aweswitch: Agent Profile Switcher

A tiny local launcher for switching AI agent runtime profiles.

One config, one command — works the same on Ubuntu, macOS, and Windows.

Start different agent sessions with different API endpoints, tokens, and models without rewriting global agent config.

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Run different agent profiles side by side without breaking sessions that are already open.

aweswitch reads profiles from ~/.config/aweswitch/config.json and offers two modes:

• Launch mode (aweswitch <profile>) — starts a new agent session with isolated env. Each session gets its own API endpoint, token, and model. Different terminals can run different profiles simultaneously. Env is frozen at launch time.
• Write mode (aweswitch apply <profile>) — makes a profile the agent's persistent default: Claude env into ~/.claude/settings.json, Codex provider+model into ~/.codex/config.toml, OpenCode provider+models into ~/.config/opencode/opencode.json, and zcode providers+models into ~/.zcode/v2/config.json. A bare aweswitch apply bulk-syncs every OpenCode and zcode profile; --opencode / --zcode narrow the bulk to one agent. Claude and Codex keep one active default at a time.

It is intentionally small. Today it supports Claude Code, Codex, OpenCode, and zcode profiles, plus official-login accounts (Claude Code / Codex OAuth).

Quick Start

aweswitch follows the same loop as the rest of the awesome family: hand the bootstrap to an agent once and you land with a working first profile, then manage day-to-day work in natural language. Step 1 covers that bootstrap and gets you using aweswitch right away; steps 2 and 3 are the more advanced operations — equipping the management skill and the daily scenarios in detail. One rule is specific to this tool — the agent never launches a profile for you, because that would nest an agent inside an agent. Applying profiles and managing the config go through the agent; launching stays in your own terminal.

1. Install and use aweswitch

If you are working in Claude Code, Codex, Cursor, or another coding agent, hand the whole job to it — the agent installs the CLI, initializes the config, installs the aweswitch skill, and writes your first profile for you: it reads API keys already exported in your shell config (~/.zshrc, ~/.bashrc, or the Windows user environment) and references them directly, asking only for what is missing. The natural-language path alone leaves a working first config. Invoke skills (/ in Claude Code, $ in Codex) afterwards to confirm the new skill appears; if not, restart the agent first.

You can tell your agent:

Read https://github.com/Webioinfo01/aweswitch/blob/main/README.ai.md and follow it to install and configure aweswitch.

Once the bootstrap finishes, aweswitch is ready to use. There are two ways to use a profile:

Write (apply) — writes a profile into the agent's own config as the persistent default, so every session you open normally uses it from then on. You can tell your agent:

Add a GLM Claude profile, then write cc-glm into Claude settings.

Launch — touches no global config: it starts a one-off session with its own API endpoint and model, and different terminals can run different profiles side by side. Run it in your own terminal (the agent will not launch it for you — that would nest an agent):

aweswitch cc-glm

Working outside a coding agent and prefer to do it yourself? Install from PyPI, create the default config, then add your first profile interactively or edit the config directly — the commands and a reference config are in the folded blocks below.

