CD scarf-single-cell
Analyze single-cell RNA-seq at million-cell scale with Scarf: out-of-core Zarr stores on disk or object storage, provenance-tracked artifacts, audited QC, clustering, markers and donor comparisons.
Analyze single-cell RNA-seq at million-cell scale with Scarf: out-of-core Zarr stores on disk or object storage, provenance-tracked artifacts, audited QC…
As a process D 44/100 · Unfinished process — References files that are not bundled: scripts/inspect_store.py
The same skill appears in 2 more places: agentic-awesome-skills, agentic-awesome-skills
How to improve
- For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 1
✓ No critical or high findings
Medium and low: 1
-
low Dangerous commands
cmd-background-processreferences/performance-and-export.md:116Starts a background / autostarted process (documentation of a security skill)nohup timeout 1800 python step_baseline.py > logs/baseline.log 2>&1 &
security skill
Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-long-hermesdescription is 197 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period) - warning
body-longSKILL.md body ≈ 5923 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: scripts/inspect_store.py - note
frontmatter-keyunknown frontmatter key "risk" - note
frontmatter-keyunknown frontmatter key "source" - note
frontmatter-keyunknown frontmatter key "source_repo" - note
frontmatter-keyunknown frontmatter key "source_type" - note
frontmatter-keyunknown frontmatter key "date_added" - note
frontmatter-keyunknown frontmatter key "license_source" - note
frontmatter-keyunknown frontmatter key "tools"
Process rating: all ten parameters 44/100
- 0Tools and files. 1 referenced file(s) missing: scripts/inspect_store.py
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 30Running it twice. 9 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 70Execution cost. Instruction body is 5923 tokens
- 85Steps. 51 steps, 1 vague phrases
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 15 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 tags): a typed call is more reliable
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +3Output format is not stated: the model decides each time
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +3Description length 197: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 51 items
- +4Has examples (1 code blocks)
- +4Reference files are cited in the instructions (11 of 11)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.