Advanced Configuration

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Use these options when you need more control over providers, policies, and integrations. For a quick start, see Config basics.

For background on project guidance, reusable capabilities, custom slash commands, subagent workflows, and integrations, see Customization. For configuration keys, see Configuration Reference.

Profiles

Profiles let you save named configuration layers and switch between them from the CLI. When you pass `--profile profile-name`, Codex loads `~/.codex/config.toml`, then overlays `~/.codex/profile-name.config.toml`. Profile names can contain letters, numbers, hyphens, and underscores.

Create a separate TOML file for each profile. Use top-level config keys in the profile file; don’t nest them under `[profiles.profile-name]`.

# ~/.codex/deep-review.config.toml
model = "gpt-5.5"
model_reasoning_effort = "xhigh"
approval_policy = "on-request"
model_catalog_json = "/Users/me/.codex/model-catalogs/deep-review.json"

codex --profile deep-review
codex exec --profile deep-review "review this change"

Because the profile file is a layer above your base user config and below project and CLI config, it only needs the values that differ from your base config. Profile files can also override `model_catalog_json`; Codex uses the profile value when both files set it.

In Codex 0.134.0 and later, `--profile` no longer reads `[profiles.profile-name]`from `config.toml`, and the top-level `profile = "profile-name"` selector is no longer supported. Move legacy profile settings into `~/.codex/profile-name.config.toml`, then remove the matching `[profiles.profile-name]` table and `profile = "profile-name"` selector from `config.toml`.

One-off overrides from the CLI

In addition to editing `~/.codex/config.toml`, you can override configuration for a single run from the CLI:

• Prefer dedicated flags when they exist (for example, `--model`).
• Use `-c` / `--config` when you need to override an arbitrary key.

Examples:

# Dedicated flag
codex --model gpt-5.4
Generic key/value override (value is TOML, not JSON)
codex --config model='"gpt-5.4"'
codex --config sandbox_workspace_write.network_access=true
codex --config 'shell_environment_policy.include_only=["PATH","HOME"]'

Notes:

• Keys can use dot notation to set nested values (for example, `mcp_servers.context7.enabled=false`).
• `--config` values are parsed as TOML. When in doubt, quote the value so your shell doesn’t split it on spaces.
• If the value can’t be parsed as TOML, Codex treats it as a string.

Config and state locations

Codex stores its local state under `CODEX_HOME` (defaults to `~/.codex`).

Common files you may see there:

• `config.toml` (your local configuration)
• `auth.json` (if you use file-based credential storage) or your OS keychain/keyring
• `history.jsonl` (if history persistence is enabled)
• Other per-user state such as logs and caches

For authentication details (including credential storage modes), see Authentication. For the full list of configuration keys, see Configuration Reference.

For shared defaults, rules, and skills checked into repos or system paths, see Team Config.

If you just need to point the built-in OpenAI provider at an LLM proxy, router, or data-residency enabled project, set `openai_base_url` in `config.toml` instead of defining a new provider. This changes the base URL for the built-in `openai` provider without requiring a separate `model_providers.<id>` entry.

openai_base_url = "https://us.api.openai.com/v1"

Project config files (`.codex/config.toml`)

In addition to your user config, Codex reads project-scoped overrides from `.codex/config.toml` files inside your repo. Codex walks from the project root to your current working directory and loads every `.codex/config.toml` it finds. If multiple files define the same key, the closest file to your working directory wins.

For security, Codex loads project-scoped config files only when the project is trusted. If the project is untrusted, Codex ignores project `.codex/` layers, including `.codex/config.toml`, project-local hooks, and project-local rules. User and system layers remain separate and still load.

Relative paths inside a project config (for example, `model_instructions_file`) are resolved relative to the `.codex/` folder that contains the `config.toml`.

Project config files can’t override settings that redirect credentials, alter host-owned app request metadata, change provider auth, select config profiles, or run machine-local notification/telemetry commands. Codex ignores the following keys in project-local `.codex/config.toml` and prints a startup warning when it sees them: `openai_base_url`, `chatgpt_base_url`, `apps_mcp_product_sku`, `model_provider`, `model_providers`, `notify`, `profile`, `profiles`, `experimental_realtime_ws_base_url`, and `otel`. Set provider, notification, and telemetry keys in your user-level `~/.codex/config.toml`; select config profiles with `--profile profile-name`and `~/.codex/profile-name.config.toml`.

