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 sc-doublet-detectiongit 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/sc-doublet-detection)<a href="https://agentmods.dev/skills/tiangzlab/omicsclaw/sc-doublet-detection"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-doublet-detection/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/sc-doublet-detection"><img src="https://agentmods.dev/badge/skills/tiangzlab/omicsclaw/sc-doublet-detection.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 | $0.00069 | $0.01346 |
| Opus 5 | $0.00034 | $0.00673 |
| Sonnet 5 | $0.00014 | $0.00269 |
| Haiku 4.5 | $0.00007 | $0.00135 |
Grade A, and why
sc-doublet-detection 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 5d 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sc-doublet-detection
When to use
The user has filtered (or at least QC'd) single-cell counts and wants
to flag putative doublet barcodes before clustering / annotation.
Five backends share one CLI: scrublet (default, Python), doubletdetection
(Python), doubletfinder (R), scdblfinder (R), scds (R). Per-cell
scores + binary calls land in obs; this skill annotates, it does not
remove cells (filter downstream with obs["predicted_doublet"]).
Inputs & Outputs
Inputs
- Modalities: scrna
- File types:
.h5ad
Outputs
tables/cell_metadata.csvtables/doublet_calls.csvtables/doublet_summary.csvtables/doubletfinder_results.csvtables/embedding_points.csvtables/group_summary.csvtables/scdblfinder_results.csvtables/scds_results.csvtables/summary.csvfigures/embedding_doublet_calls.pngfigures/embedding_doublet_scores.pngfigures/embedding_doublet_vs_group.pngfigures/r_embedding_discrete.pngfigures/r_embedding_feature.pngfigures/r_feature_violin.pnganalysis_summary.txtinput.h5adprocessed.h5adreport.mdresult.json- Processed AnnData (
saves_h5ad) — addsobs:doublet_score,predicted_doublet,doublet_classification
Flow
- Load AnnData; resolve
--methodagainst theMETHOD_REGISTRY. - Run the chosen backend (R-backed methods need a working R + rpy2 stack).
- If the requested R backend fails, fall back deterministically to a Python sibling.
- Apply the chosen
--threshold(or method default) to score → call. - Write
obs["predicted_doublet"]+obs["doublet_score"]; emit tables and the score-distribution figure. - Save
processed.h5ad+report.md+result.json.
Gotchas
- R backends silently fall back.
sc_doublet.py:304logs"DoubletFinder runtime failed (...). Falling back to scDblFinder."and continues;sc_doublet.py:359does the same forscds → cxds. After every R-method run, confirmresult.json["summary"]["method_used"]matches what you asked for — the--method doubletfinderflag does not guarantee DoubletFinder ran. - Explicit
--scds-mode(e.g.bcdsorhybrid) silently falls back to thecxdsdefault on failure.sc_doublet.py:359swaps modes when the requested one raises; the requested mode is not surfaced as an error, only logged. Inspect the warning log when the report claimsscdsran with the default. - No cells are removed. This skill annotates barcodes; downstream filtering on
obs["predicted_doublet"]is the user's responsibility. Ifsc-filterwas already run, doublets re-introduce themselves to the cluster graph if not filtered after this step. - Group summary is conditional.
tables/group_summary.csvis only written when--batch-keyis set; absence does not mean failure. - Embedding pre-flight is non-fatal.
sc_doublet.py:429logs"Preview embedding computation failed"and continues; the score-distribution figure still renders without the embedding overlay. When the figure looks sparse vs documented examples, check the warning log before assuming a bug. - Unsupported method → hard fail.
sc_doublet.py:801raisesValueError("Unsupported method: ...")for typos like--method scrubblet.
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.
- 5d ago First seen · 115 lines · 69 tokens per session scan A 7c0927a07c66
sc-doublet-detection is a skill published in the GitHub repository TianGzlab/OmicsClaw (160 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 69 tokens to every session and 1,346 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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