feat(tools): let one agent choose its tool presentation, and ship code
Code Mode was a deployment-wide field on the host `tools` row: a deployment ran every session that way or none. The obvious product shape — 代码模式 beside 标准/极简/创造 in the preset picker — had nothing to hang on. The registry itself cannot move into a preset; the agent loop's scheduler, the api-proxy's presenters, and every tool plugin are its consumers. So split the registry from its projection: `presentAs(mode)` writes one cell on the calling agent's scope layer, exactly as `restrict()` does, and the three reads that decided presentation take that scope's mode instead of the service's. The config `mode` becomes the default agents shadow rather than a process-wide fact. Two consequences are load-bearing. `run_code` now enters a view only for scopes whose own mode presents it — a native agent must not find it dispatchable because another agent in the process does — and the reserved name holds whatever the configured mode, since any agent may select a code mode later. `dsh-agent-tool-mode` is the row a preset carries to declare this. A code mode waits for the host's `codeRuntime` rather than assuming it, so a runtime-less deployment fails the preset at mount, naming the row, instead of at the session's first request. The shipped `code` preset is `standard` plus that row, ordered second.
This commit is contained in:
Yichen Jiang
261
apps/cli/config/agent-presets/code/agent.cordis.yml
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261
apps/cli/config/agent-presets/code/agent.cordis.yml
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# The `code` agent preset: the standard coding agent, presented as Code Mode.
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#
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# Everything in `standard` is here unchanged. What is added is the `tool-mode`
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# row: instead of one tool call per action, the model writes a TypeScript
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# program against a generated SDK and `run_code` executes it, so a sequence
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# that would be five round trips becomes one.
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#
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# The registry itself stays on the host plane — the agent loop's scheduler and
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# the API proxy's presenters are its consumers — so what this preset owns is
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# the PRESENTATION of that registry for this agent alone. Native sessions run
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# beside this one in the same process, each seeing its own catalog.
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#
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# This file is an AGENT-PLANE composition. It is mounted under one agent's
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# scope context, so every tool and prompt section it registers belongs to that
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# session alone. The host composition (`base.cordis.yml` + `web.cordis.yml`)
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# keeps everything a preset must not own: the registries themselves, the
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# sandbox and approval stack, persistence, and the model route.
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#
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# A service row here MUST sit inside a group carrying an `isolate` realm.
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# Without one it publishes into the root realm, where it is process-global
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# rather than per-session and the second session mounting this preset collides
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# with the first; `dsh-agent-presets` rejects that at mount. `true` means an
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# entry-local realm — one private instance per mounted session, which is the
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# default this deployment wants. A shared label would instead pool one instance
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# across every session naming it.
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# ── identity ────────────────────────────────────────────────────────────────
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# The preset's own persona, shadowing the deployment default for this agent.
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# `{{model}}` and `{{cwd}}` resolve from the agent's own route and workspace.
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- id: persona
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name: '@deepseek-ai/dsh-persona'
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config:
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text: >-
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You are a coding agent powered by the {{model}} model. Your working directory is {{cwd}}.
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- id: workspace-context
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name: '@deepseek-ai/dsh-workspace-context'
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config:
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maxBytes: 65536
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# ── shell ───────────────────────────────────────────────────────────────────
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# `tool-bash` reads as a tool but provides the `bashEnv` service, so it needs a
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# realm like any other provider. The executor behind it (`bash-sandbox`) stays
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# in the host composition, where the sandbox policy owns it.
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- id: shell
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name: cordis:group
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group: true
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isolate:
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bashEnv: true
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config:
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# The registry and its consumer share the realm: a consumer left outside
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# would resolve the host's `bashEnv`, which this plane no longer provides.
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- id: bash-env
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name: '@deepseek-ai/dsh-bash-env'
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- id: tool-bash
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name: '@deepseek-ai/dsh-tool-bash'
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# ── filesystem ──────────────────────────────────────────────────────────────
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# All three register into the host `tools` registry and provide nothing, so
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# they need no realm. The `fs` service and its policy stay in the host.
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- id: tool-fs
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name: '@deepseek-ai/dsh-tool-fs'
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- id: tool-fs-search
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name: '@deepseek-ai/dsh-tool-fs-search'
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config:
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sampleOverCapGlobResults: false
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- id: tool-str-replace-editor
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name: '@deepseek-ai/dsh-tool-str-replace-editor'
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config:
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maxOutputChars: 16000
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# ── background tasks ────────────────────────────────────────────────────────
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- id: tasks
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name: cordis:group
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group: true
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isolate:
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tasks: true
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config:
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- id: tasks-local
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name: '@deepseek-ai/dsh-tasks-local'
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- id: tool-tasks
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name: '@deepseek-ai/dsh-tool-tasks'
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# ── skills ──────────────────────────────────────────────────────────────────
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- id: skills
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name: cordis:group
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group: true
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isolate:
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skills: true
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config:
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- id: skill
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name: '@deepseek-ai/dsh-skill'
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- id: skill-local
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name: '@deepseek-ai/dsh-skill-local'
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- id: tool-skill
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name: '@deepseek-ai/dsh-tool-skill'
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# ── goals ───────────────────────────────────────────────────────────────────
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- id: goals
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name: cordis:group
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group: true
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isolate:
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goals: true
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config:
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- id: goal
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name: '@deepseek-ai/dsh-goal'
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- id: goal-session
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name: '@deepseek-ai/dsh-goal-session'
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- id: command-goal
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name: '@deepseek-ai/dsh-command-goal'
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- id: tool-goal
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name: '@deepseek-ai/dsh-tool-goal'
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# ── plan mode ───────────────────────────────────────────────────────────────
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# Plan state is per-agent by nature, so an entry-local realm is not a
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# workaround here — it is the correct lifetime.