Package page: pypi.org/project/aweswitch

# Install from PyPI
pip3 install aweswitch
aweswitch --help

# Create the default config, then align it with your real providers
aweswitch config init
aweswitch config edit

# Or add a profile / official account interactively (api or official)
aweswitch add

# Verify the configured profiles (secrets redacted)
aweswitch list
aweswitch show cc-glm

{
  "profiles": {
    "api": {
      "claude": {
        "cc-glm": {
          "env": {
            "ANTHROPIC_BASE_URL": "https://open.bigmodel.cn/api/anthropic",
            "ANTHROPIC_AUTH_TOKEN": "${GLM_ANTHROPIC_AUTH_TOKEN}",
            "ANTHROPIC_MODEL": "glm-5.1"
          }
        },
        "cc-xiaomi": {
          "env": {
            "ANTHROPIC_BASE_URL": "https://token-plan-sgp.xiaomimimo.com/anthropic",
            "ANTHROPIC_AUTH_TOKEN": "${XIAOMI_ANTHROPIC_AUTH_TOKEN}",
            "ANTHROPIC_MODEL": "mimo-v2.5-pro"
          }
        }
      },
      "codex": {
        "cx-openai": {
          "env": {
            "OPENAI_BASE_URL": "https://api.openai.com",
            "OPENAI_API_KEY": "${OPENAI_API_KEY}"
          }
        }
      },
      "opencode": {
        "oc-glm": {
          "env": {
            "OPENCODE_BASE_URL": "https://open.bigmodel.cn/api/coding/paas/v4",
            "OPENCODE_API_KEY": "${GLM_ANTHROPIC_AUTH_TOKEN}",
            "OPENCODE_NAME": "Zhipu GLM",
            "OPENCODE_MODEL": {
              "glm-5.1": "GLM-5.1",
              "glm-5.2": "GLM-5.2"
            }
          }
        }
      },
      "zcode": {
        "zc-glm": {
          "env": {
            "ZCODE_BASE_URL": "https://open.bigmodel.cn/api/coding/paas/v4",
            "ZCODE_API_KEY": "${GLM_ANTHROPIC_AUTH_TOKEN}",
            "ZCODE_NAME": "BigModel - Coding Plan",
            "ZCODE_CHAT_MODEL": {
              "GLM-5.3-Flash": "GLM-5.3-Flash",
              "GLM-5-Turbo": "GLM-5-Turbo"
            }
          }
        }
      }
    },
    "accounts": {}
  }
}

# Claude / OpenCode profiles
export GLM_ANTHROPIC_AUTH_TOKEN="..."
export XIAOMI_ANTHROPIC_AUTH_TOKEN="..."

# Codex profiles
export OPENAI_API_KEY="..."

# zcode profiles
export ZCODE_API_KEY="..."

2. Equip your agent

The bootstrap prompt in step 1 usually installs the aweswitch skill along the way (README.ai.md installs it as its own step 2), so most users arrive already equipped. If you installed by hand or the skill is missing, project it once — it teaches the agent to list, inspect, add, edit, and delete profiles, apply them to settings (aweswitch apply), restore from backup (aweswitch config restore), and read existing API keys from your shell config when writing profiles.

You can tell your agent:

Install the aweswitch skill into this agent so you can manage my aweswitch profiles in natural language.

# Via aweskill (recommended): install from GitHub and project into this agent
aweskill install Webioinfo01/aweswitch
aweskill agent add skill aweswitch --global --agent codex
aweskill agent list --global --agent codex   # expect aweswitch shown as linked

# Without aweskill: copy SKILL.md directly into the agent's skill directory
mkdir -p ~/.claude/skills/aweswitch
curl -fsSL https://raw.githubusercontent.com/Webioinfo01/aweswitch/main/resources/skills/aweswitch/SKILL.md -o ~/.claude/skills/aweswitch/SKILL.md

3. Manage profiles through natural language

From here on, profile management needs no memorized commands: state the intent and the agent reads the config, makes the change, and verifies the result. It can run aweswitch apply, aweswitch config backup, and aweswitch config restore directly; the one thing it will not do is launch a profile (that would nest an agent). The scenarios below cover day-to-day use; expand the folded blocks to run the CLI by hand or verify exactly what happens.

Which mode you need stays a human decision:

Note: The two modes do not interfere with each other. aweswitch cc-glm does not read or modify settings.json. aweswitch apply cc-glm does not affect running sessions.

List and inspect profiles

Profiles live in one local config file, and the inspection commands redact secrets. Ask the agent what exists before changing anything.