Hooks

Codex can also load lifecycle hooks from either `hooks.json` files or inline `[hooks]` tables in `config.toml` files that sit next to active config layers.

In practice, the four most useful locations are:

• `~/.codex/hooks.json`
• `~/.codex/config.toml`
• `<repo>/.codex/hooks.json`
• `<repo>/.codex/config.toml`

Project-local hooks load only when the project `.codex/` layer is trusted. User-level hooks remain independent of project trust.

Inline TOML hooks use the same event structure as `hooks.json`:

[[hooks.PreToolUse]]
matcher = "^Bash$"
[[hooks.PreToolUse.hooks]]
type = "command"
command = '/usr/bin/python3 "$(git rev-parse --show-toplevel)/.codex/hooks/pre_tool_use_policy.py"'
timeout = 30
statusMessage = "Checking Bash command"

If a single layer contains both `hooks.json` and inline `[hooks]`, Codex loads both and warns. Prefer one representation per layer.

For the current event list, input fields, output behavior, and limitations, see Hooks.

Agent roles (`[agents]` in `config.toml`)

For subagent role configuration (`[agents]` in `config.toml`), see Subagents.

Project root detection

Codex discovers project configuration (for example, `.codex/` layers and `AGENTS.md`) by walking up from the working directory until it reaches a project root.

By default, Codex treats a directory containing `.git` as the project root. To customize this behavior, set `project_root_markers` in `config.toml`:

# Treat a directory as the project root when it contains any of these markers.
project_root_markers = [".git", ".hg", ".sl"]

Set `project_root_markers = []` to skip searching parent directories and treat the current working directory as the project root.

Custom model providers

A model provider defines how Codex connects to a model (base URL, wire API, authentication, and optional HTTP headers). Custom providers can’t reuse the reserved built-in provider IDs: `openai`, `ollama`, and `lmstudio`.

Define additional providers and point `model_provider` at them:

model = "gpt-5.4"
model_provider = "proxy"
[model_providers.proxy]
name = "OpenAI using LLM proxy"
base_url = "http://proxy.example.com"
env_key = "OPENAI_API_KEY"
[model_providers.local_ollama]
name = "Ollama"
base_url = "http://localhost:11434/v1"
[model_providers.mistral]
name = "Mistral"
base_url = "https://api.mistral.ai/v1"
env_key = "MISTRAL_API_KEY"

Add request headers when needed:

[model_providers.example]
http_headers = { "X-Example-Header" = "example-value" }
env_http_headers = { "X-Example-Features" = "EXAMPLE_FEATURES" }

Use command-backed authentication when a provider needs Codex to fetch bearer tokens from an external credential helper:

[model_providers.proxy]
name = "OpenAI using LLM proxy"
base_url = "https://proxy.example.com/v1"
wire_api = "responses"
[model_providers.proxy.auth]
command = "/usr/local/bin/fetch-codex-token"
args = ["--audience", "codex"]
timeout_ms = 5000
refresh_interval_ms = 300000

The auth command receives no `stdin` and must print the token to stdout. Codex trims surrounding whitespace, treats an empty token as an error, and refreshes proactively at `refresh_interval_ms`; set `refresh_interval_ms = 0` to refresh only after an authentication retry. Don’t combine `[model_providers.<id>.auth]` with `env_key`, `experimental_bearer_token`, or `requires_openai_auth`.

Amazon Bedrock provider

Codex includes a built-in `amazon-bedrock` model provider. Set it directly as `model_provider`; unlike custom providers, this built-in provider supports only the nested AWS profile and region overrides.

model_provider = "amazon-bedrock"
model = "<bedrock-model-id>"
[model_providers.amazon-bedrock.aws]
profile = "default"
region = "eu-central-1"

If you omit `profile`, Codex uses the standard AWS credential chain. Set `region` to the supported Bedrock region that should handle requests.

