feat(dte): dynamic thinking effort (series PRs 1-5 + e2e addenda + F7)

[easonLiangWorldedtech]

Dynamic Thinking Effort — reviewer guide (trial VSIX included)

What this is: one installable VS Code build that composes the entire DTE (Dynamic Thinking Effort) series — the 5 feature PRs, both e2e addenda, and F7 (OpenAI-compatible effort declaration) — so it can be tried end-to-end as a single extension.

This PR composes the entire series into one installable build so the combined behavior can be reviewed and tried end-to-end. The 8 component PRs (listed below) remain open and can be merged independently — this PR is a review convenience vehicle for the trial build, not a replacement for them.

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1. What's in the build

#	PR (upstream)	Role	Status
1/5	#1336 feat/dte-1-experiment	dynamicThinkingEffort experimental setting	✅ CI green
2/5	#1338 feat/dte-2-task-state	task-local effort state, per-request override, adaptive envelope	✅ CI green
3/5	#1354 feat/dte-3-native-tool	set_thinking_effort native tool (model-driven, no approval)	✅ CI green
4/5	#1359 feat/dte-4-webview-ui	webview surfaces: header chip, composer toggle, in-chat display	✅ CI green
5/5	#1355 feat/dte-5-orchestrator	orchestrator new_task thinking_effort (subtask start effort)	✅ CI green
addendum	#1361 feat/dte-3-e2e	e2e: set_thinking_effort mid-task workflow	✅ CI green
addendum	#1356 feat/dte-5-e2e	e2e: orchestrator new_task thinking_effort	✅ CI green
F7	#1366 feat/dte-7-f7-openai-compat	OpenAI-compatible profiles declare supported effort levels	✅ CI green

Patch coverage (combined trial tree, Codecov on 27a2e97df): 97.31% (check codecov/patchSuccessful, target 80% — pass) · webview patch 97.67% (check codecov/patch/webview-patch, target 70% — pass). The DTE diff has no fully-missing lines — Codecov's 5 missing lines sit on files outside this PR's diff (stale-base artifact) and the DTE files carry 5 partial branches only; line-level detail in §7.

Trial branch: feat/dte-trial-all @ 27a2e97df (all 8 heads merged, additive; includes the CodeRabbit review fixes, §7). The installable VSIX is the CI-built zoo-code-vsix-pr-1379 artifact from this PR's Code QA run on the current head — it already includes the review fixes (§2).

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2. Install (5 minutes)

1. Download the CI build from the PR's Code QA run (built on head 27a2e97df; the zip contains zoo-code-3.80.0.vsix): zoo-code-vsix-pr-1379 artifact (zip: 33,684,498 bytes · zip SHA256 307100E9C745EEE1BC2A7040A7EC0F6185A5006A5AE70A2B276014927346926D). CI artifacts are retained for 7 days — if the link has expired, re-run the Code QA Roo Code workflow on this PR to get a fresh build at the same head.

2. Install it:

   code --install-extension zoo-code-3.80.0.vsix

   …or in VS Code: Extensions view → ⋯ menu → Install from VSIX… → pick the file.

3. Reload the window (Command Palette → Developer: Reload Window).

4. Open the Zoo Code panel — you're ready.

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3. How to use DTE

A. Managed providers (Anthropic / OpenAI / DeepSeek / …)

1. Pick a capable model. The composer thinking-effort toggle renders for models that advertise a reasoning-effort capability (e.g. Anthropic adaptive-thinking models, OpenAI o-series, DeepSeek, Gemini effort models).
2. Set the effort for the next request using the composer toggle (bottom bar of the chat). The chip shows the current value; open it to see the selectable levels.
3. Watch the applied effort in the header chip and the in-chat display for each turn.
4. Switch mid-task. The model can call set_thinking_effort to change the effort itself (you can also change it at any time with the composer toggle). The change is task-local — it applies from the next request only and is never written to settings; it is stored with the task (like the task mode) and restored when the task is reopened from history.\n\n > Note: the model can only call the tool when the Dynamic Thinking Effort experimental setting is enabled (see 4.5) — the composer toggle, header chip and in-chat display do not require it.
5. Subtasks. new_task can be given a starting effort; if you leave it unset it inherits the parent's effective effort.

