[System]
You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.

Schema: {"action_type": one of ["consult", "ask", "summarize", "submit", "noop"], "expert_id": one of ["analyst", "finance", "hr", "strategy"] or null, "sub_question_id": string or null, "notes": string or null}.
Rules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed.

[User] Task=expert_brief; difficulty=hard; step=5/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0

[Assistant] {"action_type":"submit"}


[System]
You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.

Schema: {"action_type": one of ["consult", "ask", "summarize", "submit", "noop"], "expert_id": one of ["analyst", "finance", "hr", "strategy"] or null, "sub_question_id": string or null, "notes": string or null}.
Rules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed.

[Assistant] {"action_type":"submit"}


[System]
You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.

Schema: {"action_type": one of ["consult", "ask", "summarize", "submit", "noop"], "expert_id": one of ["analyst", "finance", "hr", "strategy"] or null, "sub_question_id": string or null, "notes": string or null}.
Rules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed.

[User]
Decision checklist:
- task: expert_brief
- required experts: analyst, finance, strategy, hr
- already consulted: analyst, finance, strategy, hr
- still missing: none
- brief composed: True
- choose the single next action

[Assistant] {"action_type":"submit"}


[System]
You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.

Schema: {"action_type": one of ["consult", "ask", "summarize", "submit", "noop"], "expert_id": one of ["analyst", "finance", "hr", "strategy"] or null, "sub_question_id": string or null, "notes": string or null}.
Rules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed.

[User] You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True.

[Assistant] {"action_type":"submit"}


[System]
You are the Chief of Staff (CoS) in AutoDataLab++. You orchestrate four specialists: analyst, finance, strategy, hr. At each step, decide ONE action and reply with STRICT JSON only.

Schema: {"action_type": one of ["consult", "ask", "summarize", "submit", "noop"], "expert_id": one of ["analyst", "finance", "hr", "strategy"] or null, "sub_question_id": string or null, "notes": string or null}.
Rules: consult each required expert at most once before summarizing; summarize before submitting; submit only when the brief is composed.

[User] state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?

[Assistant] {"action_type":"submit"}


[System] Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy.

[User]
task_name: expert_brief
task_difficulty: hard
step_count: 5
max_steps: 14
rag_enabled: True
available_experts: ['analyst', 'finance', 'hr', 'strategy']
required_experts: ['analyst', 'finance', 'strategy', 'hr']
consulted_experts: ['analyst', 'finance', 'strategy', 'hr']
missing_required_experts: []
current_brief_present: True
data_quality_score: 1.0
recent_issues: ['brief_composed']
instruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only.

[Assistant] {"action_type":"submit"}


[System] Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy.

[User] Task=expert_brief; difficulty=hard; step=5/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0

[Assistant] {"action_type":"submit"}


[System] Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy.

[Assistant] {"action_type":"submit"}


[System] Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy.

[User]
Decision checklist:
- task: expert_brief
- required experts: analyst, finance, strategy, hr
- already consulted: analyst, finance, strategy, hr
- still missing: none
- brief composed: True
- choose the single next action

[Assistant] {"action_type":"submit"}


[System] Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy.

[User] You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True.

[Assistant] {"action_type":"submit"}


[System] Act as AutoDataLab++ Chief of Staff. Choose the next orchestration step. Return strict JSON only with keys action_type, expert_id, sub_question_id, notes. Valid actions: consult, ask, summarize, submit, noop. Valid experts: analyst, finance, hr, strategy.

[User] state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?

[Assistant] {"action_type":"submit"}


[System] You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation.

[User]
task_name: expert_brief
task_difficulty: hard
step_count: 5
max_steps: 14
rag_enabled: True
available_experts: ['analyst', 'finance', 'hr', 'strategy']
required_experts: ['analyst', 'finance', 'strategy', 'hr']
consulted_experts: ['analyst', 'finance', 'strategy', 'hr']
missing_required_experts: []
current_brief_present: True
data_quality_score: 1.0
recent_issues: ['brief_composed']
instruction: Run the full office: data quality and KPIs on Q3, finance forecast and variance vs plan, strategy view on the NVDA/AAPL/JPM watchlist aligned to our numbers, and a crisp executive memo. When advanced memory (RAG) is on, tie strategy to SOPs and external tape; otherwise internal metrics only.

[Assistant] {"action_type":"submit"}


[System] You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation.

[User] Task=expert_brief; difficulty=hard; step=5/14; rag=True; required=['analyst', 'finance', 'strategy', 'hr']; consulted=['analyst', 'finance', 'strategy', 'hr']; missing=[]; brief_ready=True; dq=1.0

[Assistant] {"action_type":"submit"}


[System] You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation.

[Assistant] {"action_type":"submit"}


[System] You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation.

[User]
Decision checklist:
- task: expert_brief
- required experts: analyst, finance, strategy, hr
- already consulted: analyst, finance, strategy, hr
- still missing: none
- brief composed: True
- choose the single next action

[Assistant] {"action_type":"submit"}


[System] You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation.

[User] You are at step 5 for expert_brief. Consulted experts are ['analyst', 'finance', 'strategy', 'hr']. The brief is summarized and ready for final submission. RAG mode is True.

[Assistant] {"action_type":"submit"}


[System] You are a routing policy for a CEO brief environment. Consult missing required experts first, then summarize, then submit. Output one JSON object only; no markdown and no explanation.

[User] state: task=expert_brief | required=['analyst', 'finance', 'strategy', 'hr'] | consulted=['analyst', 'finance', 'strategy', 'hr'] | missing=[] | has_brief=True | action?

[Assistant] {"action_type":"submit"}