deepspot-m SKILL.md skillA
deepspot-m from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/deepspot-m@v1.2Pins v1.2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/deepspot-m/SKILL.md- Versions recorded
- 4
- Latest version
- v1.2, committed Oct 1, 2026
- First version recorded
- Aug 4, 2026
- Size
- 9,939 bytes
- Repository stars
- 56,497
- License
- MIT
Generates transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M. Used for predicted log1p-CPM expression from 224x224 tiles at about 20x, querying the released protein-coding gene panel by symbol, and whole-slide prediction after resolution-aware tiling with histolab.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# DeepSpot-M ## Overview DeepSpot-M is a multimodal foundation model that maps a 224x224 H&E histology tile to spatial gene expression in log1p-CPM. The output is virtual spatial transcriptomics: one value per queried gene per tile, laid out on the grid the tiles came from. A LoRA-adapted pathology foundation backbone (Midnight) tokenises the tile. A cross-attention gene decoder lets each gene query attend to the patch tokens, and a gene router hypernetwork builds gene-specific projections from frozen biological embeddings (Evo 2, Orthrus, ProtT5, scGPT, Apertus). Genes enter the model as queryable embeddings rather than fixed output slots, so the released model covers a ~19k protein-coding gene panel including genes unseen in training. The panel ships with the weights as `tokens.csv` and is exposed as `model.gene_names`; genes outside it cannot be queried in this release. Applied to TCGA, the model produced a virtual spatial transcriptomics atlas of 28,664 slides across 32 cancer types. ## Licensing The code is PolyForm Noncommercial 1.0.0 and the weights are CC-BY-NC-SA-4.0. The current model access form additionally restricts eligibility to academic/public …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/deepspot-m@sha256:a917434c523e136dThe line at the top of this page pins the label v1.2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_ilpxymwmkytrdkti)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between Aug 4, 2026 and Oct 1, 2026, about one every 20 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.2 latest | 2026-10-01 | a92663a | 9,939 B | A | view · diff |
| v1.1 | 2026-09-30 | ce9e6e9 | 7,786 B | A | view · diff |
| v1.0 | 2026-08-07 | 9477641 | 7,367 B | A | view · diff |
| v1.0 | 2026-08-04 | de981da | 6,997 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (9939 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_ilpxymwmkytrdkti GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/deepspot-m GET https://markdownregistry.com/api/v1/blob/a917434c523e136ddc1ce45b54acbef8c28398dd293314f72faa278431e67418
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.