NotExpectedYet
4bc4296494
The preset's persona row copied the deployment's suffix, "Your working directory
is {{cwd}}". The harness substitutes only registered prompt variables and throws
on an unregistered one during prompt assembly — so when a harness release stopped
registering `cwd` (only `provider` and `model` remain), every session on this
preset failed its first turn with
unknown prompt variable "{{cwd}}" in section "deployment:persona-suffix"
and chat was dead rather than degraded. The row now carries the prefix only.
The folder is stated where it can follow the session instead: the facet binding
already names the facet, and now names the session folder as well when the two
differ — which is every conversation that started higher up and was narrowed, and
exactly the case where relative tool paths need saying out loud.
`test/presets.test.js` makes this class of failure impossible to reintroduce
silently: it scans every shipped preset for a variable reference and requires the
name to be one the harness registers, and holds this bundle's own rule and
binding text to no references at all. Restoring the old suffix fails it.
196 lines
10 KiB
YAML
196 lines
10 KiB
YAML
# Agent preset facet: one `@deepseek-ai/dsh-agent-preset` declaration inserted
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# after the web patch.
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#
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# The composition is `standard` with three changes, and this file is the only
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# place any of them is decided:
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#
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# * compaction is configured (see the `compaction` row below) so the pressure
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# trigger is a budget rather than a formality. The shipped ratio is 0.80 of a
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# 1,000,000-token window, i.e. 800k, and on this deployment nothing has ever
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# come within 1.5% of it — compaction had never once run;
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#
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# * `facet-guard` is mounted, which confines the session to its own folder;
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#
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# * the persona row carries no suffix. The shipped one states the working
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# directory through a prompt variable the harness no longer registers, and
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# an unregistered variable fails the whole turn — see the note on that row.
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#
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# Everything else is copied verbatim from the shipped `standard` patch, and that
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# is deliberate: a preset declaration replaces the whole plugin list rather than
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# merging into it, so a clone that drifts from the original silently loses
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# whatever it drifted past. When the harness next changes `standard`, re-copy
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# this file and re-apply the three changes — do not hand-patch around it. The
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# persona row must be re-checked by hand: re-copying it from `standard` restores
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# the suffix, and the harness's variable set is what decides whether it composes.
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- insert:
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- id: preset-facet
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name: '@deepseek-ai/dsh-agent-preset'
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config:
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id: facet
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name: Facet
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description: One module of the system, not all of it — the session's own folder, plus the files you grant.
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order: 5
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plugins:
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# No suffix. It used to state the working directory through the `cwd`
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# prompt variable, which the harness does not register — and an unknown
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# variable is not rendered as text: assembly throws and the whole turn
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# fails with it. Only `provider` and `model` are registered now, so the
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# prefix keeps its model reference and the folder is stated per session
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# by `facet-guard`'s runtime binding instead, which follows the user
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# when they narrow it.
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- id: persona
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name: '@deepseek-ai/dsh-persona'
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config:
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prefix: You are a coding agent powered by the {{model}} model.
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- id: agent-instructions
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name: '@deepseek-ai/dsh-agent-instructions'
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config:
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maxBytes: 65536
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# The facet itself: a rule in the system prompt, the binding in the
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# runtime context, the `facet` tool, and the pre-execute guard that
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# asks before a file call leaves the session's folder. Configured by
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# the `facet-policy` host row, not here — one place for the mode and
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# the standing grants, whichever preset is selected.
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- id: facet-guard
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name: 'dsh-facet/guard'
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- id: tool-bash
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name: '@deepseek-ai/dsh-tool-bash'
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disabled: !!js process.platform === 'win32'
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- id: tool-pwsh
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name: '@deepseek-ai/dsh-tool-pwsh'
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disabled: !!js process.platform !== 'win32'
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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-jobs
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name: '@deepseek-ai/dsh-tool-jobs'
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- id: skill-filesystem
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name: '@deepseek-ai/dsh-skill-filesystem'
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- id: tool-skill
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name: '@deepseek-ai/dsh-tool-skill'
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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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- 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 to keep the tool catalog unchanged. 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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- id: compaction
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name: cordis:group
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group: true
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isolate:
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compaction: true
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toolResultPruner: true
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config:
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- id: compaction-basic
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name: '@deepseek-ai/dsh-compaction-basic'
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config:
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# 0.80 of a 1M window is a 800k trigger, and the deepest session
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# ever recorded here peaked at 787,668 pressure tokens: the
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# trigger was never reached, so every token below it was re-read
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# on every subsequent step. 0.35 puts the ceiling at 350k.
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thresholdRatio: 0.35
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# Retention is absolute rather than a ratio, because "16% of a
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# 1M window" (160k) is not a working-set measurement. Where the
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# summarisation call is capped explicitly: the schema default
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# inherits `headroomTokens` (65536), which is a far larger
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# output bill than this needs.
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retainTokens: 80000
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maxTokens: 16384
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- id: command-compact
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name: '@deepseek-ai/dsh-command-compact'
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- id: tool-result-pruner
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name: '@deepseek-ai/dsh-compaction-tool-result-pruner'
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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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- id: delegation
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name: cordis:group
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group: true
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isolate:
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workflowEngine: 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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modelSelectionSettings: true
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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-codex
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name: '@deepseek-ai/dsh-tool-subagent'
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disabled: true
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config:
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provider: codex
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toolName: subagent_codex
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backgroundMode: one-shot
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maxDepth: provider-managed
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- id: tool-subagent-claude-code
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name: '@deepseek-ai/dsh-tool-subagent'
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disabled: true
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config:
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provider: claude-code
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toolName: subagent_claude_code
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backgroundMode: one-shot
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maxDepth: provider-managed
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- id: workflow-ptc
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name: '@deepseek-ai/dsh-workflow-ptc'
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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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disabled: true
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config:
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subagentProvider: spawn
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maxRounds: 64
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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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config:
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allowParallelInProgress: true
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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: true
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searchTimeoutMs: 60000
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- id: present
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name: '@deepseek-ai/dsh-tool-present'
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- id: tool-plugin-manager
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name: '@deepseek-ai/dsh-plugin-manager/tools'
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disabled: true
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