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/tiangzlab/omicsclaw/spatial-registernpx skills add TianGzlab/OmicsClaw --skill spatial-registergit 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/spatial-register)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/spatial-register"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/spatial-register.svg" alt="Measured on agentmods" 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 | $0.00062 | $0.01796 |
| Opus 5 | $0.00031 | $0.00898 |
| Sonnet 5 | $0.00012 | $0.00359 |
| Haiku 4.5 | $0.00006 | $0.00180 |
Grade A, and why
spatial-register 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 yesterday.
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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
spatial-register
When to use
The user has a multi-slice spatial AnnData (slices stacked into one
object with a --slice-key column) and wants the slices registered
into a shared coordinate frame so a downstream analysis can use the
common axes. Two methods:
paste(default) — PASTE optimal-transport alignment based on gene expression similarity + spatial proximity (--paste-alpha,--paste-dissimilarity). Requirespaste-bio+pot(+ optionaltorchfor GPU).stalign— STalign image-aware diffeomorphic registration; best when histology images are available (--stalign-niter,--stalign-image-size,--stalign-a). RequiresSTalign+torch.
For expression-space batch correction across slices use
spatial-integrate. For aligning a single slice to a reference atlas
use the same skill with that atlas as the reference slice.
Inputs & Outputs
Inputs
- Modalities: visium, xenium
- File types:
.h5ad - Requires a preprocessed AnnData (
Xnormalised, PCA/neighbours present)
Outputs
tables/registration_disparities.csvtables/registration_metrics.csvtables/registration_points.csvtables/registration_run_summary.csvtables/registration_shift_by_slice.csvtables/registration_summary.csvfigures/registration_disparities.pngfigures/registration_shift_by_slice.pngfigures/registration_shift_distribution.pngfigures/registration_shift_map.pngfigures/slices_after.pngfigures/slices_before.pngprocessed.h5adreport.mdresult.json- Processed AnnData (
saves_h5ad) — addsobsm:spatial_aligned,spatial,X_spatial
Flow
- Load AnnData (
--input) or build a multi-slice demo via the bundledspatial-preprocessrunner (chains across slices). parser.errorvalidates numeric flag ranges (--paste-alpha∈ [0, 1];--stalign-niter/-image-size/-a> 0).- Resolve
--slice-key(auto-pick fromslice/sample/library_idif unset); raise if< 2slices. - Pick a reference slice (largest by default) and align all others to it.
- For PASTE: compute pairwise transport plans using
--paste-alpha(gene-vs-spatial weight); apply translations. - For STalign: run iterative image-aware diffeomorphism with
--stalign-niteriterations. - Save
processed.h5ad(registered coords inobsm["spatial_aligned"]; originalobsm["spatial"]preserved unchanged), tables, figures,report.md,result.json.
What ships with it
8 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.
- yesterday First seen · 132 lines · 62 tokens per session scan A 84ca31d559ed
spatial-register is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 62 tokens to every session and 1,796 once invoked, about $0.0003 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 2026-09-03.
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