For the full setup flow, authentication options, supported models, and feature availability, see Use Codex with Amazon Bedrock.

OSS mode (local providers)

Codex can run against a local “open source” provider (for example, Ollama or LM Studio) when you pass `--oss`. If you pass `--oss` without specifying a provider, Codex uses `oss_provider` as the default.

# Default local provider used with `--oss`
oss_provider = "ollama" # or "lmstudio"

Azure provider and per-provider tuning

[model_providers.azure]
name = "Azure"
base_url = "https://YOUR_PROJECT_NAME.openai.azure.com/openai"
env_key = "AZURE_OPENAI_API_KEY"
query_params = { api-version = "2025-04-01-preview" }
wire_api = "responses"
request_max_retries = 4
stream_max_retries = 10
stream_idle_timeout_ms = 300000

To change the base URL for the built-in OpenAI provider, use `openai_base_url`; don’t create `[model_providers.openai]`, because you can’t override built-in provider IDs.

ChatGPT customers using data residency

Projects created with data residency enabled can create a model provider to update the base\_url with the correct prefix.

model_provider = "openaidr"
[model_providers.openaidr]
name = "OpenAI Data Residency"
base_url = "https://us.api.openai.com/v1" # Replace 'us' with domain prefix

Model reasoning, verbosity, and limits

model_reasoning_summary = "none"          # Disable summaries
model_verbosity = "low"                   # Shorten responses
model_supports_reasoning_summaries = true # Force reasoning
model_context_window = 128000             # Context window size

`model_verbosity` applies only to providers using the Responses API. Chat Completions providers will ignore the setting.

Approval policies and sandbox modes

Pick approval strictness (affects when Codex pauses) and sandbox level (affects file/network access).

For operational details to keep in mind while editing `config.toml`, see Common sandbox and approval combinations, Protected paths in writable roots, and Network access.

For beta permission profiles that configure filesystem and network access together, see Permissions.

You can also use a granular approval policy (`approval_policy = { granular = { ... } }`) to allow or auto-reject individual prompt categories. This is useful when you want normal interactive approvals for some cases but want others, such as `request_permissions` or skill-script prompts, to fail closed automatically.

Set `approvals_reviewer = "auto_review"` to route eligible interactive approval requests through automatic review. This changes the reviewer, not the sandbox boundary.

Use `[auto_review].policy` for local reviewer policy instructions. Managed `guardian_policy_config` takes precedence.

approval_policy = "untrusted"   # Other options: on-request, never, or { granular = { ... } }
approvals_reviewer = "user"     # Or "auto_review" for automatic review
sandbox_mode = "workspace-write"
allow_login_shell = false       # Optional hardening: disallow login shells for shell tools
Example granular approval policy:
approval_policy = { granular = {
  sandbox_approval = true,
  rules = true,
  mcp_elicitations = true,
  request_permissions = false,
  skill_approval = false
} }
[sandbox_workspace_write]
exclude_tmpdir_env_var = false  # Allow $TMPDIR
exclude_slash_tmp = false       # Allow /tmp
writable_roots = ["/Users/YOU/.pyenv/shims"]
network_access = false          # Opt in to outbound network
[auto_review]
policy = """
Use your organization's automatic review policy.
"""

Named permission profiles

For built-in profiles, custom profile syntax, and the full filesystem and network configuration model, see Permissions.

For the complete key list and requirements constraints, see Configuration Reference and Managed configuration.

In workspace-write mode, some environments keep `.git/` and `.codex/`read-only even when the rest of the workspace is writable. This is why commands like `git commit` may still require approval to run outside the sandbox. If you want Codex to skip specific commands (for example, block `git commit` outside the sandbox), use rules.

Disable sandboxing entirely (use only if your environment already isolates processes):

sandbox_mode = "danger-full-access"

Shell environment policy

`shell_environment_policy` controls which environment variables Codex passes to any subprocess it launches (for example, when running a tool-command the model proposes). Start from a clean start (`inherit = "none"`) or a trimmed set (`inherit = "core"`), then layer on excludes, includes, and overrides to avoid leaking secrets while still providing the paths, keys, or flags your tasks need.

