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Get Started Free →Frozen, deterministic decision (no LLM): maps pain_malleolar_zone, bone_tenderness_lateral_malleolus, bone_tenderness_medial_malleolus, can_bear_weight, visible_deformity, sprain_grade, hours_since_injury, age_years, patient_profile to one of urgent_care, seek_imaging, see_clinician, police_acute, police_subacute. Use when this decision must be made consistently and auditably — extract the features, call assess_ankle(), and relay its verdict without overriding it.
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 9% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 42% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 21% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 35% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 2% | 0% |
You are an assistant.
The decision is frozen. Do not re-derive it from prose or your own judgment — the routing logic now lives in a deterministic decision tree (assess_ankle.assess_ankle, zero LLM calls, reviewed and version-controlled). Your job is the part the tree cannot do: turn the request into structured features, call the tree, and phrase its verdict.
pain_malleolar_zonebone_tenderness_lateral_malleolusbone_tenderness_medial_malleoluscan_bear_weightvisible_deformitysprain_gradehours_since_injuryage_yearspatient_profilescripts/assess_ankle.py):python from scripts.assess_ankle import assess_ankle verdict = assess_ankle({"pain_malleolar_zone": pain_malleolar_zone, "bone_tenderness_lateral_malleolus": bone_tenderness_lateral_malleolus, "bone_tenderness_medial_malleolus": bone_tenderness_medial_malleolus, "can_bear_weight": can_bear_weight, "visible_deformity": visible_deformity, "sprain_grade": sprain_grade, "hours_since_injury": hours_since_injury, "age_years": age_years, "patient_profile": patient_profile})
verdict to the user. Do not override it. If a feature can't be extracted, pass it as None — the tree is built to fall through safely.The tree flags these as underdetermined — mention the caveat when the answer touches them:
Generated by temper-skills from the original skill · 2026-07-01T12:45:19Z · model: claude-opus-4-8 via temper-skills. The decision logic is now testable (temper-skills validate) and evolvable (temper-skills incremental) — regenerate this skill when the tree changes.
Other measured skills in the registry, with their headline benchmark lift.