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 skills add PKU-YuanGroup/OpenAI4S --skill bio-alternative-splicing-long-read-splicinggit clone --depth 1 https://github.com/PKU-YuanGroup/OpenAI4SWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-alternative-splicing-long-read-splicing)<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-alternative-splicing-long-read-splicing"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-alternative-splicing-long-read-splicing/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pku-yuangroup/openai4s/bio-alternative-splicing-long-read-splicing"><img src="https://agentmods.dev/badge/skills/pku-yuangroup/openai4s/bio-alternative-splicing-long-read-splicing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00000 | $0.06593 |
| Opus 5 | $0.00000 | $0.03297 |
| Sonnet 5 | $0.00000 | $0.01319 |
| Haiku 4.5 | $0.00000 | $0.00659 |
Grade A, and why
bio-long-read-splicing 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 12d 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.
This is a copy
95% identical to bio-long-read-splicing — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 496 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: FLAIR 2.0+, IsoQuant 3.5+, Bambu 3.4+, SQANTI3 5.4+, minimap2 2.26+, samtools 1.19+, rMATS-long 0.2+, IsoSeq3 4.0+
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.
Long-Read Splicing Analysis
Full-length long-read sequencing solves problems that short-read AS cannot: anchor-length-limited microexon detection, complex multi-exon isoform deconvolution, recursive splicing in long introns, and transcript-quantification uncertainty in DTU. The 2024-2026 transition: long-read is becoming the splicing default for high-resolution analysis.
When Long-Read Wins
| Question | Why long-read wins |
|---|---|
| Microexon detection (3-27 nt) | Reads span the microexon entirely; no aligner anchor problem |
| Long-intron recursive splicing | Can detect ratchet point usage (Sibley 2015 Nature) |
| Complex isoform deconvolution (TTN, MAPT, NEFM) | Single read per isoform avoids EM ambiguity |
| DTU without quantification uncertainty | Transcript identity is read-level, not inferred |
| Novel transcript discovery | No annotation dependence |
| Phasing splicing with SNVs | Allele-resolved isoforms |
| Single-cell full-length isoforms | MAS-Iso-seq + 10X 5' is the practical SOTA |
| Cryptic splicing in TDP-43 ALS | Full-length reads confirm cryptic exon inclusion in target transcripts |
Platform Selection Matrix
| Platform | Throughput | Accuracy (modal) | Best for | Fails when |
|---|---|---|---|---|
| PacBio Revio HiFi (Iso-Seq) | ~25M reads / SMRT cell | Q30+ (CCS) | Bulk transcript discovery; gold standard | Cost prohibitive for very large cohorts |
| PacBio Kinnex / MAS-Iso-seq | ~16x Iso-Seq via concatemer | Q30+ | High-throughput single-cell long-read | Kinnex de-array (skera) is an extra step |
| ONT direct cDNA (R10.4.1, PCS-114) | Millions / flowcell | ~98% simplex, ~99% duplex | Cost-effective; throughput | Minor higher error than HiFi |
| ONT direct RNA (RNA004, 2024+) | ~30M reads | ~96-98% | Native modifications (m6A, pseudo-U); no RT bias | Lower throughput; higher input |
| ONT pre-R10 (R9.4.1) | Same as R10 | ~85-90% | Legacy data | Pre-R10 not recommended for splicing analysis (false novel junctions) |
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.
- 12d ago First seen · 496 lines · 0 tokens per session scan A 3eb43fc5e323
bio-long-read-splicing is a skill published in the GitHub repository PKU-YuanGroup/OpenAI4S (407 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 6,593 tokens. A static security scan graded it A with 0 findings. It is 95% identical to bio-long-read-splicing, differing in 12 lines, and is treated as a copy.
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