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- id: planning
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name: cordis:group
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group: true
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isolate:
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planMode: true
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config:
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- id: plan-mode
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name: '@deepseek-ai/dsh-plan-mode'
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config:
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section: |
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You are in plan mode. Stay in plan mode until exit_plan_mode succeeds or the user switches the session mode. Imperative language to implement changes means plan the implementation, not execute it. A user's conversational agreement — including an answer confirming something you asked — approves nothing and does not end plan mode; fold the confirmed decision into the plan and submit it through exit_plan_mode.
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Explore first. Use non-mutating reads, searches, static analysis, and checks to ground the plan in the actual repository. Do not edit or write files, change configuration, run formatters or code generation that rewrites tracked files, commit, or otherwise carry out the plan. Prefer existing functions and patterns over new machinery.
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The tool catalog stays the same across modes for request-cache stability. These plan-mode rules override any later tool description or guidance that suggests using mutation tools; those tools remain listed only to keep the request shape stable. Do not use todo_write to track this planning phase: it tracks implementation after an approved plan, while the plan itself belongs in exit_plan_mode.
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Resolve discoverable facts by inspection. Use ask_user_question only for user-owned choices or material ambiguity that inspection cannot answer. Do not ask the user where code lives or how current behavior works when you can find out.
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Make the plan decision-complete: state the goal and success criteria; group implementation changes by subsystem; identify public API, schema, and data-flow changes; cover edge cases, failure modes, tests, acceptance criteria, and explicit assumptions. Keep it concise enough to review but detailed enough that another engineer can implement it without making design decisions.
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When ready, call exit_plan_mode with the complete plan markdown, starting with a # title. Make exit_plan_mode the only and final tool call in that assistant response: it presents the plan for approval, and implementation begins only in a later step after approval. Do not paste the final plan as a plain reply or ask "should I proceed?" through prose or ask_user_question. If review rejects it, incorporate the feedback and present again. If the review channel is unavailable or aborted, stay in plan mode and ask the user to switch modes manually; do not proceed with implementation.
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# ── compaction ──────────────────────────────────────────────────────────────
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# `compact-basic` reads `toolResultPrune` through `ctx.get`, so the pruner must
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# share this realm rather than sit outside it.
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- id: compaction
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name: cordis:group
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group: true
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isolate:
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tokenMeter: true
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compact: true
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toolResultPrune: true
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config:
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- id: token-meter
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name: '@deepseek-ai/dsh-token-meter'
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- id: compact-basic
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name: '@deepseek-ai/dsh-compact-basic'
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- id: command-compact
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name: '@deepseek-ai/dsh-command-compact'
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- id: tool-result-prune
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name: '@deepseek-ai/dsh-compact-tool-result-prune'
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config:
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thresholdChars: 8192
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headChars: 4096
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tailChars: 1024
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# ── delegation and workflows ────────────────────────────────────────────────
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# The `subagents` registry and its spawn/fork backends live in the HOST
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# composition: the registry is a process singleton whose cross-session queries
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# the api-proxy serves to the browser, and a provider name may only be
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# registered once. This preset contributes the delegation TOOLS, which resolve
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# that host registry.
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#
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# `workflows` is different — nothing outside an agent reads it — so every row
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# that reaches it shares one entry-local realm here, and a consumer left
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# outside would resolve a host registry this preset does not populate.
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- id: delegation
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name: cordis:group
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group: true
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isolate:
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workflows: true
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config:
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- id: tool-subagent-control
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name: '@deepseek-ai/dsh-tool-subagent-control'
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- id: tool-subagent-list-agents
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name: '@deepseek-ai/dsh-tool-subagent-control/list-agents'
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- id: tool-subagent
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name: '@deepseek-ai/dsh-tool-subagent'
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config:
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provider: spawn
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toolName: subagent
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backgroundMode: continuable
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- id: tool-subagent-fork
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name: '@deepseek-ai/dsh-tool-subagent'
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config:
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provider: fork
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toolName: subagent_fork
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backgroundMode: continuable
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- id: tool-subagent-report
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name: '@deepseek-ai/dsh-tool-subagent-report'
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- id: workflow-workerthread
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name: '@deepseek-ai/dsh-workflow-workerthread'
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config:
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provider: spawn
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- id: tool-workflow
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name: '@deepseek-ai/dsh-tool-workflow'
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- id: tool-ralph
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name: '@deepseek-ai/dsh-tool-ralph'
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config:
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subagentProvider: spawn
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maxRounds: 64
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# ── remaining model-facing rows ─────────────────────────────────────────────
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- id: tool-ask-user
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name: '@deepseek-ai/dsh-tool-ask-user'
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- id: tool-todo
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name: '@deepseek-ai/dsh-tool-todo'
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# The `web` service and its search provider stay in the host composition; only
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# the model-facing tool is per-session.
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- id: tool-web
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name: '@deepseek-ai/dsh-tool-web'
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config:
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fetch: false
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searchTimeoutMs: 60000
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# ── presentation ────────────────────────────────────────────────────────────
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# Code Mode for this agent alone. The row waits for the host's `codeRuntime`
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# rather than assuming it: a deployment that composes no TypeScript runtime
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# fails this preset at mount, naming this id, instead of at the first request.
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- id: tool-mode
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name: '@deepseek-ai/dsh-agent-tool-mode'
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config:
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mode: code
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3
apps/cli/config/agent-presets/code/preset.yml
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3
apps/cli/config/agent-presets/code/preset.yml
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name: 代码模式
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description: 标准模式的工具改为 Code Mode 呈现：模型写一段 TypeScript 调用 SDK，一次执行代替多轮工具调用。
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order: 2
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