[shell_environment_policy]
inherit = "none"
set = { PATH = "/usr/bin", MY_FLAG = "1" }
ignore_default_excludes = false
exclude = ["AWS_*", "AZURE_*"]
include_only = ["PATH", "HOME"]

Patterns are case-insensitive globs (`*`, `?`, `[A-Z]`); `ignore_default_excludes = false` keeps the automatic KEY/SECRET/TOKEN filter before your includes/excludes run.

MCP servers

See the dedicated MCP documentation for configuration details.

Observability and telemetry

Enable OpenTelemetry (OTel) log export to track Codex runs (API requests, SSE/events, prompts, tool approvals/results). Disabled by default; opt in via `[otel]`:

[otel]
environment = "staging"   # defaults to "dev"
exporter = "none"         # set to otlp-http or otlp-grpc to send events
log_user_prompt = false   # redact user prompts unless explicitly enabled

Choose an exporter:

[otel]
exporter = { otlp-http = {
  endpoint = "https://otel.example.com/v1/logs",
  protocol = "binary",
  headers = { "x-otlp-api-key" = "${OTLP_TOKEN}" }
}}

[otel]
exporter = { otlp-grpc = {
  endpoint = "https://otel.example.com:4317",
  headers = { "x-otlp-meta" = "abc123" }
}}

If `exporter = "none"` Codex records events but sends nothing. Exporters batch asynchronously and flush on shutdown. Event metadata includes service name, CLI version, env tag, conversation id, model, sandbox/approval settings, and per-event fields (see Config Reference).

What gets emitted

Codex emits structured log events for runs and tool usage. Representative event types include:

• `codex.conversation_starts` (model, reasoning settings, sandbox/approval policy)
• `codex.api_request` (attempt, status/success, duration, and error details)
• `codex.sse_event` (stream event kind, success/failure, duration, plus token counts on `response.completed`)
• `codex.websocket_request` and `codex.websocket_event` (request duration plus per-message kind/success/error)
• `codex.user_prompt` (length; content redacted unless explicitly enabled)
• `codex.tool_decision` (approved/denied and whether the decision came from config vs user)
• `codex.tool_result` (duration, success, output snippet)

OTel metrics emitted

When the OTel metrics pipeline is enabled, Codex emits counters and duration histograms for API, stream, and tool activity.

Each metric below also includes default metadata tags: `auth_mode`, `originator`, `session_source`, `model`, and `app.version`.

| Metric | Type | Fields | Description | | ------------------------------------ | --------- | --------------- | ----------------------------------------------------------------- | | codex.api\_request | counter | status, success | API request count by HTTP status and success/failure. | | codex.api\_request.duration\_ms | histogram | status, success | API request duration in milliseconds. | | codex.sse\_event | counter | kind, success | SSE event count by event kind and success/failure. | | codex.sse\_event.duration\_ms | histogram | kind, success | SSE event processing duration in milliseconds. | | codex.websocket.request | counter | success | WebSocket request count by success/failure. | | codex.websocket.request.duration\_ms | histogram | success | WebSocket request duration in milliseconds. | | codex.websocket.event | counter | kind, success | WebSocket message/event count by type and success/failure. | | codex.websocket.event.duration\_ms | histogram | kind, success | WebSocket message/event processing duration in milliseconds. | | codex.tool.call | counter | tool, success | Tool invocation count by tool name and success/failure. | | codex.tool.call.duration\_ms | histogram | tool, success | Tool execution duration in milliseconds by tool name and outcome. |

For more security and privacy guidance around telemetry, see Security.

Metrics

By default, Codex periodically sends a small amount of anonymous usage and health data back to OpenAI. This helps detect when Codex isn’t working correctly and shows what features and configuration options are being used, so the Codex team can focus on what matters most. These metrics don’t contain any personally identifiable information (PII). Metrics collection is independent of OTel log/trace export.

If you want to disable metrics collection entirely across Codex surfaces on a machine, set the analytics flag in your config:

[analytics]
enabled = false

Each metric includes its own fields plus the default context fields below.

