Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
mims-harvard avatar

Tooluniverse Clinical Risk Scoring

  • 71 installs
  • 1.6k repo stars
  • Updated August 4, 2026
  • mims-harvard/tooluniverse

Helps with ai & agent building tasks.

About

tooluniverse-clinical-risk-scoring is a Claude Code skill in the AI & Agent Building category.

  • tooluniverse-clinical-risk-scoring
  • AI & Agent Building
  • AI-coding skill

Tooluniverse Clinical Risk Scoring by the numbers

  • 71 all-time installs (skills.sh)
  • +6 installs in the week ending Aug 4, 2026 (Skillselion tracking)
  • Ranked #5,673 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-clinical-risk-scoring

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs71
repo stars1.6k
Last updatedAugust 4, 2026
Repositorymims-harvard/tooluniverse

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Clinical Risk Scoring

Turn a clinical scenario into the right validated risk score, compute it with a deterministic calculator tool, and interpret the number into a clinical action. All 10 backing tools are pure-compute (no network, no API key) and return {status, data:{score, interpretation, components, ...}}.

This skill is decision-support only — see LIMITATIONS. It does not replace clinical judgment.

Step 1 — Map the scenario to the score(s)

Clinical scenarioScore(s)Tool(s)
Atrial fibrillation — stroke risk / anticoagulate?CHA2DS2-VASc and HAS-BLED (pair)ClinicalCalc_CHA2DS2_VASc + ClinicalCalc_HAS_BLED
Community-acquired pneumonia — severity / admit?CURB-65ClinicalCalc_CURB_65
Suspected sepsis (infection + ? deterioration)qSOFAClinicalCalc_qSOFA
Cirrhosis / chronic liver disease severityChild-Pugh and MELD-Na (pair)ClinicalCalc_Child_Pugh + ClinicalCalc_MELD_Na
Suspected DVT — pretest probabilityWells DVTClinicalCalc_Wells_DVT
Suspected PE — pretest probabilityWells PEClinicalCalc_Wells_PE
Primary CVD prevention — 10-yr risk / statin?ASCVDClinicalCalc_ASCVD_risk
Kidney function / renal drug dosing / CKD stageeGFR CKD-EPIClinicalCalc_eGFR_CKD_EPI

When the scenario names a pair, always run both — one alone is misleading (e.g. stroke risk without bleeding risk, or Child-Pugh without MELD-Na).

Step 2 — Gather the required inputs

Required vs optional inputs per tool (omitted booleans default to false/absent; omitted scalars are rejected when required):

ToolRequiredKey optional booleans/values
ClinicalCalc_CHA2DS2_VAScagechf, hypertension, diabetes, stroke_history(2pt), vascular_disease, female
ClinicalCalc_HAS_BLEDagehypertension, renal_disease, liver_disease, stroke_history, bleeding_history, labile_inr, drugs, alcohol
ClinicalCalc_CURB_65ageconfusion, elevated_urea(BUN>19), high_resp_rate(>=30), low_bp
ClinicalCalc_qSOFA(none)high_resp_rate(>=22), altered_mentation, low_sbp(<=100)
ClinicalCalc_Child_Pughbilirubin, albumin, inrascites(none/mild/moderate), encephalopathy(none/grade1-2/grade3-4)
ClinicalCalc_MELD_Nacreatinine, bilirubin, inr, sodiumdialysis (forces creatinine to 4.0)
ClinicalCalc_Wells_DVT(none)active_cancer, immobilization, recent_surgery, localized_tenderness, leg_swollen, calf_swelling, pitting_edema, collateral_veins, previous_dvt, alternative_diagnosis(-2)
ClinicalCalc_Wells_PE(none)clinical_dvt(3), pe_most_likely(3), tachycardia(1.5), immobilization(1.5), previous_vte(1.5), hemoptysis(1), malignancy(1)
ClinicalCalc_ASCVD_riskage(40-79), total_cholesterol, hdl_cholesterol, systolic_bpbp_treated, smoker, diabetes, female, race("white"/"black")
ClinicalCalc_eGFR_CKD_EPIcreatinine, agefemale

If a required value is missing, ask the user for it — do not guess. State explicitly which booleans you assumed false.

