TO

tooluniverse-drug-research

Generates evidence-based research reports on drugs, mechanisms, and clinical trials.

Install

mkdir -p .claude/skills/tooluniverse-drug-research && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1959" && unzip -o skill.zip -d .claude/skills/tooluniverse-drug-research && rm skill.zip

Installs to .claude/skills/tooluniverse-drug-research

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory work.
325 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Advanced

Key capabilities

  • Resolve chemical compound identifiers
  • Grade scientific evidence with T1-T4 scores
  • Trace drug mechanism of action
  • Compile full clinical/safety profiles

How it works

Queries clinical and chemical databases to aggregate information, applying evidence grading and section-specific completion logic.

Inputs & outputs

You give it
Name of drug or chemical compound
You get back
Full technical report including pharmacology and trials

When to use tooluniverse-drug-research

  • Generating a drug mechanism report
  • Finding clinical trial status for a compound
  • Assembling safety data for regulatory research

About this skill

Drug Research Strategy

Comprehensive drug investigation using 50+ ToolUniverse tools across chemical databases, clinical trials, adverse events, pharmacogenomics, and literature.

KEY PRINCIPLES:

  1. Report-first approach - Create report file FIRST, then populate progressively
  2. Compound disambiguation FIRST - Resolve identifiers before research
  3. Citation requirements - Every fact must have inline source attribution
  4. Evidence grading - Grade claims by evidence strength (T1-T4)
  5. Mandatory completeness - All sections must exist, even if "data unavailable"
  6. English-first queries - Always use English drug/compound names in tool calls, even if the user writes in another language. Only try original-language terms as a fallback. Respond in the user's language

LOOK UP, DON'T GUESS

When asked about a drug, query ChEMBL/PubChem/DailyMed FIRST. Don't guess at mechanism, targets, or side effects — look them up. When you're not sure about a fact, your first instinct should be to SEARCH for it using tools, not to reason harder from memory.


Drug Mechanism Reasoning

When investigating a drug's mechanism of action, trace the full causal chain:

  1. Target engagement - Which protein(s) does the drug bind, and with what affinity/selectivity?
  2. Molecular effect - Does binding inhibit, activate, or modulate the target's function?
  3. Pathway consequence - Which signaling or metabolic pathway is altered downstream?
  4. Cellular phenotype - What changes occur at the cell level (proliferation, apoptosis, secretion)?
  5. Physiological outcome - How does the cellular effect translate to the therapeutic benefit in the patient?

Workflow Overview

1. Report-First Approach (MANDATORY)

DO NOT show the search process or tool outputs to the user. Instead:

  1. Create the report file FIRST - [DRUG]_drug_report.md with all 11 section headers and [Researching...] placeholders. See REPORT_TEMPLATE.md for the full template.
  2. Progressively update the report - Replace placeholders with findings as you query each tool.
  3. Use ALL relevant tools - Query multiple databases for each data type; cross-reference across sources.

2. Citation Requirements (MANDATORY)

Every piece of information MUST include its source. Use inline citations:

*Source: PubChem via `PubChem_get_compound_properties_by_CID` (CID: 4091)*

3. Progressive Writing Workflow

Step 1:  Create report file with all section headers
Step 2:  Resolve compound identifiers -> Update Section 1
Step 3:  Query PubChem/ADMET-AI/DailyMed SPL -> Update Section 2 (Chemistry)
Step 4:  Query FDA Label MOA + ChEMBL + DGIdb -> Update Section 3 (Mechanism)
Step 5:  Query ADMET-AI tools -> Update Section 4 (ADMET)
Step 6:  Query ClinicalTrials.gov -> Update Section 5 (Clinical)
Step 7:  Query FAERS/DailyMed -> Update Section 6 (Safety)
Step 8:  Query PharmGKB -> Update Section 7 (Pharmacogenomics)
Step 9:  Query DailyMed/Orange Book -> Update Section 8 (Regulatory)
Step 10: Query PubMed/literature -> Update Section 9 (Literature)
Step 11: Synthesize findings -> Update Executive Summary & Section 10
Step 12: Document all sources -> Update Section 11 (Data Sources)

Compound Disambiguation (Phase 1)

CRITICAL: Establish compound identity before any research.

