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116524e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | #!/usr/bin/env python3
"""Clean v4 Haiku skillbook: remove harmful/duplicate skills, merge near-duplicates, update incomplete ones.
Changes from v3 (79 skills):
- Remove 2 harmful skills contradicting airline policy (00001, 00002)
- Remove 5 duplicates (00068, 00080, 00078, 00020, 00101)
- Merge 00091+00092 into single name-change verification skill
- Update 00041 with urgency from deleted 00101
- Update 00009 with full baggage allowance table (3 tiers × 3 cabins)
- Update 00007 with cancellation eligibility rules
Expected result: 72 skills (79 - 7 removed)
"""
import argparse
import json
from pathlib import Path
DEFAULT_INPUT = Path("tau_benchmark_results/cleaned_haiku_skillbook.json")
DEFAULT_OUTPUT = Path("tau_benchmark_results/cleaned_v4_haiku_skillbook.json")
# Skills to remove entirely
REMOVE_IDS = {
# Harmful: contradicts airline policy
"reservation_management-00001", # "Accept contextual justifications for policy exceptions"
"reservation_management-00002", # "Process cancellations without additional verification"
# Duplicate of 00004+00011: "request IDs upfront"
"reservation_management-00068",
"task_management-00080",
# Duplicate of 00033: "modification sequencing"
"flight_modification-00078",
# Duplicate of 00069: "identity verification"
"fraud_prevention-00020",
# Merged into 00041: "task transition timing"
"task_management-00101",
}
# Merge 00091 + 00092 → keep 00092 with merged content, remove 00091
MERGE_REMOVE = "passenger_management-00091"
def main():
parser = argparse.ArgumentParser(description="Clean skillbook v4")
parser.add_argument("--input", type=Path, default=DEFAULT_INPUT)
parser.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
args = parser.parse_args()
data = json.loads(args.input.read_text())
before = len(data["skills"])
assert before == 79, f"Expected 79 skills, got {before}"
# 1. Remove harmful and duplicate skills
for sid in REMOVE_IDS:
removed = data["skills"].pop(sid, None)
assert removed is not None, f"Skill {sid} not found"
# 2. Merge 00091 into 00092
assert MERGE_REMOVE in data["skills"], f"{MERGE_REMOVE} not found"
data["skills"].pop(MERGE_REMOVE)
s92 = data["skills"]["passenger_management-00092"]
s92["content"] = (
"Verify old and new passenger names explicitly before executing name change: "
"confirm current name on reservation matches, then confirm new name with user"
)
s92["helpful"] = 2 # sum of both
# 3. Update 00041: add urgency from 00101
s41 = data["skills"]["task_management-00041"]
s41["content"] = (
"Transition explicitly between tasks with confirmation before moving to the next task; "
"move from information gathering to action execution within the first few conversation steps"
)
# 4. Update 00009: full baggage allowance table (3 tiers × 3 cabins)
s09 = data["skills"]["baggage_policy-00009"]
s09["content"] = (
"Baggage allowance (checked bags per person): "
"Regular — economy:1, business:2, first:3; "
"Silver — economy:2, business:3, first:3; "
"Gold — economy:3, business:3, first:3. "
"All tiers get 1 free carry-on and 1 personal item."
)
# 5. Update 00007: add cancellation eligibility rules
s07 = data["skills"]["reservation_management-00007"]
s07["content"] = (
"Follow all required flight_cancellation workflow steps sequentially: "
"identify_reservation, check_cancellation_eligibility, confirm_cancellation_policy, "
"process_cancellation, provide_confirmation. "
"Cancellation is only allowed if: booked within last 24 hours, OR flight was cancelled by airline, "
"OR cabin is business/first, OR reservation has travel insurance. "
"The API does NOT enforce eligibility — the agent must check these conditions."
)
# 6. Rebuild sections index
new_sections: dict[str, list[str]] = {}
for sid, skill in data["skills"].items():
sec = skill["section"]
new_sections.setdefault(sec, []).append(sid)
data["sections"] = new_sections
after = len(data["skills"])
expected = before - len(REMOVE_IDS) - 1 # -1 for merge
assert after == expected, f"Expected {expected} skills, got {after}"
args.output.write_text(json.dumps(data, indent=2) + "\n")
print(f"Cleaned: {before} -> {after} skills ({before - after} removed/merged)")
print(f"Sections: {sorted(data['sections'].keys())}")
print(f"Updated skills: 00007, 00009, 00041, 00092")
print(f"Saved to {args.output}")
if __name__ == "__main__":
main()
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