chore(sync): mirror docs from openclaw/openclaw@797d574dfd

.openclaw-sync/source.json

@@ -1,5 +1,5 @@
 {
   "repository": "openclaw/openclaw",
-  "sha": "9289a502bb070c51dd86e9b3f10538398e36da54",
-  "syncedAt": "2026-04-30T15:32:29.061Z"
+  "sha": "797d574dfdc4e7e62c7f409bf5a179f9a869e951",
+  "syncedAt": "2026-04-30T15:35:28.747Z"
 }

docs/providers/deepseek.md

@@ -79,6 +79,8 @@ is available to that process (for example, in `~/.openclaw/.env` or via
 V4 models support DeepSeek's `thinking` control. OpenClaw also replays
 DeepSeek `reasoning_content` on follow-up turns so thinking sessions with tool
 calls can continue.
+Use `/think xhigh` or `/think max` with DeepSeek V4 models to request DeepSeek's
+maximum `reasoning_effort`.
 </Tip>
 
 ## Thinking and tools

docs/tools/thinking.md

@@ -26,6 +26,7 @@ title: "Thinking levels"
   - Anthropic Claude Opus 4.7 does not default to adaptive thinking. Its API effort default remains provider-owned unless you explicitly set a thinking level.
   - Anthropic Claude Opus 4.7 maps `/think xhigh` to adaptive thinking plus `output_config.effort: "xhigh"`, because `/think` is a thinking directive and `xhigh` is the Opus 4.7 effort setting.
   - Anthropic Claude Opus 4.7 also exposes `/think max`; it maps to the same provider-owned max effort path.
+  - DeepSeek V4 models expose `/think xhigh|max`; both map to DeepSeek `reasoning_effort: "max"` while lower non-off levels map to `high`.
   - Ollama thinking-capable models expose `/think low|medium|high|max`; `max` maps to native `think: "high"` because Ollama's native API accepts `low`, `medium`, and `high` effort strings.
   - OpenAI GPT models map `/think` through model-specific Responses API effort support. `/think off` sends `reasoning.effort: "none"` only when the target model supports it; otherwise OpenClaw omits the disabled reasoning payload instead of sending an unsupported value.
   - Custom OpenAI-compatible catalog entries can opt into `/think xhigh` by setting `models.providers.<provider>.models[].compat.supportedReasoningEfforts` to include `"xhigh"`. This uses the same compat metadata that maps outbound OpenAI reasoning effort payloads, so menus, session validation, agent CLI, and `llm-task` agree with transport behavior.