B. Self-hosted / OpenAI-compatible (F7)

1. Go to Settings → your OpenAI-compatible profile (custom OpenAI endpoint, LM Studio, Ollama, vLLM, SGLang, …).
2. Use the new supportedEffortLevels multi-select to declare which effort levels your model supports.
3. This unlocks the DTE capability + UI surfaces for that profile.

   ⚠️ Honest scope note: F7 lands the declaration half (capability + settings + UI). For most OpenAI-compatible families the wire half — sending the selected effort level to the server — is a follow-up PR, because each server family needs a different wire shape (LM Studio reasoning:{effort}, vLLM/SGLang flat reasoning_effort). Exception — Ollama: its effort wire is already live today via the pre-existing think request parameter (requires the “Model Reasoning Effort” toggle; low/medium/high map 1:1 and xhigh/max clamp to high), so declaring levels on an Ollama profile also unlocks a working effort wire. Undeclared profiles keep today's behavior exactly.

C. Effort resolution (precedence, strongest first)

task-local override (composer selection, set_thinking_effort, subtask start effort from new_task — all stored with the task and restored when it reopens; none is ever written to settings) → settings.reasoningEffort → model default.
disable is a UI off-switch (not a level, not sent). adaptive is Anthropic's model-decides soft signal.

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4. New UI surfaces — screenshots & guide

Every new DTE surface, what it is, where it appears, and how to use it. (Captured from the real webview components; light + dark themes.)

4.1 Composer thinking-effort toggle (PR 4/5)

Bottom bar of the chat composer, next to the API-config selector. Renders only for models that advertise per-request effort support (registry capability, or an F7 declaration — see 4.6). The chip shows the current effective effort; open it to switch the task-local effort — the change applies from the next request and is never persisted to settings. If no task is open yet, the selection is parked and applied to the next top-level task you start (when that task's model supports the level; a stale selection never leaks into a later task).

Menu (selectable levels)	Resting (current effort)

Dark: menu · resting

4.2 Task header chip (PR 4/5)

Sits in the task header (top of the chat, next to the task title). Shows the current effective effort plus a source badge so you can tell where it came from:

• you — you set it with the composer toggle (and it differs from the default)
• Zoo (auto) — model-driven or inherited (e.g. a subtask inherits the parent's effort)
• default — from the provider-profile setting or model default

Task-local override (source: you)	Settings default (source: default)

Dark: you · default

4.3 In-chat effort display (PR 3/5 + 4/5)

One-line entries in the chat whenever the effort changes, so the switch is visible in the conversation:

• model-driven: "Thinking effort: high (Zoo) — " (the model called set_thinking_effort with a reason)
• user-driven: "Thinking effort set to: low" (you changed it via the composer)
• refused: escalation cap (max 3 upward changes per task) or oscillation detection

Applied (model, with reason) · Applied (you) · Refused (oscillation)

Dark: in-chat lines

4.4 Settings — supported reasoning effort levels (F7, self-hosted)

New control in Settings → your OpenAI-compatible profile (custom OpenAI endpoint, LM Studio, Ollama, vLLM, SGLang). Self-hosted models don't advertise effort capability, so declare the levels your model accepts — this unlocks the whole DTE feature set for that profile. Values buffer in the settings form and persist on Save.

Declared (5 levels)	Undeclared (nothing declared — DTE stays off)

Dark: declared · undeclared

4.5 Settings — experimental toggle (PR 1/5)

Settings → Experimental → Dynamic Thinking Effort. This toggle gates model-driven mid-task switching only — when it is on, capable models are given the set_thinking_effort tool so the model itself can change the effort during a task. The UI surfaces (composer toggle, header chip, in-chat display, new_task selector, F7 settings) are gated by model capability, not by this experiment — they render without it. Turn it on to try the model-driven flow (step 4 of §3).

