Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/gptomics/bioskills/splicing-quantificationnpx skills add GPTomics/bioSkills --skill splicing-quantificationgit clone --depth 1 https://github.com/GPTomics/bioSkillsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00187 | $0.07168 |
| Opus 5 | $0.00093 | $0.03584 |
| Sonnet 5 | $0.00037 | $0.01434 |
| Haiku 4.5 | $0.00019 | $0.00717 |
Grade A, and why
bio-splicing-quantification scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- bio-splicing-quantification — 97% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: rMATS-turbo 4.3+, SUPPA2 2.4+, leafcutter 0.2.9+, MAJIQ 3.0+, IRFinder-S 2.0+, kallisto 0.50+, Salmon 1.10+, pandas 2.2+, STAR 2.7.11+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - R:
packageVersion('<pkg>')then?function_nameto verify parameters - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Splicing Quantification
Quantify alternative splicing events as PSI (percent spliced in) from RNA-seq. PSI = inclusion read evidence / (inclusion + skipping read evidence), normalized for differential mapping opportunity between isoforms. The choice of quantification unit (event, intron cluster, LSV, transcript) determines which biological questions can be answered and which failure modes apply.
Algorithmic Taxonomy
| Family | Unit | Reference tools | Fails when |
|---|---|---|---|
| Event-based | Pre-defined SE/A5SS/A3SS/MXE/RI events from annotation | rMATS-turbo, SUPPA2, VAST-TOOLS | Event isn't in annotation; complex multi-junction events split arbitrarily; AFE/ALE confounded with splicing |
| LSV-based | Local Splice Variations at single source/target nodes | MAJIQ V3 | Memory-constrained environments; cohorts smaller than ~3 reps; non-academic users (license) |
| Junction-cluster | Annotation-free intron clusters by shared splice sites | leafcutter, leafcutter2 | Undersampled clusters lose power; topology biologically uninterpretable for novel events |
| Splice-graph | Graph nodes (non-overlapping exonic regions) | Whippet, Shiba | Whippet maintenance status uncertain since ~2022; complex multi-exon graphs |
| Coverage-aware (IR) | Intron body coverage + flanking junctions | IRFinder-S, S-IRFindeR, iREAD | Confounded by overlapping exons, repeats, low mappability regions |
| Isoform-based | Transcript abundance via EM | Salmon/kallisto + tximport | Salmon EM uncertainty propagates; many similar isoforms (TTN, MAPT) become indistinguishable |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 377 lines · 187 tokens per session scan A 5252e845e9e2
bio-splicing-quantification is a skill published in the GitHub repository GPTomics/bioSkills (1,198 stars, last pushed 18d ago), licensed MIT. It adds 187 tokens to every session and 7,168 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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