Borrowing it
Nothing to install: this file belongs to cafferychen777/ChatSpatial. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/cafferychen777/ChatSpatial/main/.agents/skills/cell-dynamics/SKILL.mdgit clone --depth 1 https://github.com/cafferychen777/ChatSpatialWrote 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/cafferychen777/chatspatial/cell-dynamics)<a href="https://agentmods.dev/skills/cafferychen777/chatspatial/cell-dynamics"><img src="https://agentmods.dev/badge/skills/cafferychen777/chatspatial/cell-dynamics/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/cafferychen777/chatspatial/cell-dynamics"><img src="https://agentmods.dev/badge/skills/cafferychen777/chatspatial/cell-dynamics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00086 | $0.01398 |
| Opus 5 | $0.00043 | $0.00699 |
| Sonnet 5 | $0.00017 | $0.00280 |
| Haiku 4.5 | $0.00009 | $0.00140 |
Grade A, and why
cell-dynamics 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 10d 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 — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cell Dynamics Analysis
Overview
This skill answers: How do cells change over time, and what are their fate decisions?
Two complementary approaches:
- RNA Velocity: Infers directionality from spliced/unspliced ratios
- Pseudotime/Trajectory: Orders cells along developmental paths
Decision Tree: Which Approach?
Q: Does your data have spliced/unspliced information?
│
├─ YES (velocyto/kallisto processed)
│ │
│ └─ RNA Velocity Analysis
│ ├─ scVelo (deterministic) - Fast, good default
│ ├─ scVelo (dynamical) - More accurate, slower
│ └─ VeloVI - Deep learning, handles noise
│ │
│ └─ Then: CellRank for fate probability
│
└─ NO (standard scRNA-seq/spatial)
│
└─ Pseudotime Analysis
├─ Palantir - Multi-lineage, fate probabilities
├─ DPT (Diffusion Pseudotime) - Classic, fast
└─ PAGA - Trajectory + clustering
RNA Velocity Workflow
Prerequisites
Data must contain:
adata.layers['spliced']: Spliced countsadata.layers['unspliced']: Unspliced counts
Check with: 'spliced' in adata.layers and 'unspliced' in adata.layers
Step 1: Preprocessing for Velocity
Velocity-specific preprocessing:
1. Filter genes by spliced/unspliced detection
2. Normalize spliced and unspliced separately
3. Compute moments (first/second order)
Step 2: Compute Velocity
Use analyze_velocity_data tool with method selection:
| Mode | Speed | Accuracy | When to Use |
|---|---|---|---|
| deterministic | Fast | Good | Initial exploration |
| stochastic | Moderate | Better | Publication, noisy data |
| dynamical | Slow | Best | Complex dynamics, time recovery |
Step 3: Visualize Velocity
Use visualize_data with plot_type="velocity":
subtype="stream": Velocity streamlines on embeddingsubtype="phase": Phase portraits for specific genessubtype="proportions": Spliced/unspliced ratiossubtype="heatmap": Velocity across pseudotime
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.
- 10d ago First seen · 200 lines · 86 tokens per session scan A b8af8f322818
cell-dynamics is a skill published in the GitHub repository cafferychen777/ChatSpatial (44 stars, last pushed 25d ago), licensed MIT. It adds 86 tokens to every session and 1,398 once invoked, about $0.0004 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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