Experimental section with DTE enabled

Dark: experimental

4.6 Composer toggle — self-hosted model with F7 declaration (F7 + 4/5)

The same composer toggle for a self-hosted OpenAI-compatible model (Qwen3.8:27B) whose effort levels were declared in 4.4 — the declared levels appear in the menu (webview capability fill-in).

Menu (declared levels)	Resting (current effort)

Dark: menu · resting

4.7 new_task start-effort selector (PR 5/5)

When the orchestrator asks to start a subtask (new_task), the ask block shows a small Brain-icon effort selector next to the prompt (only when the target model supports effort). It is pre-filled with the parent task's effective effort and can be switched before entering the subtask; leave it as-is to inherit. (Rendered inline in the ask bar — see the e2e addendum #1356 for the wire-level proof.)

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5. Provider support & thinking-effort options

Which providers wire thinking effort into the request, the levels they accept, and the wire shape:

Provider	Effort on the wire	Thinking-effort options (levels)	Wire field / shape	Notes
Anthropic / Anthropic Vertex (adaptive-thinking)	✅	low · medium · high · xhigh · max (out-of-range → omitted → API default)	output_config.effort (adaptive envelope)	First-class DTE — per-request override fully wired
OpenAI / OpenAI-native	✅	low · medium · high (model default + selected)	reasoning_effort	o-series
OpenRouter	✅ (per-model)	effort levels (model metadata)	{ effort }	capability from model supported_parameters
Google Gemini	✅	minimal · low · medium · high (effort) / thinkingBudget (2.5)	thinkingConfig.thinkingLevel
DeepSeek	✅	low · high · max	reasoning_effort
xAI	✅	low · medium · high	reasoning: { effort }	object shape
Z.ai (GLM)	✅	none · minimal · low · medium · high · xhigh · max	reasoning_effort + thinking toggle
Roo Code	✅	(capability array)	reasoning: { enabled, effort }
nanoGPT	✅	low · medium · high (or model-declared)	reasoning_effort
opencode-go	✅	low · medium · high	reasoning_effort
kimi-code	✅	(boolean / array)	—
Friendli (OpenAI-compatible)	✅	minimal · low · medium · high · xhigh · max	reasoning_effort (extended enum)
Poe	✅	low · medium · high	reasoning_effort
Requesty	✅	low · medium · high (allow-listed)	reasoning_effort
Unbound	✅	low · medium · high (allow-listed)	reasoning_effort
Ollama	✅ (pre-existing)	low / medium / high (xhigh/max → high)	think (bool or level)	Pre-existing wire — requires the Model Reasoning Effort toggle; F7's level declaration unlocks the UI menu on top of it\n

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6. What to verify during the trial

• Composer toggle appears for a capable model; chip + menu render (see §4).
• Selecting an effort changes the next request (not mid-stream); the value is never written to settings — it is stored with the task and restored when the task is reopened from history.
• set_thinking_effort mid-task: applied / no-op / refused transitions behave correctly (escalation cap = max 3 upward changes per task + oscillation refusal). Requires the DTE experiment enabled (4.5).
• new_task: explicit start effort honored; unset inherits the parent's effective effort.
• Header chip + in-chat display track the applied effort.
• F7: declaring supportedEffortLevels on a self-hosted profile unlocks the UI; undeclared profiles are unchanged.
• Settings round-trip: declared levels survive a reload (storage → webview).

Known limitations (by design, for this trial):

• Self-hosted OpenAI-compatible per-server wire pass-through is a follow-up for custom endpoints / LM Studio / vLLM / SGLang (Ollama already has a live think wire — see §5).
• adaptive is a soft guidance signal, not a concrete level.
• Effort overrides are never written to settings; they are stored with the task (task layer) and restored when the task is reopened from history.

