Staffer.tool_level now controls which subsystems a specific run gets:
full — qwen3.5 + qwen3 + cloud T3 + cloud rescue
local — qwen3.5 + qwen3 + local gpt-oss:20b T3 + rescue
basic — qwen2.5 + qwen2.5 + local T3, no rescue
minimal — qwen2.5 + qwen2.5, NO T3, NO rescue. Playbook
inheritance only.
applyToolLevel() mutates module-scoped ACTIVE_* slots each run from the
env defaults, so prior staffer's overrides never leak. Hot-path code
reads ACTIVE_EXECUTOR / ACTIVE_REVIEWER / ACTIVE_T3_DISABLED /
ACTIVE_OVERVIEW_CLOUD / ACTIVE_RETRY_ON_FAIL instead of the baked
constants.
The architectural question this answers: does playbook_memory
inheritance carry enough knowledge to let a weakly-tooled coordinator
still produce usable outcomes? "Minimal" Alex runs qwen2.5 exec + no
reviewer overseer + no cloud rescue. If Alex still fills events at a
reasonable rate, the playbook system is the real knowledge carrier —
the senior stack is nice-to-have, not the sine qua non.
Demo personas mapped:
Maria (senior, 48mo, full)
James (mid, 14mo, local)
Sam (junior, 4mo, basic)
Alex (trainee, 1mo, minimal)
Same 3 contracts (Nashville downtown, Joliet warehouse, Indianapolis
assembly) across all four → 12 runs. KB + kb_staffer_report.py
leaderboard already wired; competence_score will now reflect real tool
asymmetry instead of LLM sampling variance.
73 lines
2.0 KiB
JSON
73 lines
2.0 KiB
JSON
{
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"client": "Riverline Logistics — Nashville Downtown Build-Out",
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"date": "2026-04-28",
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"contract": {
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"deadline": "2026-05-19",
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"budget_total_usd": 180000,
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"budget_per_hour_max": 32,
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"local_bonus_per_hour": 4,
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"local_bonus_radius_mi": 75,
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"fill_requirement": "paramount"
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},
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"staffer": {
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"id": "S-003",
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"name": "Sam Torres",
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"tenure_months": 4,
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"role": "junior",
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"tool_level": "basic"
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},
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"events": [
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{
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"kind": "baseline_fill",
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"at": "07:00",
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"role": "Welder",
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"count": 4,
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"city": "Nashville",
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"state": "TN",
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"shift_start": "07:00 AM",
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"scenario_note": "Staffed by Sam Torres (junior, 4mo). Contract deadline 2026-05-19, fill=paramount."
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},
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{
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"kind": "expansion",
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"at": "08:30",
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"role": "Packaging Operator",
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"count": 6,
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"city": "Nashville",
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"state": "TN",
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"shift_start": "08:30 AM",
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"scenario_note": "Staffed by Sam Torres (junior, 4mo). Contract deadline 2026-05-19, fill=paramount."
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},
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{
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"kind": "baseline_fill",
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"at": "09:00",
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"role": "Shipping Clerk",
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"count": 2,
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"city": "Nashville",
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"state": "TN",
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"shift_start": "09:00 AM",
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"scenario_note": "Staffed by Sam Torres (junior, 4mo). Contract deadline 2026-05-19, fill=paramount."
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},
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{
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"kind": "emergency",
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"at": "13:00",
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"role": "Welder",
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"count": 2,
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"deadline": "15:00",
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"city": "Nashville",
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"state": "TN",
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"shift_start": "13:00 PM",
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"scenario_note": "Staffed by Sam Torres (junior, 4mo). Contract deadline 2026-05-19, fill=paramount."
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},
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{
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"kind": "misplacement",
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"at": "15:30",
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"role": "Packaging Operator",
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"count": 1,
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"replaces_event": "08:30",
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"city": "Nashville",
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"state": "TN",
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"shift_start": "15:30 PM",
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"scenario_note": "Staffed by Sam Torres (junior, 4mo). Contract deadline 2026-05-19, fill=paramount."
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}
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]
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} |