Step 3 — Compute

tu run ClinicalCalc_CHA2DS2_VASc '{"age":76,"female":true,"hypertension":true,"diabetes":true}'

Every tool returns data.score plus a human-readable data.interpretation and a data.components breakdown (per-factor points). MELD/eGFR/ASCVD also return unit; Child-Pugh returns child_pugh_class; Wells PE returns three_tier and two_tier. Echo the components so the user can audit which factors drove the score.

Step 4 — Interpret (per-score tables)

CHA2DS2-VASc (stroke risk in AF, 0–9)

ScoreStroke riskAction
0 (men) / 1 (women, sex point only)LowNo anticoagulation
1 (men)IntermediateConsider anticoagulation
>=2 (men) / >=3 (women)ElevatedOral anticoagulation recommended

HAS-BLED (major bleeding on anticoagulation, 0–9)

ScoreBleeding riskAction
0–2Low–moderateAnticoagulation reasonable
>=3HighCaution; correct reversible factors (BP, labile INR, antiplatelet/NSAID, alcohol), closer follow-up — NOT an automatic contraindication

How to weigh CHA2DS2-VASc + HAS-BLED together

A high HAS-BLED does not by itself withhold anticoagulation. If CHA2DS2-VASc meets the threshold, the stroke benefit usually outweighs bleeding risk; HAS-BLED instead flags modifiable risk factors to fix and patients needing closer monitoring. Only a very high, non-modifiable bleeding risk shifts the decision against anticoagulation.

CURB-65 (CAP severity, 0–5)

Score30-day mortalityDisposition
0–1Low (~1.5–3%)Outpatient
2Intermediate (~9%)Short-stay / inpatient admission
3–5High (~15–40%)Inpatient; assess for ICU at 4–5

qSOFA (sepsis screen, 0–3)

ScoreMeaning
0–1Lower risk — does not rule out sepsis; reassess
>=2Higher risk of poor outcome — escalate, full sepsis workup, consider full SOFA / lactate

qSOFA is a screen, not a diagnosis; a low score never excludes sepsis.

Child-Pugh (cirrhosis severity, class A/B/C)

ClassScore1-yr survival (approx)Meaning
A5–6~100%Well-compensated
B7–9~80%Significant functional compromise
C10–15~45%Decompensated; high surgical/anesthetic risk

MELD-Na (90-day mortality / transplant priority, 6–40)

MELD-Na90-day mortality (approx)Transplant relevance
<=9~2%Low priority
10–19~6%
20–29~20%Rising allocation priority
30–39~50%High priority
>=40>50%Highest priority

Pair with Child-Pugh: Child-Pugh class anchors chronic severity / surgical risk; MELD-Na drives short-term mortality and transplant listing.

Wells DVT (pretest probability)

ScoreProbabilityWorkup
<2 (esp. <=0)DVT unlikelyD-dimer; if negative, DVT excluded
>=2DVT likelyProceed to compression ultrasound

Wells PE (pretest probability)

Two-tierThree-tierWorkup
PE unlikely (<=4)low (0–1) / moderate (2–6)D-dimer; if negative, PE excluded (consider PERC if very low)
PE likely (>4)high (>6)CT pulmonary angiography (D-dimer not sufficient to exclude)

ASCVD 10-year risk (%)

Risk %CategoryStatin guidance (with shared decision-making)
<5%LowLifestyle
5–7.4%BorderlineConsider if risk-enhancers present
7.5–19.9%IntermediateModerate-intensity statin reasonable
>=20%HighHigh-intensity statin

eGFR CKD-EPI (mL/min/1.73m^2) → CKD stage

eGFRStageNote
>=90G1Normal (CKD only if other markers of damage)
60–89G2Mildly decreased
45–59G3aMild–moderate
30–44G3bModerate–severe
15–29G4Severe — nephrology referral
<15G5Kidney failure

Use eGFR for renal drug dosing and CKD staging; a single value is an estimate — confirm with a repeat/eGFR trend for staging.