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7. Provenance

• Branch: feat/dte-trial-all @ 27a2e97df (fork).
• Build: CI artifact zoo-code-vsix-pr-1379 (zip) from the Code QA run 32976523650 on head 27a2e97df — zip SHA256 307100E9C745EEE1BC2A7040A7EC0F6185A5006A5AE70A2B276014927346926D (33,684,498 bytes, 7-day retention). The earlier fork-release build (head 310f0da97, VSIX SHA256 04F6B33B847101E203CA098B2381087EA4C324B9DF904F90CDDADB007D9E7594) is superseded; the §4 UI screenshots remain hosted on that fork release.
• Post-build changes on the branch (CodeRabbit review fixes; bug/robustness only, no new user-facing features): feat(task): task-local thinking effort state, per-request override, and adaptive effort envelope (DTE series 2/5) #1338 01394aeea + 77ec064d3 (cleared-effort persistence through the history-store merge; pre-dispose effort snapshot on the abort final save), feat(orchestrator): new_task thinking_effort — subtask start effort, switchable before entering (DTE series 5/5) #1355 2ab330e53 + 6eba686c1 (unsupported-model thinking_effort wording; capability-level normalization), feat(webview): thinking effort surfaces — header chip, composer toggle, in-chat display (DTE series 4/5) #1359 94928c2f5 (typed webview spec doubles), test(e2e): set_thinking_effort mid-task workflow — e2e coverage (DTE series 3/5 addendum) #1361 7aeec7938 + 0b335c682 (flow-scoped e2e fixtures; predicate-scoped continuation turns), feat(settings): let OpenAI-compatible profiles declare supported reasoning effort levels (DTE F7) #1366 62b3ba56c + 65ee7b5e6 (nl settings typo; native-Ollama per-request override threading).
• Upstream PRs: feat(experiments): add dynamic thinking effort experimental setting (DTE series 1/5) #1336, feat(task): task-local thinking effort state, per-request override, and adaptive effort envelope (DTE series 2/5) #1338, feat(tools): set_thinking_effort native tool — model-driven per-turn thinking effort, no approval (DTE series 3/5) #1354, feat(webview): thinking effort surfaces — header chip, composer toggle, in-chat display (DTE series 4/5) #1359, feat(orchestrator): new_task thinking_effort — subtask start effort, switchable before entering (DTE series 5/5) #1355, test(e2e): orchestrator new_task thinking_effort — e2e coverage (DTE series 5/5 addendum) #1356, test(e2e): set_thinking_effort mid-task workflow — e2e coverage (DTE series 3/5 addendum) #1361, feat(settings): let OpenAI-compatible profiles declare supported reasoning effort levels (DTE F7) #1366 (all CI-green, CodeRabbit-clean; combined trial tree: 97.31% patch coverage (Codecov check codecov/patchSuccessful, target 80% — pass) and 97.67% webview patch (check codecov/patch/webview-patch, target 70% — pass) on head 27a2e97df; the DTE diff has zero fully-missing lines — Codecov's 5 missing lines are all on files not in the PR diff (its diff base is the branch fork point, so upstream main commits feat: Add Read+Write allowlists #1274/fix(openai-codex): complete prompts over the streaming transport #1243/[Fix] Terminal startup failures can leave commands unresolved #1351/[Fix] Background service failures can surface as unhandled rejections #1352 that landed after the fork count as "changes"), and the DTE files carry 5 partial branches only (ClineProvider.ts x3, webviewMessageHandler.ts x2)).
• Fork companion: easonLiangWorldedtech/Zoo-Code#29 (same head branch, same body).

Summary by CodeRabbit

• New Features
  • Added configurable thinking-effort controls for supported models.
  • Users can select effort levels in the chat composer and view the active level in task headers.
  • Added in-task effort changes with validation, fallback handling, refusal messages, and escalation safeguards.
  • Added effort selection and inheritance for delegated tasks.
  • Added provider settings and an experimental dynamic-effort option.
  • Effort selections persist with tasks and support adaptive models.
• Localization
  • Added translated labels, guidance, and status messages.
• Tests
  • Added comprehensive coverage across providers, delegation, persistence, and UI interactions.

[easonLiangWorldedtech]

Superseded by the DTE-v2 400-line redo. Content re-lands from the verified union 27a2e97 (feat/dte-trial-all, branch retained) as units U1-U39. New tracking issue: easonLiangWorldedtech#35.