#### Default context fields (applies to every event/metric)

• `auth_mode`: `swic` | `api` | `unknown`.
• `model`: name of the model used.
• `app.version`: Codex version.

#### Metrics catalog

Each metric includes the required fields plus the default context fields above. Metric names below omit the `codex.` prefix. Most metric names are centralized in `codex-rs/otel/src/metrics/names.rs`; feature-specific metrics emitted outside that file are included here too. If a metric includes the `tool` field, it reflects the internal tool used (for example, `apply_patch` or `shell`) and doesn’t contain the actual shell command or patch `codex` is trying to apply.

#### Runtime and model transport

| Metric | Type | Fields | Description | | -------------------------------------------------- | --------- | ---------------- | ------------------------------------------------------------ | | api\_request | counter | status, success | API request count by HTTP status and success/failure. | | api\_request.duration\_ms | histogram | status, success | API request duration in milliseconds. | | sse\_event | counter | kind, success | SSE event count by event kind and success/failure. | | sse\_event.duration\_ms | histogram | kind, success | SSE event processing duration in milliseconds. | | websocket.request | counter | success | WebSocket request count by success/failure. | | websocket.request.duration\_ms | histogram | success | WebSocket request duration in milliseconds. | | websocket.event | counter | kind, success | WebSocket message/event count by type and success/failure. | | websocket.event.duration\_ms | histogram | kind, success | WebSocket message/event processing duration in milliseconds. | | responses\_api\_overhead.duration\_ms | histogram | | Responses API overhead timing from WebSocket responses. | | responses\_api\_inference\_time.duration\_ms | histogram | | Responses API inference timing from WebSocket responses. | | responses\_api\_engine\_iapi\_ttft.duration\_ms | histogram | | Responses API engine IAPI time-to-first-token timing. | | responses\_api\_engine\_service\_ttft.duration\_ms | histogram | | Responses API engine service time-to-first-token timing. | | responses\_api\_engine\_iapi\_tbt.duration\_ms | histogram | | Responses API engine IAPI time-between-token timing. | | responses\_api\_engine\_service\_tbt.duration\_ms | histogram | | Responses API engine service time-between-token timing. | | transport.fallback\_to\_http | counter | from\_wire\_api | WebSocket-to-HTTP fallback count. | | remote\_models.fetch\_update.duration\_ms | histogram | | Time to fetch remote model definitions. | | remote\_models.load\_cache.duration\_ms | histogram | | Time to load the remote model cache. | | startup\_prewarm.duration\_ms | histogram | status | Startup prewarm duration by outcome. | | startup\_prewarm.age\_at\_first\_turn\_ms | histogram | status | Startup prewarm age when the first real turn resolves it. | | cloud\_requirements.fetch.duration\_ms | histogram | | Workspace-managed cloud requirements fetch duration. | | cloud\_requirements.fetch\_attempt | counter | See note | Workspace-managed cloud requirements fetch attempts. | | cloud\_requirements.fetch\_final | counter | See note | Final workspace-managed cloud requirements fetch outcome. | | cloud\_requirements.load | counter | trigger, outcome | Workspace-managed cloud requirements load outcome. |

The `cloud_requirements.fetch_attempt` metric includes `trigger`, `attempt`, `outcome`, and `status_code` fields. The `cloud_requirements.fetch_final` metric includes `trigger`, `outcome`, `reason`, `attempt_count`, and `status_code` fields.

