TCR-Epitope Binding (bioSkills)

A Claude Code skill that infers or annotates TCR antigen specificity through clustering and database lookup, with supervised predictors framed under explicit reliability caveats.


Type	Claude Skill
Supplier	GPTomics bioSkills (community OSS, MIT)
Availability	GA — part of the bioSkills collection
Pricing	Free / OSS (MIT)
Capabilities	Read/Write — Claude runs the skill’s workflow locally (Bash/Python), not as an MCP tool
Verified	works · 2026-07-20
Security	cleared · 2026-07-20 — provenance matches GPTomics/bioSkills, MIT, no advisories

How to install

bioSkills is not an npm package — skills are plain markdown/code read directly by the agent. Clone the repo, then either run the installer for the whole category or copy the single skill directory.

Claude Code — clone and install via the bundled script:
```
git clone https://github.com/GPTomics/bioSkills
cd bioSkills
./install-claude.sh --categories "immunoinformatics"
```
The installer copies matching skills into ~/.claude/skills/ (default target). Use ./install-claude.sh --list to preview the skills first.
Claude Code / other agents — copy just this one skill:
```
cp -r bioSkills/immunoinformatics/tcr-epitope-binding ~/.claude/skills/
```
(run from inside your clone — the previous step left you in bioSkills/; otherwise replace bioSkills/ with the absolute path of your clone). The skill declares its external dependencies (tcrdist3, GLIPH2, clusTCR, GIANA, ERGO-II, NetTCR, pMTnet) in SKILL.md; install them when prompted on first use.

What it does

Assigns TCR antigen specificity through a two-tier approach:

Clustering & lookup (the defensible task) — groups TCRs likely sharing specificity using distance-based methods (tcrdist3, GLIPH2, clusTCR, GIANA) and matches against curated databases (VDJdb, IEDB, McPAS-TCR) with confidence filtering, operating within single cohorts to avoid HLA and background confounds.
Caveated supervised prediction — ranks candidates with ERGO-II, NetTCR-2.x, and pMTnet, under the explicit warning that “general TCR-epitope prediction for unseen epitopes essentially does not work” (training data dominated by immunodominant epitopes, absence of true negatives).

The skill is emphatic that clustering is the defensible discovery task while per-pair predictions on novel epitopes require wet-lab validation (e.g., tetramer assays) and should never substitute for functional experiments.

Primary use cases: TCR specificity annotation, antigen-specific clonotype discovery via clustering, ranking TCR-epitope candidates for validation.

Notes

Distributed as a SKILL.md (plus reference material) in the bioSkills collection — Claude executes the workflow locally via Bash/Python rather than as an MCP server. The upstream skill front-matter name is bio-immunoinformatics-tcr-epitope-binding; if you invoke it as a namespaced plugin command it resolves under the bioSkills plugin, not as a bare /tcr-epitope-binding. Complements the single-cell/bulk repertoire skills (scirpy-analysis, mixcr-analysis, immcantation-analysis). Several bundled predictors and databases require separate download/registration from their vendors. Upstream directory: immunoinformatics/tcr-epitope-binding.

Sources

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