Identifier Resolution Chain

1. PubChem_get_CID_by_compound_name(compound_name)
   -> Extract: CID, canonical SMILES, formula

2. ChEMBL_search_molecules(query=drug_name)
   -> Extract: ChEMBL ID, pref_name

3. DailyMed_search_spls(drug_name)
   -> Extract: Set ID, NDC codes (if approved)

4. PharmGKB_search_drugs(query=drug_name)
   -> Extract: PharmGKB ID (PA...)

Handle Naming Ambiguity

IssueExampleResolution
Salt formsmetformin vs metformin HClNote all CIDs; use parent compound
Isomersomeprazole vs esomeprazoleVerify SMILES; separate entries if distinct
Prodrugsenalapril vs enalaprilatDocument both; note conversion
Brand confusionDifferent products same nameClarify with user

Research Paths Summary

Each path has detailed tool chains and output examples in REPORT_GUIDELINES.md.

PATH 1: Chemical Properties & CMC

Tools: PubChem properties -> ADMET-AI physicochemical -> ADMET-AI solubility -> DailyMed chemistry/description Output: Physicochemical table, Lipinski assessment, QED score, salt forms, formulation comparison

PATH 2: Mechanism & Targets

Tools: DailyMed MOA -> ChEMBL activities (NOT ChEMBL_get_molecule_targets) -> ChEMBL target details -> DGIdb -> PubChem bioactivity Critical: Derive targets from activities filtered to pChEMBL >= 6.0. Avoid ChEMBL_get_molecule_targets. Output: FDA MOA text, target table with UniProt/potency, selectivity profile

PATH 3: ADMET Properties

Tools: ADMET-AI (bioavailability, BBB, CYP, clearance, toxicity) Fallback: DailyMed clinical_pharmacology + pharmacokinetics + drug_interactions Critical: If ADMET-AI fails, automatically use fallback. Never leave Section 4 empty.

PATH 4: Clinical Trials

Tools: search_clinical_trials -> compute phase counts -> extract outcomes/AEs -> fda_pharmacogenomic_biomarkers Critical: Section 5.2 must show actual counts by phase/status in table format.

PATH 5: Post-Marketing Safety

Tools: FAERS (reactions, seriousness, outcomes, deaths, age) + DailyMed (DDI, dosing, warnings) Critical: Include FAERS date window, seriousness breakdown, and limitations paragraph.

PATH 6: Pharmacogenomics

Tools: PharmGKB (search -> details -> annotations -> guidelines) Fallback: DailyMed pharmacogenomics section + PubMed literature

PATH 7: Regulatory & Patents

Tools: FDA Orange Book (search, approval history, exclusivity, patents, generics) + DailyMed (special populations via LOINC codes) Note: US-only data; document EMA/PMDA limitation.

PATH 8: Real-World Evidence

Tools: ClinicalTrials.gov (OBSERVATIONAL studies) + PubMed (real-world, registry, surveillance)

PATH 9: Comparative Analysis

Tools: Abbreviated tool chains for each comparator + head-to-head trial search + PubMed meta-analyses


FDA Label Core Fields

For approved drugs, retrieve these DailyMed sections early (after getting set_id):

BatchSectionsMaps to Report
Phase 1mechanism_of_action, pharmacodynamics, chemistrySections 2-3
Phase 2clinical_pharmacology, pharmacokinetics, drug_interactionsSections 4, 6.5
Phase 3warnings_and_cautions, adverse_reactions, dosage_and_administrationSections 6, 8.2
Phase 4pharmacogenomics, clinical_studies, description, inactive_ingredientsSections 5, 7