#### Turn and tool activity

| Metric | Type | Fields | Description | | -------------------------------------- | --------- | ---------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------- | | turn.e2e\_duration\_ms | histogram | | End-to-end time for a full turn. | | turn.ttft.duration\_ms | histogram | | Time to first token for a turn. | | turn.ttfm.duration\_ms | histogram | | Time to first model output item for a turn. | | turn.network\_proxy | counter | active, tmp\_mem\_enabled | Whether the managed network proxy was active for the turn. | | turn.memory | counter | read\_allowed, feature\_enabled, config\_use\_memories, has\_citations | Per-turn memory read availability and memory citation usage. | | turn.tool.call | histogram | tmp\_mem\_enabled | Number of tool calls in the turn. | | turn.token\_usage | histogram | token\_type, tmp\_mem\_enabled | Per-turn token usage by token type (total, input, cached\_input, output, or reasoning\_output). | | tool.call | counter | tool, success | Tool invocation count by tool name and success/failure. | | tool.call.duration\_ms | histogram | tool, success | Tool execution duration in milliseconds by tool name and outcome. | | tool.unified\_exec | counter | tty | Unified exec tool calls by TTY mode. | | approval.requested | counter | tool, approved | Tool approval request result (approved, approved\_with\_amendment, approved\_for\_session, denied, abort). | | mcp.call | counter | See note | MCP tool invocation result. | | mcp.call.duration\_ms | histogram | See note | MCP tool invocation duration. | | mcp.tools.list.duration\_ms | histogram | cache | MCP tool-list duration, including cache hit/miss state. | | mcp.tools.fetch\_uncached.duration\_ms | histogram | | Duration of MCP tool fetches that miss the cache. | | mcp.tools.cache\_write.duration\_ms | histogram | | Duration of Codex Apps MCP tool-cache writes. | | hooks.run | counter | hook\_name, source, status | Hook run count by hook name, source, and status. | | hooks.run.duration\_ms | histogram | hook\_name, source, status | Hook run duration in milliseconds. |

The `mcp.call` and `mcp.call.duration_ms` metrics include `status`; normal tool-call emissions also include `tool`, plus `connector_id` and `connector_name` when available. Blocked Codex Apps MCP calls may emit `mcp.call` with only `status`.

#### Threads, tasks, and features

| Metric | Type | Fields | Description | | ---------------------------------- | --------- | ----------------- | ----------------------------------------------------------------------------- | | feature.state | counter | feature, value | Feature values that differ from defaults (emit one row per non-default). | | status\_line | counter | | Session started with a configured status line. | | model\_warning | counter | | Warning sent to the model. | | thread.started | counter | is\_git | New thread created, tagged by whether the working directory is in a Git repo. | | conversation.turn.count | counter | | User/assistant turns per thread, recorded at the end of the thread. | | thread.fork | counter | source | New thread created by forking an existing thread. | | thread.rename | counter | | Thread renamed. | | thread.side | counter | source | Side conversation created. | | thread.skills.enabled\_total | histogram | | Number of skills enabled for a new thread. | | thread.skills.kept\_total | histogram | | Number of enabled skills kept after prompt rendering. | | thread.skills.truncated | histogram | | Whether skill rendering truncated the enabled skills list (1 or 0). | | task.compact | counter | type | Number of compactions per type (remote or local), including manual and auto. | | task.review | counter | | Number of reviews triggered. | | task.undo | counter | | Number of undo actions triggered. | | task.user\_shell | counter | | Number of user shell actions (! in the TUI for example). | | shell\_snapshot | counter | See note | Whether taking a shell snapshot succeeded. | | shell\_snapshot.duration\_ms | histogram | success | Time to take a shell snapshot. | | skill.injected | counter | status, skill | Skill injection outcomes by skill. | | plugins.startup\_sync | counter | transport, status | Curated plugin startup sync attempts. | | plugins.startup\_sync.final | counter | transport, status | Final curated plugin startup sync outcome. | | multi\_agent.spawn | counter | role | Agent spawns by role. | | multi\_agent.resume | counter | | Agent resumes. | | multi\_agent.nickname\_pool\_reset | counter | | Agent nickname pool resets. |

The `shell_snapshot` metric includes `success` and, on failures, `failure_reason`.

