = "Key "
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models = [
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{ id = "google/gemini-2.5-flash", context = 1000000, max_output = 32000, vision = true },
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]
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enabled = false
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# Self-hosted (Ollama shown; vLLM/llama.cpp/LM Studio work the same way).
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# From inside Docker, the host is reachable as host.docker.internal.
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[providers.local]
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kind = "openai"
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base_url = "http://host.docker.internal:11434/v1"
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api_key = ""
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models = []
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enabled = false
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# -----------------------------------------------------------------------------
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# MCP servers
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# -----------------------------------------------------------------------------
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# type = "stdio" → command + args (+ env), started as a child process
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# type = "http" → Streamable HTTP endpoint (url + optional headers)
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# Tools appear to the model as mcp__<server>__<tool>.
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# MCP servers may ask you questions (elicitation); they show up in the UI.
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# -----------------------------------------------------------------------------
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# [mcp.trilium]
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# type = "http"
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# url = "https://notes.example.org/mcp"
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# headers = { Authorization = "Bearer ${TRILIUM_TOKEN}" }
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# [mcp.filesystem]
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# type = "stdio"
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# command = "npx"
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# args = ["-y", "@modelcontextprotocol/server-filesystem", "/workspace"]
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# env = {}
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# enabled = false
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# -----------------------------------------------------------------------------
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# Permissions
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# -----------------------------------------------------------------------------
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# For each tool: "allow" | "ask" | "deny". "ask" forwards the request to the UI.
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# MCP tools can be addressed as "mcp__<server>__<tool>" or "mcp__<server>__*".
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# Session permission modes in the UI override this:
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# default → these rules
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# accept_edits → file edits allowed without asking
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# bypass → everything allowed (use with care)
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# -----------------------------------------------------------------------------
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[permissions]
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read = "allow"
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glob = "allow"
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grep = "allow"
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list = "allow"
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todo_write = "allow"
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ask_user = "allow"
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task = "allow"
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write = "ask"
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edit = "ask"
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bash = "ask"
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web_fetch = "ask"
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browser_snapshot = "allow"
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image_compare = "allow"
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"mcp__*" = "ask"
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# Shell command patterns (glob, matched against the full command). First match wins.
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[permissions.bash_rules]
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"git status*" = "allow"
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"git diff*" = "allow"
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"git log*" = "allow"
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"ls*" = "allow"
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"pwd" = "allow"
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"rm -rf /*" = "deny"
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# -----------------------------------------------------------------------------
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# Agents (modes)
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# -----------------------------------------------------------------------------
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# Built-in: build (full access), plan (read-only, proposes a plan),
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# craft (study → build → check → ready), and subagents
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# general + explore used by the "task" tool.
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# Define your own or override built-ins here. mode = "primary" shows up in the
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# mode switcher, mode = "subagent" is only available through the task tool.
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# -----------------------------------------------------------------------------
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# [agents.reviewer]
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# mode = "subagent"
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# description = "Reviews code changes for bugs and style issues."
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# model = "anthropic/claude-opus-5-5" # optional, otherwise session model
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# tools = ["read", "glob", "grep", "bash"] # optional, default: all tools
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# prompt = """
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# You are a meticulous code reviewer. ...
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# """
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# -----------------------------------------------------------------------------
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# Craft mode
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# -----------------------------------------------------------------------------
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[craft]
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# Headless Chromium binary used to study websites and check builds.
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chromium = "chromium"
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# Screen widths used for screenshots and comparisons.
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widths = [390, 768, 1440]
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# Clean room: only what a visitor sees (screenshots, visible text, layout).
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# Set to false for "deep" mode (page source and scripts may be read).
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clean_room = true
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