You can tell your agent:

List all my aweswitch profiles and show what cc-glm points to.

aweswitch list                        # list all profiles (api + account kinds)
aweswitch show cc-glm                 # inspect one profile (secrets redacted)
aweswitch config path                 # print config file path
aweswitch config show                 # full config (secrets redacted)
aweswitch config edit                 # open the config in an editor

Add or edit a profile

Adding a profile means one entry under profiles.api.<provider> with ${VAR_NAME} token references. The agent reads the current config first, then scans your shell config (~/.zshrc, ~/.bashrc, or the Windows user environment) for API keys you already export and writes the profile referencing them directly — only a missing key needs your input, and the agent can persist it into your shell config for you. Editing works the same way: rename a profile, change the model in cc-glm to glm-5.2, or add a lighter haiku-tier model for background tasks.

You can tell your agent:

Add an AiHubMix codex profile named cx-aihubmix; reuse the API key I already have in my shell, and ask me only if it is missing.

aweswitch add                         # add a profile or official account interactively
# Provider: codex
# Profile name: cx-myprovider
# OPENAI_BASE_URL: https://myprovider.com/v1
# OPENAI_API_KEY env var name: MY_PROVIDER_KEY

aweswitch config edit                 # or edit ~/.config/aweswitch/config.json directly

Set a persistent default profile

aweswitch apply <profile> writes a profile into the agent's own config so it becomes the persistent default — Claude env into ~/.claude/settings.json, Codex provider+model into ~/.codex/config.toml, OpenCode and zcode provider+model lists into their config files. Claude and Codex keep one active default at a time; OpenCode and zcode profiles coexist, so a bare aweswitch apply bulk-syncs both sides. First writes back up the originals, and aweswitch config restore undoes Claude changes.

You can tell your agent:

Write cc-glm into Claude settings so I can switch models with /model.

aweswitch apply cc-glm                # Claude: env -> ~/.claude/settings.json
aweswitch apply cx-glm                # Codex: provider+model -> ~/.codex/config.toml
aweswitch apply oc-glm                # OpenCode: provider+models -> ~/.config/opencode/opencode.json
aweswitch apply zc-glm                # zcode: provider+models -> ~/.zcode/v2/config.json
aweswitch apply                       # bulk: every OpenCode profile, then every zcode profile
aweswitch apply --opencode            # OpenCode bulk only
aweswitch apply --zcode               # zcode bulk only
aweswitch apply cc-glm cx-glm oc-glm  # mixed: one per agent in a single call
aweswitch apply cc-glm --force        # overwrite existing backup

# Prune managed OpenCode / zcode providers left without a backing profile
aweswitch apply --prune orphans             # bulk both agents, remove tracked providers no profile backs
aweswitch apply --opencode --prune all      # also remove every provider no profile backs (hand-written included)
aweswitch apply --opencode --prune old-a,old-b --dry-run  # preview named removals, write nothing

# Back up and restore Claude settings
aweswitch config backup               # back up on demand and print the backup path
aweswitch config restore              # restore settings from default backup
aweswitch config restore <file>       # restore settings from an explicit backup file

Launch profiles side by side

Launching is the one action that stays yours: an agent refuses to run aweswitch <profile> because it would nest an agent inside an agent. Each launch starts a fresh session with its own frozen env, so different terminals can run different profiles at the same time without rewriting global agent config.

Run it in your own terminal:

aweswitch cc-glm                      # launch Claude Code profile
aweswitch cx-openai                   # launch Codex profile
aweswitch oc-glm glm-5.2              # launch OpenCode profile with a specific model
aweswitch cxo-work                    # launch Codex official account (see below)

# Pass extra arguments through to the agent
aweswitch cc-glm --dangerously-skip-permissions
aweswitch cx-openai --model o3
aweswitch oc-glm glm-5.1 --mini

# Auto-bookmark the session with aweshelf
aweswitch cc-glm -c backend -t "Fix auth bug"

Run multiple official accounts side by side

Official-login accounts (OAuth) are saved as accounts and launched through a private per-account config dir, so several Claude Code or Codex logins run side by side without touching your global ~/.claude or ~/.codex. The OAuth login flow is interactive and runs in your terminal; importing the current login and syncing refreshed tokens back can go through the agent.