#### Memory and local state

| Metric | Type | Fields | Description | | ------------------------------ | --------- | ------------------- | -------------------------------------------------------- | | memory.phase1 | counter | status | Memory phase 1 job counts by status. | | memory.phase1.e2e\_ms | histogram | | End-to-end duration for memory phase 1. | | memory.phase1.output | counter | | Memory phase 1 outputs written. | | memory.phase1.token\_usage | histogram | token\_type | Memory phase 1 token usage by token type. | | memory.phase2 | counter | status | Memory phase 2 job counts by status. | | memory.phase2.e2e\_ms | histogram | | End-to-end duration for memory phase 2. | | memory.phase2.input | counter | | Memory phase 2 input count. | | memory.phase2.token\_usage | histogram | token\_type | Memory phase 2 token usage by token type. | | memories.usage | counter | kind, tool, success | Memory usage by kind, tool, and success/failure. | | external\_agent\_config.detect | counter | See note | External agent config detections by migration item type. | | external\_agent\_config.import | counter | See note | External agent config imports by migration item type. | | db.backfill | counter | status | Initial state DB backfill results (upserted, failed). | | db.backfill.duration\_ms | histogram | status | Duration of the initial state DB backfill. | | db.error | counter | stage | Errors during state DB operations. |

The `external_agent_config.detect` and `external_agent_config.import` metrics include `migration_type`; skills migrations also include `skills_count`.

#### Windows sandbox

| Metric | Type | Fields | Description | | -------------------------------------------------- | --------- | ----------------------------------- | ----------------------------------------------------- | | windows\_sandbox.setup\_success | counter | originator, mode | Windows sandbox setup successes. | | windows\_sandbox.setup\_failure | counter | originator, mode | Windows sandbox setup failures. | | windows\_sandbox.setup\_duration\_ms | histogram | result, originator, mode | Windows sandbox setup duration. | | windows\_sandbox.elevated\_setup\_success | counter | | Elevated Windows sandbox setup successes. | | windows\_sandbox.elevated\_setup\_failure | counter | See note | Elevated Windows sandbox setup failures. | | windows\_sandbox.elevated\_setup\_canceled | counter | See note | Canceled elevated Windows sandbox setup attempts. | | windows\_sandbox.elevated\_setup\_duration\_ms | histogram | result | Elevated Windows sandbox setup duration. | | windows\_sandbox.elevated\_prompt\_shown | counter | | Elevated sandbox setup prompt shown. | | windows\_sandbox.elevated\_prompt\_accept | counter | | Elevated sandbox setup prompt accepted. | | windows\_sandbox.elevated\_prompt\_use\_legacy | counter | | User chose legacy sandbox from the elevated prompt. | | windows\_sandbox.elevated\_prompt\_quit | counter | | User quit from the elevated prompt. | | windows\_sandbox.fallback\_prompt\_shown | counter | | Fallback sandbox prompt shown. | | windows\_sandbox.fallback\_retry\_elevated | counter | | User retried elevated setup from the fallback prompt. | | windows\_sandbox.fallback\_use\_legacy | counter | | User chose legacy sandbox from the fallback prompt. | | windows\_sandbox.fallback\_prompt\_quit | counter | | User quit from the fallback prompt. | | windows\_sandbox.legacy\_setup\_preflight\_failed | counter | See note | Legacy Windows sandbox setup preflight failure. | | windows\_sandbox.setup\_elevated\_sandbox\_command | counter | | Elevated sandbox setup command invoked. | | windows\_sandbox.createprocessasuserw\_failed | counter | error\_code, path\_kind, exe, level | Windows CreateProcessAsUserW failures. |

The elevated setup failure metrics include `code` and `message` when Windows setup failure details are available, and may include `originator` when emitted from the shared setup path. The `windows_sandbox.legacy_setup_preflight_failed` metric includes `originator` when emitted from the shared setup path, but fallback-prompt preflight failures may not include any fields.

Feedback controls

By default, Codex lets users send feedback from `/feedback`. To disable feedback collection across Codex surfaces on a machine, update your config:

[feedback]
enabled = false

When disabled, `/feedback` shows a disabled message and Codex rejects feedback submissions.

Hide or surface reasoning events

If you want to reduce noisy “reasoning” output (for example in CI logs), you can suppress it:

hide_agent_reasoning = true

If you want to surface raw reasoning content when a model emits it:

show_raw_agent_reasoning = true

Enable raw reasoning only if it’s acceptable for your workflow. Some models/providers (like `gpt-oss`) don’t emit raw reasoning; in that case, this setting has no visible effect.

