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/shangbiolab/spatialclaw/spatial-regulationnpx skills add ShangBioLab/SpatialClaw --skill spatial-regulationgit clone --depth 1 https://github.com/ShangBioLab/SpatialClawWrote 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/shangbiolab/spatialclaw/spatial-regulation)<a href="https://agentmods.dev/skills/shangbiolab/spatialclaw/spatial-regulation"><img src="https://agentmods.dev/badge/skills/shangbiolab/spatialclaw/spatial-regulation.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 | $0.00018 | $0.00289 |
| Opus 5 | $0.00009 | $0.00144 |
| Sonnet 5 | $0.00004 | $0.00058 |
| Haiku 4.5 | $0.00002 | $0.00029 |
Grade A, and why
spatial-regulation 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 4d 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.
What it actually says
Spatial Regulation
Spatial Regulation infers transcription-factor activity and regulatory programs in spatial context.
Interface
Python API only. This skill is intentionally not registered for spatialclaw run or other CLI execution routing.
Python API
from skills.spatial._lib.regulation import run_regulation
result = run_regulation(adata, method="tf_activity", species="human")
Capabilities
- TF activity scoring from expression matrices.
- Optional SpaGRN and SCENIC-style regulatory workflows.
- Optional paired RNA/ATAC regulatory inference helpers.
- Spatial regulatory pattern summaries.
Validation
Covered by tests/spatial/test_library_only_skills.py::test_spatial_regulation_smoke.
What ships with it
1 file 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.
- 4d ago First seen · 50 lines · 18 tokens per session scan A 1484b3c85146
spatial-regulation is a skill published in the GitHub repository ShangBioLab/SpatialClaw (11 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 18 tokens to every session and 289 once invoked, about $0.0001 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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