Worked example A — Atrial fibrillation, weigh anticoagulation (paired)

76-year-old woman with AF, hypertension, type 2 diabetes; on an NSAID; no prior stroke/bleed, BP controlled, stable INR.

tu run ClinicalCalc_CHA2DS2_VASc '{"age":76,"female":true,"hypertension":true,"diabetes":true}'
# -> score 5: "Elevated risk (5) — oral anticoagulation recommended"
#    components: Age>=75 2, Hypertension 1, Diabetes 1, Female 1

tu run ClinicalCalc_HAS_BLED '{"age":76,"hypertension":true,"drugs":true}'
# -> score 3: "High bleeding risk (3) — caution, review reversible factors"
#    components: Hypertension_uncontrolled 1, Elderly_>65 1, Drugs_antiplatelet_NSAID 1

Interpretation. CHA2DS2-VASc 5 (>=3 for a woman) → anticoagulation recommended. HAS-BLED 3 is high but driven by modifiable factors: stop the NSAID and control BP and 2 of the 3 points disappear, lowering bleeding risk. The high HAS-BLED does not cancel anticoagulation — it directs you to fix reversible risks and monitor more closely.

Worked example B — Cirrhosis severity and transplant priority (paired)

Cirrhotic patient: bilirubin 3.5 mg/dL, albumin 2.5 g/dL, INR 2.4, moderate ascites, grade 1–2 encephalopathy; creatinine 2.0, sodium 128, not on dialysis.

tu run ClinicalCalc_Child_Pugh '{"bilirubin":3.5,"albumin":2.5,"inr":2.4,"ascites":"moderate","encephalopathy":"grade1-2"}'
# -> score 14, child_pugh_class "C": "Class C (score 14): decompensated disease"

tu run ClinicalCalc_MELD_Na '{"creatinine":2.0,"bilirubin":5.0,"inr":2.0,"sodium":128,"dialysis":false}'
# -> score 31: "MELD-Na 31: very high ... 90-day mortality risk"

Interpretation. Child-Pugh class C (14) = decompensated cirrhosis, very high surgical/anesthetic risk — avoid elective surgery. MELD-Na 31 implies roughly a third-or-higher 90-day mortality and a high transplant-allocation priority. Together they justify urgent hepatology / transplant evaluation. (Note MELD uses bilirubin 5.0 and INR 2.0 from this patient's labs; lower bounds of 1.0 are applied internally.)

Completeness checklist

  • [ ] Picked the score(s) that match the scenario — ran both members of a pair (CHA2DS2-VASc+HAS-BLED, Child-Pugh+MELD-Na)
  • [ ] Confirmed all required inputs; asked for missing ones rather than guessing
  • [ ] Stated which optional booleans were assumed false
  • [ ] Reported score, interpretation, and the components breakdown
  • [ ] Mapped the score to a clinical action using the interpretation table
  • [ ] For pairs, explained how to weigh the two scores together
  • [ ] Stated the LIMITATIONS caveat (decision-support, validated population, ASCVD age 40–79)

LIMITATIONS

  • Decision-support only. These scores inform, but do not replace, clinical judgment and the full clinical picture. Do not present output as a treatment directive.
  • Validated populations. Each score was derived/validated in specific cohorts and may not transfer to children, pregnancy, valvular AF (CHA2DS2-VASc is for non-valvular AF), or other excluded groups.
  • ASCVD Pooled Cohort Equations are validated only for ages 40–79 and the White / African-American coefficient sets; they can mis-estimate for other ancestries and are for primary prevention (no prior ASCVD event).
  • eGFR CKD-EPI assumes stable kidney function (steady-state creatinine); it is unreliable in acute kidney injury, extremes of muscle mass, or amputees, and a single value does not stage CKD on its own.
  • qSOFA / CURB-65 / Wells are screening / pretest-probability tools — a reassuring score does not exclude the diagnosis; combine with clinical gestalt and confirmatory testing.
  • MELD-Na / Child-Pugh apply to chronic liver disease; they do not capture acute liver failure or hepatocellular-carcinoma exception points.
  • Inputs are taken at face value — garbage in, garbage out. Verify lab units (mg/dL vs mmol/L, BUN vs urea) before entry.
  • Not a substitute for institutional protocols, guideline updates, or specialist consultation.

Related skills

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.