Notifications

Use `notify` to trigger an external program whenever Codex emits supported events (currently only `agent-turn-complete`). This is handy for desktop toasts, chat webhooks, CI updates, or any side-channel alerting that the built-in TUI notifications don’t cover.

notify = ["python3", "/path/to/notify.py"]

Example `notify.py` (truncated) that reacts to `agent-turn-complete`:

#!/usr/bin/env python3
import json, subprocess, sys
def main() -> int:
    notification = json.loads(sys.argv[1])
    if notification.get("type") != "agent-turn-complete":
        return 0
    title = f"Codex: {notification.get('last-assistant-message', 'Turn Complete!')}"
    message = " ".join(notification.get("input-messages", []))
    subprocess.check_output([
        "terminal-notifier",
        "-title", title,
        "-message", message,
        "-group", "codex-" + notification.get("thread-id", ""),
        "-activate", "com.googlecode.iterm2",
    ])
    return 0
if _name_ == "_main_":
    sys.exit(main())

The script receives a single JSON argument. Common fields include:

• `type` (currently `agent-turn-complete`)
• `thread-id` (session identifier)
• `turn-id` (turn identifier)
• `cwd` (working directory)
• `input-messages` (user messages that led to the turn)
• `last-assistant-message` (last assistant message text)

Place the script somewhere on disk and point `notify` to it.

#### `notify` vs `tui.notifications`

• `notify` runs an external program (good for webhooks, desktop notifiers, CI hooks).
• `tui.notifications` is built in to the TUI and can optionally filter by event type (for example, `agent-turn-complete` and `approval-requested`).
• `tui.notification_method` controls how the TUI emits terminal notifications (`auto`, `osc9`, or `bel`).
• `tui.notification_condition` controls whether TUI notifications fire only when the terminal is `unfocused` or `always`.

In `auto` mode, Codex prefers OSC 9 notifications (a terminal escape sequence some terminals interpret as a desktop notification) and falls back to BEL (`\x07`) otherwise.

See Configuration Reference for the exact keys.

History persistence

By default, Codex saves local session transcripts under `CODEX_HOME` (for example, `~/.codex/history.jsonl`). To disable local history persistence:

[history]
persistence = "none"

To cap the history file size, set `history.max_bytes`. When the file exceeds the cap, Codex drops the oldest entries and compacts the file while keeping the newest records.

[history]
max_bytes = 104857600 # 100 MiB

Clickable citations

If you use a terminal/editor integration that supports it, Codex can render file citations as clickable links. Configure `file_opener` to pick the URI scheme Codex uses:

file_opener = "vscode" # or cursor, windsurf, vscode-insiders, none

Example: a citation like `/home/user/project/main.py:42` can be rewritten into a clickable `vscode://file/...:42` link.

Project instructions discovery

Codex reads `AGENTS.md` (and related files) and includes a limited amount of project guidance in the first turn of a session. Two knobs control how this works:

• `project_doc_max_bytes`: how much to read from each `AGENTS.md` file
• `project_doc_fallback_filenames`: additional filenames to try when `AGENTS.md` is missing at a directory level

For a detailed walkthrough, see Custom instructions with AGENTS.md.

TUI options

Running `codex` with no subcommand launches the interactive terminal UI (TUI). Codex exposes some TUI-specific configuration under `[tui]`, including:

• `tui.notifications`: enable/disable notifications (or restrict to specific types)
• `tui.notification_method`: choose `auto`, `osc9`, or `bel` for terminal notifications
• `tui.notification_condition`: choose `unfocused` or `always` for when notifications fire
• `tui.animations`: enable/disable ASCII animations and shimmer effects
• `tui.alternate_screen`: control alternate screen usage (set to `never` to keep terminal scrollback)
• `tui.show_tooltips`: show or hide onboarding tooltips on the welcome screen

`tui.notification_method` defaults to `auto`. In `auto` mode, Codex prefers OSC 9 notifications (a terminal escape sequence some terminals interpret as a desktop notification) when the terminal appears to support them, and falls back to BEL (`\x07`) otherwise.

See Configuration Reference for the full key list.