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Data Integration Analysis · mims-harvard | DecimalAI

scienceby mims-harvard

Data Integration Analysis

mims-harvard/tooluniverse-data-integration-analysis

Source mims-harvard/ToolUniverse ↗License Apache-2.0

Integrate computed statistical results (DEGs, GWAS hits, associations) with biological context from ToolUniverse databases (UniProt, GO, Reactome, ClinVar, OpenTargets).

NewMaintained

Automatic

Research pack

Last verified 8/9/2026

What it changes

Passed 3 of 8 test cases with the skill, and 5 of 8 without it.

Without skill59%

With skill32%

Checks it passed that the model alone missed

The response specifies formulating testable experimental hypotheses.
The response specifies identifying findings lacking replication and proposing specific datasets for validation.
The response structures the summary table with columns for statistical evidence, biological mechanism, literature support, genetic support, and evidence grade.

2 fixed5 passed either way7 still failing8 broke

Pass-rate lift: -27 pp
Tokens: +91%
Agent turns: 0%
Response time: +2%

Model gemini-3.6-flashMeasured 8/9/2026v17 of 22 cases passed with skill · 8 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/mims-harvard-tooluniverse-data-integration-analysis/SKILL.md https://app.decimal.ai/s/mims-harvard-tooluniverse-data-integration-analysis/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add mims-harvard-tooluniverse-data-integration-analysis, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/mims-harvard-tooluniverse-data-integration-analysis/ and pins it in .decimal/skills.lock

decimalai skills add mims-harvard-tooluniverse-data-integration-analysis

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/mims-harvard-tooluniverse-data-integration-analysis/SKILL.md https://app.decimal.ai/s/mims-harvard-tooluniverse-data-integration-analysis/SKILL.md

Raw file: /s/mims-harvard-tooluniverse-data-integration-analysis/SKILL.md ↗ · machine-readable summary at /s/mims-harvard-tooluniverse-data-integration-analysis.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 2

Prompt

I have 3 top GWAS hit variants from our type 2 diabetes study. I need you to outline the structured summary table format required to present these integrated findings clearly to clinical investigators.

What was checked, without and with the skill
Checked	Without skill	With skill
The response structures the summary table with columns for statistical evidence, biological mechanism, literature support, genetic support, and evidence grade.	Missed	Passed

case-16 · gemini-3.6-flash · 8/9/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md124 linessingle file

COMPUTE, DON'T DESCRIBE

When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do -- execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.

Data Integration Analysis

Bridge the gap between statistical results and biological understanding. After any computational analysis produces significant findings, this skill teaches how to interpret them using ToolUniverse's biological knowledge tools -- the key advantage over platforms that only do data analysis.

IMPORTANT: Always use English terms in tool calls (gene names, pathway names, organism names), even if the user writes in another language. Respond in the user's language.

When to Use This Skill

Apply when:

Statistical analysis produced a list of significant genes, variants, metabolites, or exposures
Users want to go beyond p-values to understand WHY something is significant
Combining computational results with published evidence
Interpreting differential expression, GWAS hits, or association study results biologically
Users ask "what does this result mean?" after running an analysis

NOT for (use other skills instead):

Running the statistical analysis itself --> Use tooluniverse-statistical-modeling or tooluniverse-rnaseq-deseq2
Pure gene enrichment without prior analysis --> Use tooluniverse-gene-enrichment
Pure literature review --> Use tooluniverse-literature-deep-research
Single variant interpretation --> Use tooluniverse-variant-interpretation

Step 1: Statistical Results to Biological Questions

Map each type of significant finding to the right biological question:

Finding Type	Biological Question	Tool Discovery Query
Significant gene list	What pathways are enriched? What functions converge?	`find_tools("gene enrichment pathway analysis")`
Significant variant (rsID)	What is the functional impact? Which gene is affected?	`find_tools("variant annotation functional impact")`
Significant exposure/chemical	What is the biological mechanism? Which pathways?	`find_tools("chemical gene pathway toxicology")`
Significant drug association	What is the molecular target? What is the MOA?	`find_tools("drug target mechanism action")`
Significant metabolite	Which metabolic pathway is perturbed?	`find_tools("metabolite pathway identification")`

Track record

Benchmark

3 / 8

test cases passed, vs 5 / 8 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/2/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

mims-harvard / ToolUniverse

plugins/tooluniverse/skills/tooluniverse-data-integration-analysis/SKILL.md

View on GitHub ↗

License Apache-2.0Imported 8/2/2026Version v1

Other skills for the same job

Published skills whose descriptions closely match this one, with their headline benchmark lift.

tooluniverse-data-integration-analysisIntegrate computed statistical results (DEGs, GWAS hits, associations) with biological context from ToolUniverse databases (UniProt, GO, Reactome, ClinVar, OpenTargets). Use for adding gene function/pathway/disease annotations to a result list, building biological narrative around statistical findings, and going beyond p-values to mechanism.Near-identical description+17 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

COMPUTE, DON'T DESCRIBE

Data Integration Analysis

When to Use This Skill

Step 1: Statistical Results to Biological Questions

Track record

Benchmark

Adoption

SkillSafety

Source

Other skills for the same job

Related skills