Fallback Chains

Primary ToolFallbackUse When
PubChem_get_CID_by_compound_nameChEMBL_search_drugsName not in PubChem
ChEMBL_get_molecule_targetsUse ChEMBL_search_activities insteadAlways avoid this tool
ChEMBL_get_activityPubChemBioAssay_get_assay_summaryNo ChEMBL ID
DailyMed_search_splsPubChemTox_get_acute_effectsDailyMed timeout
PharmGKB_search_drugsDailyMed PGx sections + PubMedPharmGKB unavailable
PharmGKB_get_dosing_guidelinesDailyMed pharmacogenomics sectionPharmGKB API error
FAERS_count_reactions_by_drug_eventDocument "FAERS unavailable" + use label AEsAPI error
ADMETAI_* (all tools)DailyMed clinical_pharmacology + pharmacokineticsInvalid SMILES or API error

Quick Reference: Tools by Use Case

Use CasePrimary ToolFallbackEvidence
Name -> CIDPubChem_get_CID_by_compound_nameChEMBL_search_drugsT1
PropertiesPubChem_get_compound_properties_by_CIDADMET-AI physicochemicalT1/T2
FDA MOADailyMed_parse_clinical_pharmacology (mechanism_of_action)-T1
TargetsChEMBL_search_activities -> ChEMBL_get_targetDGIdb_get_drug_infoT1
ADMETADMETAI_predict_* (5 tools)DailyMed PK sectionsT2/T1
Trialssearch_clinical_trials-T1
Trial outcomesextract_clinical_trial_outcomes-T1
FAERSFAERS_count_reactions_by_drug_eventLabel adverse_reactionsT1
Dose modsDailyMed_parse_clinical_pharmacology (dosage, warnings)-T1
PGxPharmGKB_search_drugsDailyMed PGx + PubMedT2/T1
LabelDailyMed_search_splsPubChemTox_get_acute_effectsT1
LiteraturePubMed_search_articlesEuropePMC_search_articlesVaries
RegulatoryFDA_OrangeBook_* toolsDailyMed label dataT1

See TOOLS_REFERENCE.md for the complete tool listing with parameters and input format requirements.


Type Normalization

Many tools require string inputs. Always convert IDs before API calls:

  • ChEMBL IDs, PubMed IDs, NCT IDs: convert int -> str
  • SMILES for ADMET-AI: pass as list ["SMILES_STRING"]
  • FAERS drug names: use UPPERCASE (e.g., "METFORMIN")
  • ChEMBL IDs: full format "CHEMBL1431" not "1431"
  • PharmGKB IDs: PA prefix "PA450657" not "450657"

Common Use Cases

Use CasePrimary SectionsLight Sections
Approved Drug ProfileAll 11 sectionsNone
Investigational Compound1, 2, 3, 4, 95, 6, 7, 8
Safety Review1, 5, 6, 7, 92, 3, 4, 8
ADMET Assessment1, 2, 43, 5, 6, 7, 8, 9
Clinical Development Landscape1, 5, 92, 3, 4, 6, 7, 8

Always maintain all section headers but adjust depth based on query focus and data availability.


When NOT to Use This Skill

  • Target research -> Use target-intelligence-gatherer skill
  • Disease research -> Use disease-resea

Content truncated.

When not to use it

  • Non-pharmaceutical research
  • Situations requiring real-time diagnostic advice

Prerequisites

Access to pharmacological databases

Limitations

  • Strictly for research, not clinical decision support
  • Data availability dependent on external registry sources

How it compares

Requires citation of every fact and uses a structured evidence-grading system.

Compared to similar skills

tooluniverse-drug-research side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
tooluniverse-drug-research (this skill)32moNo flagsAdvanced
scientific-critical-thinking187moReviewAdvanced
scholar-evaluation42moReviewIntermediate
literature-review5592moReviewAdvanced

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