pytdc-therapeutics-data-commons SKILL.md skillA
pytdc-therapeutics-data-commons from jaechang-hits/sciagent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add jaechang-hits/sciagent-skills/pytdc-therapeutics-data-commons@git:20260428.81ea2d2Pins git:20260428.81ea2d2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- jaechang-hits/sciagent-skills
- Path
skills/structural-biology-drug-discovery/pytdc-therapeutics-data-commons/SKILL.md- Versions recorded
- 2
- Latest version
- git:20260428.81ea2d2, committed Apr 28, 2026
- First version recorded
- Feb 18, 2026
- Size
- 17,933 bytes
- Repository stars
- 381
- License
- a license file GitHub does not identify
Therapeutics Data Commons (TDC) AI-ready drug discovery datasets. Curated ADME, toxicity, DTI, DDI with scaffold/cold splits, standardized metrics, molecular oracles, and ADMET benchmarks for therapeutic ML and property prediction. For chemical database queries use chembl-database-bioactivity; for featurization use molfeat.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# PyTDC (Therapeutics Data Commons) ## Overview PyTDC is an open-science platform providing AI-ready datasets and benchmarks for drug discovery. It organizes therapeutics data into three categories: single-instance prediction (molecular/protein properties), multi-instance prediction (drug-target interactions), and generation (molecule design, retrosynthesis). All datasets come with standardized splits, evaluation metrics, and molecular oracles. ## When to Use - Loading curated ADME, toxicity, or bioactivity datasets for ML model training - Benchmarking drug discovery models with standardized 5-seed evaluation protocols - Predicting drug-target or drug-drug interactions with proper cold-split evaluation - Generating novel molecules and scoring them with molecular oracles (QED, SA, DRD2, GSK3B) - Accessing scaffold-based or temporal train/test splits for pharmaceutical ML - Converting molecular representations (SMILES to PyG graphs, ECFP fingerprints, SELFIES) - For chemical database queries (compound search, bioactivity), use `chembl-database-bioactivity` instead - For molecular featurization beyond format conversion, use `molfeat` instead ## Prerequisites ```bash …
Read the whole file at its exact version.
How to install
mdr add jaechang-hits/sciagent-skills/pytdc-therapeutics-data-commons@sha256:6ed7e70efc0448fcThe line at the top of this page pins the label git:20260428.81ea2d2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_xkotf65ygfzch4te)
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Versions
The registry has recorded 2 versions of this file, between Feb 18, 2026 and Apr 28, 2026, about one every 69 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260428.81ea2d2 latest | 2026-04-28 | 81ea2d2 | 17,933 B | A | view · diff |
| git:20260218.8df1694 | 2026-02-18 | 8df1694 | 18,054 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (17933 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
jaechang-hits/sciagent-skills · 381 stars · license a license file GitHub does not identify · pushed 2026-10-16 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_xkotf65ygfzch4te GET https://markdownregistry.com/api/v1/resolve?ref=jaechang-hits/sciagent-skills/pytdc-therapeutics-data-commons GET https://markdownregistry.com/api/v1/blob/6ed7e70efc0448fc0483f10e965aedf1be38d5b1fddc681aa84eb18e2b2070f7
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.