You can tell your agent:

Import the Claude account I am currently logged in with as an account named team-a.

aweswitch account login codex work    # run codex login and capture it as account "work"
aweswitch account add claude team-a   # import the currently logged-in claude account
aweswitch cxo-work                    # launch codex with the "work" account
aweswitch account sync codex work     # copy refreshed tokens back into the config
aweswitch account remove codex work --purge

Support Tools

aweswitch is powered by three companion tools:

• aweskill — CLI skill package manager for AI agents. Handles skill installation, updates, and projection across 47+ coding agents.
• aweshelf — Session bookmark manager for Claude Code and Codex. Bookmark, categorize, and restore sessions with aweswitch profiles.
• awerouter — Smart LLM router: routes agent requests to flash (cheap) or pro (strong) providers based on structural signals.

aweswitch manages how you launch sessions; aweshelf manages how you remember them. Use aweswitch -c to auto-bookmark at launch, and aweshelf resume to restore with the same profile later. And awerouter pairs just as smoothly: point a profile's BASE_URL at the awerouter daemon (ANTHROPIC_MODEL=auto), and every session you launch goes through its flash/pro routing.

Self-Update

aweswitch checks PyPI for newer versions in the background on each run. If an update is available, a reminder is printed to stderr after the session ends.

aweswitch self-update                 # update manually
aweswitch self-update --check         # check without updating
export AWESWITCH_NO_UPDATE_CHECK=1    # disable the background check

aweshelf Integration

aweshelf is a session bookmark manager for Claude Code and Codex CLI. It lets you save, tag, search, and resume past coding sessions.

aweswitch integrates with aweshelf so you can bookmark a session at launch time, without a separate step:

aweswitch cc-glm -c backend -t "Fix auth bug"

Options

Both options require aweshelf to be installed. If aweshelf is not found, they are ignored with a warning printed to stderr. Claude Code launches normally regardless.

Note: launching multiple aweswitch -c sessions simultaneously in the same project may result in incorrect bookmark assignment. Sequential launches are safe — as long as the previous session's JSONL file has been created before starting the next one (typically a few seconds). See CONTRIBUTING.md for details.

Install aweshelf

pip3 install aweshelf

aweshelf bookmark               # bookmark a session interactively
aweshelf bookmark --current     # bookmark the most recent session in this project
aweshelf list                   # list all bookmarks
aweshelf search "auth"          # full-text search across bookmarks
aweshelf resume BOOKMARK_ID     # resume a saved session
aweshelf browse                 # interactive TUI browser

See the aweshelf README for full documentation.

FAQ

Why aweswitch, and who is it for?

aweswitch is for people who use AI coding agents with more than one runtime endpoint, model, or token source and want a repeatable local command instead of editing settings by hand.

• One local config file at ~/.config/aweswitch/config.json
• Named agent profiles such as cc-glm, cc-gemini, cc-xiaomi, cx-openai, or oc-glm
• Side-by-side sessions where different terminals can launch different API/model combinations
• Runtime-only injection through provider-specific arguments
• No mutation of global agent config, so already-open agent sessions keep working with the settings they started with
• Token references through shell variables or ~/.claude/settings.json
• Readable JSON with profiles.api (env-based profiles) and profiles.accounts (official logins) grouping

~/.config/aweswitch/config.json

Similar Tools

cc-switch

cc-switch is an adjacent Claude Code switching tool. It is useful reference material for the same problem space: making Claude Code provider/model switching easier from the command line.

The key difference is that aweswitch avoids global config mutation. Many switching tools work by changing the agent's shared API/model settings; that can make already-open agent sessions unreliable because the global API endpoint changed underneath them. aweswitch keeps profiles in its own JSON file and injects settings only when launching a new process, so each session keeps the API and model it started with.

aweswitch currently takes a smaller Python-package approach: local JSON profiles, runtime-only injection (Claude Code --settings, Codex -c flags and env vars), secret redaction for inspection commands, and provider grouping that leaves room for future agent support.

