config-advanced.md Codex Docs, 2026-03-07 00:33 UTC → 2026-04-08 00:40 UTC

2 2 

3Use these options when you need more control over providers, policies, and integrations. For a quick start, see [Config basics](https://developers.openai.com/codex/config-basic).3Use these options when you need more control over providers, policies, and integrations. For a quick start, see [Config basics](https://developers.openai.com/codex/config-basic).

4 4 

5For background on project guidance, reusable capabilities, custom slash commands, multi-agent workflows, and integrations, see [Customization](https://developers.openai.com/codex/concepts/customization). For configuration keys, see [Configuration Reference](https://developers.openai.com/codex/config-reference).5For background on project guidance, reusable capabilities, custom slash commands, subagent workflows, and integrations, see [Customization](https://developers.openai.com/codex/concepts/customization). For configuration keys, see [Configuration Reference](https://developers.openai.com/codex/config-reference).

6 6 

7## Profiles7## Profiles

8 8 

15Define profiles under `[profiles.<name>]` in `config.toml`, then run `codex --profile <name>`:15Define profiles under `[profiles.<name>]` in `config.toml`, then run `codex --profile <name>`:

16 16 

17```toml17```toml

18model = "gpt-5-codex"18model = "gpt-5.4"

19approval_policy = "on-request"19approval_policy = "on-request"

20model_catalog_json = "/Users/me/.codex/model-catalogs/default.json"20model_catalog_json = "/Users/me/.codex/model-catalogs/default.json"

21 21 

74 74 

75For shared defaults, rules, and skills checked into repos or system paths, see [Team Config](https://developers.openai.com/codex/enterprise/admin-setup#team-config).75For shared defaults, rules, and skills checked into repos or system paths, see [Team Config](https://developers.openai.com/codex/enterprise/admin-setup#team-config).

76 76 

77If you just need to point the built-in OpenAI provider at an LLM proxy, router, or data-residency enabled project, set environment variable `OPENAI_BASE_URL` instead of defining a new provider. This overrides the default OpenAI endpoint without a `config.toml` change.77If 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.

78 78 

79```toml79```toml

80export OPENAI_BASE_URL="https://api.openai.com/v1"80openai_base_url = "https://us.api.openai.com/v1"

81codex

82```81```

83 82 

84## Project config files (`.codex/config.toml`)83## Project config files (`.codex/config.toml`)

87 86 

88For security, Codex loads project-scoped config files only when the project is trusted. If the project is untrusted, Codex ignores `.codex/config.toml` files in the project.87For security, Codex loads project-scoped config files only when the project is trusted. If the project is untrusted, Codex ignores `.codex/config.toml` files in the project.

89 88 

90Relative paths inside a project config (for example, `experimental_instructions_file`) are resolved relative to the `.codex/` folder that contains the `config.toml`.89Relative paths inside a project config (for example, `model_instructions_file`) are resolved relative to the `.codex/` folder that contains the `config.toml`.

90 

91## Hooks (experimental)

92 

93Codex can also load lifecycle hooks from `hooks.json` files that sit next to

94active config layers.

95 

96In practice, the two most useful locations are:

97 

98- `~/.codex/hooks.json`

99- `<repo>/.codex/hooks.json`

100 

101Turn hooks on with:

102 

103```toml

104[features]

105codex_hooks = true

106```

107 

108For the current event list, input fields, output behavior, and limitations, see

109[Hooks](https://developers.openai.com/codex/hooks).

91 110 

92## Agent roles (`[agents]` in `config.toml`)111## Agent roles (`[agents]` in `config.toml`)

93 112 

94For multi-agent role configuration (`[agents]` in `config.toml`), see [Multi-agents](https://developers.openai.com/codex/multi-agent).113For subagent role configuration (`[agents]` in `config.toml`), see [Subagents](https://developers.openai.com/codex/subagents).

95 114 

96## Project root detection115## Project root detection

97 116 

113Define additional providers and point `model_provider` at them:132Define additional providers and point `model_provider` at them:

114 133 

115```toml134```toml

116model = "gpt-5.1"135model = "gpt-5.4"

117model_provider = "proxy"136model_provider = "proxy"

118 137 

119[model_providers.proxy]138[model_providers.proxy]

190 209 

191Pick approval strictness (affects when Codex pauses) and sandbox level (affects file/network access).210Pick approval strictness (affects when Codex pauses) and sandbox level (affects file/network access).

192 211 

193For operational details that are easy to miss while editing `config.toml`, see [Common sandbox and approval combinations](https://developers.openai.com/codex/agent-approvals-security#common-sandbox-and-approval-combinations), [Protected paths in writable roots](https://developers.openai.com/codex/agent-approvals-security#protected-paths-in-writable-roots), and [Network access](https://developers.openai.com/codex/agent-approvals-security#network-access).212For operational details to keep in mind while editing `config.toml`, see [Common sandbox and approval combinations](https://developers.openai.com/codex/agent-approvals-security#common-sandbox-and-approval-combinations), [Protected paths in writable roots](https://developers.openai.com/codex/agent-approvals-security#protected-paths-in-writable-roots), and [Network access](https://developers.openai.com/codex/agent-approvals-security#network-access).

194 213 

195You can also use a granular reject policy (`approval_policy = { reject = { ... } }`) to auto-reject only selected prompt categories, such as sandbox approvals, `execpolicy` rule prompts, or MCP input requests (`mcp_elicitations`), while keeping other prompts interactive.214You 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.

196 215 

197```216```

198approval_policy = "untrusted" # Other options: on-request, never, or { reject = { ... } }217approval_policy = "untrusted" # Other options: on-request, never, or { granular = { ... } }

199sandbox_mode = "workspace-write"218sandbox_mode = "workspace-write"

200allow_login_shell = false # Optional hardening: disallow login shells for shell tools219allow_login_shell = false # Optional hardening: disallow login shells for shell tools

201 220 

221# Example granular approval policy:

222# approval_policy = { granular = {

223# sandbox_approval = true,

224# rules = true,

225# mcp_elicitations = true,

226# request_permissions = false,

227# skill_approval = false

228# } }

229 

202[sandbox_workspace_write]230[sandbox_workspace_write]

203exclude_tmpdir_env_var = false # Allow $TMPDIR231exclude_tmpdir_env_var = false # Allow $TMPDIR

204exclude_slash_tmp = false # Allow /tmp232exclude_slash_tmp = false # Allow /tmp