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openclaw-model-switch

openclaw-model-switch

github.com/daymadeAgent workflows1.5k330 installsUpdated today
Repository

About openclaw-model-switch

A skill for diagnosing and switching OpenClaw model configurations, aimed at maintainers troubleshooting model calls. It probes endpoints, discovers and syncs config mirrors, backs up files, and calls for verification with a real agent turn.

Key features

  1. 01Discover config files and mirrors
  2. 02Switch models and sync configs
  3. 03Probe endpoint and model availability
  4. 04Back up configs and restart gateway
  5. 05Verify with a real agent turn

Use cases

  1. 01Diagnose model-call failures
  2. 02Switch models across config mirrors
  3. 03Check model access from the host
  4. 04Verify whether a fallback model was used

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/daymade/claude-code-skills --skill openclaw-model-switch

After installing, type/openclaw-model-switchin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
kimi-models.md
troubleshooting-model-config.md
scripts/
switch-model.py

Details

From the project README

OpenClaw Model Switch

Switch or repair an OpenClaw instance's model configuration by safely editing openclaw.json.

Diagnose before you edit. Model failures on OpenClaw are usually NOT the model id — they are key routing (env hijack), provider-plugin restrictions, or endpoint/model mismatch. Changing the model id without checking these first is how a 5-minute fix becomes a 2-hour debugging session. The full trap catalog with discovery commands lives in references/troubleshooting-model-config.md — read it the moment anything errors.

Step 1 — Find the real config file(s)

Do NOT assume a hardcoded path. Candidate locations (check all, edit all that exist):

  1. ~/.openclaw/openclaw.json — the gateway's live config on most installs
  2. ~/.kimi/kimi-claw/openclaw.json — Kimi Claw mirror, kept in sync on some installs
  3. ~/.kimi_openclaw/openclaw.json — legacy desktop path

Confirm which one the gateway actually reads: openclaw gateway status prints Config (service): <path>. If several exist, treat them as mirrors: edit all of them identically, otherwise the next sync overwrites your fix.

Step 2 — Probe the endpoint + model BEFORE touching config

Never trust a relay's model listing (GET /v1/models on new-api style relays is frequently incomplete — a model can be absent from the list yet serve fine). The only authority is a real completion probe from the host that will run the bot:

curl -sS -o /tmp/probe.json -w "HTTP %{http_code}\n" \
  -X POST "<baseUrl>/v1/messages" \
  -H "Authorization: Bearer <apiKey>" \
  -H "Content-Type: application/json" \
  -H "anthropic-version: 2023-06-01" \
  -d '{"model":"<model-id>","max_tokens":16,"messages":[{"role":"user","content":"hi"}]}'

Expected: HTTP 200 and a content array in the body. 401 Invalid token with a token you just verified works elsewhere → the wire key is being hijacked (see trap #1 in the troubleshooting reference). 503 No available channel → the model is not served for this token/group from this network (trap #3) — pick a served model or fix the relay, don't blind-switch.

Step 3 — Switch the model

python3 scripts/switch-model.py <model-id> --restart
# target a specific provider instead of the guessed one:
python3 scripts/switch-model.py k3 --provider kimi-relay --restart
# explicit config path (skips discovery):
python3 scripts/switch-model.py k3 --config ~/.openclaw/openclaw.json --restart

The script: discovers and backs up every candidate config to <config-dir>/config-backups/, adds the model definition if known, sets agents.defaults.model.primary, syncs mirror files, and restarts the gateway with --restart.

Step 4 — Verify end-to-end (mandatory)

A restarted gateway proves nothing. Run one real agent turn and read the result metadata:

openclaw agent --local --json --agent main --session-id verify-$(date +%s) -m "ping"

Success looks like: "result": "success", "fallbackUsed": false, and the gateway log shows agent model: <provider>/<model> (thinking=...). "result": "success" with fallbackUsed: true means your target failed and a fallback saved the turn — the config is still wrong.

Common failures → read the troubleshooting reference

SymptomMost likely trap
LLM error new_api_error: Invalid token, but the token works in curlTrap #1 — env KIMI_API_KEY hijacks the provider's wire key
Thinking level "max" is not supported ... Use one of: off, onTrap #2 — kimi-provider plugin hardcodes binary thinking; bypass with a custom provider
Thinking level ... Use one of: off, minimal, low, medium, highTrap #2 variant — anthropic-messages base profile; unlock via params.canonicalModelId
503 No available channel for model X under group defaultTrap #3 — model not served for this group/network; listing ≠ availability
Edit saved + gateway restarted, nothing changedTrap #5 — edited the wrong file / mirror not synced

Safety rules

  • Always backup before editing (the script does this; manual edits: copy to config-backups/ first)
  • Preserve existing apiKey, headers, plugin configs, and env blocks — retype only the fields you mean to change
  • Validate JSON after manual edits: python3 -m json.tool openclaw.json > /dev/null
  • Do not commit config files containing API keys to version control
  • After changing anything, redo the Step-4 verification — and if it fails, restore the newest backup before trying something else

Resources

  • scripts/switch-model.py — model switcher with config discovery, backup, mirror sync, and restart
  • references/kimi-models.md — known model specs (k3, k2p6, kimi-k2.7-code) and config snippets
  • references/troubleshooting-model-config.md — the trap catalog: env key hijack, plugin binary thinking, canonicalModelId, relay availability, config discovery. Read on any error.

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