Profile Rules

• Profiles live under profiles.api.<provider>.<profileName>; official accounts under profiles.accounts.<provider>.<accountName>.
• Supported providers: claude, codex, opencode (accounts: claude, codex).
• Profile and account names must be unique across the whole profiles tree and cannot reuse a top-level aweswitch command name; account names must also be a single path component.
• env values only apply to the launched process.
• ${VAR_NAME} values are expanded from the current shell environment.
• show and config show redact keys matching token, key, secret, password, or auth; account credential blobs are masked entirely.

Claude Profiles

• Pass env through runtime --settings '{"env": ...}'.
• Set the model with env.ANTHROPIC_MODEL.
• Token values can also expand from ~/.claude/settings.json when they are missing from the shell.

ANTHROPIC_DEFAULT_HAIKU_MODEL, ANTHROPIC_DEFAULT_SONNET_MODEL, and ANTHROPIC_DEFAULT_OPUS_MODEL are not configured by default. If you want Claude Code to use a lighter model for lightweight or background tasks, add ANTHROPIC_DEFAULT_HAIKU_MODEL to the profile:

{
  "profiles": {
    "api": {
      "claude": {
        "cc-xiaomi": {
          "env": {
            "ANTHROPIC_BASE_URL": "https://token-plan-sgp.xiaomimimo.com/anthropic",
            "ANTHROPIC_AUTH_TOKEN": "${XIAOMI_ANTHROPIC_AUTH_TOKEN}",
            "ANTHROPIC_MODEL": "mimo-v2.5-pro",
            "ANTHROPIC_DEFAULT_HAIKU_MODEL": "mimo-v2.5"
          }
        }
      }
    }
  }
}

This keeps the main model on mimo-v2.5-pro while allowing Claude Code to use mimo-v2.5 for lighter work.

Codex Profiles

• Requires OPENAI_BASE_URL and OPENAI_API_KEY in env.
• Optionally set OPENAI_MODEL (dict, list, or comma-separated string) to pick a model at launch: aweswitch <profile> [model]. The first entry is the default; matching is case-insensitive. Without the key, the profile only switches the API source and the first positional argument passes through to codex as usual.
• Base URL is injected via -c model_providers.custom.base_url=..., the model via -c model=... (no file writes).
• API key is injected via environment variable (no writes to ~/.codex/auth.json).
• Extra arguments are passed through to the codex CLI.

Note that Codex has no model-tier system like Claude's OPUS/SONNET/HAIKU slots — only one model is active at a time, and OPENAI_MODEL selects it per launch. In practice, Codex works best with OpenAI's own models — using third-party providers as a relay is the common use case, while switching to entirely different model providers tends to give a poor experience.

{
  "profiles": {
    "api": {
      "codex": {
        "cx-aihubmix": {
          "env": {
            "OPENAI_BASE_URL": "https://aihubmix.com/v1",
            "OPENAI_API_KEY": "${AIHUBMIX_OPENAI_KEY}"
          }
        }
      }
    }
  }
}

aweswitch does not write to ~/.codex/. The base URL is passed via Codex's -c flag and the API key via environment variable. This keeps your global Codex config untouched.

To add a Codex profile interactively:

aweswitch add
# Provider: codex
# Profile name: cx-myprovider
# OPENAI_BASE_URL: https://myprovider.com/v1
# OPENAI_API_KEY env var name: MY_PROVIDER_KEY

OpenCode Profiles

• Requires OPENCODE_BASE_URL, OPENCODE_API_KEY, and OPENCODE_MODEL in env.
• The profile name (e.g. oc-glm) is used as the provider key in ~/.config/opencode/opencode.json.
• OPENCODE_MODEL supports three formats: dict, list, or comma-separated string.
• Model is specified as the first positional argument: aweswitch oc-glm glm-5.1. Matching is case-insensitive against both model IDs and display names (e.g. doubao-seed-evolving selects Doubao-Seed-Evolving).
• If no model is given, the first model in the list is used as default.
• Extra arguments are passed through to the opencode CLI.
• API key is written to opencode.json as {env:VAR} — the actual key is never stored on disk.

