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 TianGzlab/OmicsClaw --skill bulkrna-trajblendgit clone --depth 1 https://github.com/TianGzlab/OmicsClawWrote 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/tiangzlab/omicsclaw/bulkrna-trajblend)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/bulkrna-trajblend"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/bulkrna-trajblend/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/tiangzlab/omicsclaw/bulkrna-trajblend"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/bulkrna-trajblend.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Rogue Agent · line 3 Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
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 | $0.00065 | $0.01448 |
| Opus 5.5 | $0.00026 | $0.00579 |
| Sonnet 5.5 | $0.00013 | $0.00290 |
| Haiku 4.5 | $0.00006 | $0.00145 |
Grade A, and why
bulkrna-trajblend 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 17d 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.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
bulkrna-trajblend
When to use
Place bulk samples on an observed single-cell pseudotime axis and estimate
cell-type fractions. Use bulkrna-deconvolution for fractions without placement
and sc-pseudotime to infer a trajectory on the reference first.
Use from a step
from skills._sdk.notebook import load_skill, write_output
library = load_skill('bulkrna-trajblend')
data, reference, labels, pseudotime = library.demo_data(random_state=42)
result = library.map_trajectory(data, reference=reference, labels=labels, pseudotime=pseudotime)
write_output(result, 'tables/pseudotime_estimates.csv')
For real files, pass read_fastq, read_log or read_reference as appropriate
to read_input(..., reader=...). examples/example_step.py is executable.
API
read_reference(path: str | Path, *, cell_type_key: str='cell_type', pseudotime_key: str='pseudotime') -> tuple
Read a reference with annotations; pass this function as reader= to read_input.
:param path: H5AD with expression in X, or cell-by-gene CSV/TSV with annotation columns. :param cell_type_key: CLI default cell_type; change for a named annotation column. :param pseudotime_key: CLI default pseudotime; supply an observed reference trajectory value. :returns: Cell-by-gene DataFrame, indexed cell-type Series and indexed pseudotime Series. :raises ValueError: Required annotations are missing. :raises ImportError: H5AD reading needs anndata; install it with install_skill_deps.
map_trajectory(bulk: pd.DataFrame, *, reference: pd.DataFrame, labels: pd.Series, pseudotime: pd.Series, k: int=15, random_state: int=42) -> pd.DataFrame
Return bulk pseudotime estimates from NNLS and joint PCA/kNN placement.
:param bulk: Sample-by-gene nonnegative expression on a scale comparable with the reference. :param reference: Cell-by-gene expression with at least fifty shared genes. :param labels: Cell-type labels indexed by reference cell identifiers. :param pseudotime: Observed reference pseudotime indexed by cell identifiers; never synthesized. :param k: CLI default 15 nearest reference cells; reduce for a smaller reference. :param random_state: CLI seed 42 forwarded to PCA; change to assess randomized-solver sensitivity. :returns: New sample-indexed pseudotime table; fractions and embeddings remain in attrs. :raises ValueError: Matrices, annotations, gene overlap or neighbor count are invalid. :raises ImportError: Missing scipy/scikit-learn; use install_skill_deps.
What ships with it
7 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.
- 17d ago Changed · +68 lines 5afa75e3420d
- 1mo ago First seen · 86 lines · 65 tokens per session scan A c9db639f4f14
bulkrna-trajblend is a skill published in the GitHub repository TianGzlab/OmicsClaw (161 stars, last pushed 17d ago), licensed Apache-2.0. It adds 65 tokens to every session and 1,448 once invoked, about $0.0003 per session on Opus 5.5. 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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