{
  "profiles": {
    "api": {
      "opencode": {
        "oc-glm": {
          "env": {
            "OPENCODE_BASE_URL": "https://open.bigmodel.cn/api/coding/paas/v4",
            "OPENCODE_API_KEY": "${GLM_ANTHROPIC_AUTH_TOKEN}",
            "OPENCODE_NAME": "Zhipu GLM",
            "OPENCODE_MODEL": {
              "glm-5.1": "GLM-5.1",
              "glm-5.2": "GLM-5.2"
            }
          }
        }
      }
    }
  }
}

OPENCODE_MODEL formats (optional when OPENCODE_RESPONSES_MODEL is set — at least one of the two is required):

OPENCODE_NAME (optional) sets the display name for the provider in opencode.json. Defaults to the profile name.

OPENCODE_RESPONSES_MODEL (optional) is a comma-separated string or list of model IDs that get a per-model Responses override ("provider": {"npm": "@ai-sdk/openai"} on that model entry) while the rest of the provider stays on chat (@ai-sdk/openai-compatible). It has equal standing with OPENCODE_MODEL: when OPENCODE_MODEL is omitted, this list is the profile's full model list and every model runs on the Responses API. A model may not appear in both fields — an overlap is rejected with an error. Model order — and with it the no-arg default launch model — follows OPENCODE_MODEL when present; responses models not in OPENCODE_MODEL are appended after it. Clearing the list removes the stale overrides on the next sync; a hand-set vendor npm on a model not listed here is never touched.

Launch:

aweswitch oc-glm                      # default: first model (glm-5.1)
aweswitch oc-glm glm-5.2              # specific model
aweswitch oc-glm glm-5.1 --mini       # pass extra args

On first launch, aweswitch writes the provider entry to ~/.config/opencode/opencode.json. Subsequent launches reuse the existing entry and only add new models if needed.

To add an OpenCode profile interactively:

aweswitch add
# Provider: opencode
# Profile name: oc-myprovider
# OPENCODE_BASE_URL: https://myprovider.com/v1
# OPENCODE_API_KEY env var name: MY_API_KEY
# OPENCODE_MODEL: model-1,model-2

Support

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aweswitch is free and open source. Sponsors keep it maintained — thank you.

Development

See Contributing for setup, testing, branching, and release workflow.

• Contributing
• Changelog

Awesome Ecosystem

aweswitch is part of a growing family of "awesome" tools — CLI-first, local-first, and operable by AI agents.

CLI Tools

• aweskill — CLI-first skill package manager supporting 47+ AI coding agents.
• aweswitch — Agent profile switcher for Claude Code, Codex, and OpenCode.
• awerouter — Smart router that splits requests between Flash and Pro models using structural signals, cutting unnecessary model spend.
• aweshelf — Bookmark, categorize, and restore AI coding sessions; pairs with aweswitch to save profiles and launch with one command.
• aweshare — Share local Ollama/vLLM backends, domestic coding plans, or authorized OpenAI/Anthropic subscriptions through a self-hosted hub — a sharing economy for tokens.
• awewarm — Subscription window warmer that keeps AI coding-plan windows active, for local setups and through a remote hub server.
• awescholar — AI-agent-operable scientific literature discovery and curation.

Desktop Apps

• awedot — A floating orb at your screen edge keeps track of the current AI session: bookmark it in one click, resume anytime, and pair with aweswitch to pin the agent's config (e.g., relaunch with the GLM model).

Project Collections

• Awesome AI Meets Biology — A curated survey of AI applications in biology, bioinformatics, and biomedical research. Powered by awescholar.
• Awesome AI Virtual Tumor — A curated collection of state-of-the-art AI systems for virtual tumor modeling and simulation: static models, dynamic models, agents, benchmarks, and reviews.