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spatial-transcriptomics-mapper

Map spatial transcriptomics data from 10x Genomics Visium/Xenium onto.

43

Quality

54%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./scientific-skills/Data Analysis/spatial-transcriptomics-mapper/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The core operational content (commands, parameter table, input/output structures, API example) is accurate and executable, but the document is padded with duplicated wrapper sections and generic template boilerplate, scatters its workflow across redundant sections, and includes broken references to a missing test-data script and undefined parameters. It functions but wastes context and misleads on a few paths.

Suggestions

Remove the duplicated wrapper sections ("Key Features", "Implementation Details", the Quick Check/Audit-Ready Commands duplication, and the generic Risk/Security/Lifecycle/Evaluation boilerplate), keeping one dependency list and one description.

Fix broken references: either ship scripts/generate_test_data.py or drop the Quick Start test-data path, and remove the --hires/--downsample notes for parameters main.py does not define.

Consolidate the workflow into one sequenced section with explicit validation checkpoints (py_compile check → run with validated inputs → verify expected output files exist → fallback path on failure), and move API usage and audit details into separate reference files.

DimensionReasoningScore

Conciseness

The ~415-line body is noticeably padded: wrapper sections ("Key Features", "Dependencies", "Example Usage", "Implementation Details") that only point to other sections, "Quick Check" and "Audit-Ready Commands" repeating identical commands, two separate dependency listings, and generic template boilerplate (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) that applies to any skill rather than this one. Not score 1 because the core Usage/Parameters/Examples sections are skill-specific and free of educational filler.

2 / 5

Actionability

Provides copy-paste-ready commands, a parameter table that matches the actual argparse definitions in scripts/main.py (verified: platform, data-dir, gene/genes, mode, cluster-file, output, dpi, cmap, spot-size, alpha, min-count, crop), input/output file structures, and a working Python API example. Falls short of 5 because the Quick Start references a nonexistent scripts/generate_test_data.py, the Notes cite undefined --hires/--downsample parameters, and the Example Usage cd path is a non-portable internal directory.

4 / 5

Workflow Clarity

A reasonable sequence exists (confirm inputs → validate scope → py_compile check → run main.py → review output → fallback on failure), but it is scattered across five overlapping sections (Quick Check, Audit-Ready Commands, Example run plan, Workflow, Error Handling) with output verification left implicit and steps phrased abstractly ("Return a structured result that separates assumptions, deliverables, risks..."). Not score 4 because the duplication and abstraction blur the actual operational checkpoints.

3 / 5

Progressive Disclosure

Section structure exists and the script references that do exist (scripts/__init__.py, scripts/main.py) are real and clearly signaled, but everything is inlined in one long file — generic audit/security/lifecycle boilerplate and API details that belong in separate reference files — and the generate_test_data.py reference is broken (the file is absent from the bundle). Not score 2 because headers make the document navigable and script paths are surfaced rather than buried.

3 / 5

Total

12

/

20

Passed

Description

40%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description names a distinctive niche (10x Genomics Visium/Xenium spatial transcriptomics) but is grammatically truncated — "onto." with no stated target — and provides no 'Use when...' trigger guidance. It is clearly about a specific domain yet under-serves both capability description and skill triggering.

Suggestions

Complete the truncated sentence, e.g.: "Map spatial transcriptomics data from 10x Genomics Visium or Xenium onto tissue section images to visualize gene-space distribution, spatial clustering, and multi-gene overlays."

Add an explicit trigger clause: "Use when working with Visium or Xenium output, spatial gene expression data, or when the user asks to project gene expression onto tissue images."

Include natural synonyms and file types users would mention (e.g., "spatial gene expression", "Space Ranger output", ".h5 matrices") to broaden trigger term coverage.

DimensionReasoningScore

Specificity

Names the domain ("spatial transcriptomics", "10x Genomics Visium/Xenium") but the single action verb "Map ... onto" is truncated mid-phrase with no object, leaving the actions minimal and grammatically incomplete — closer to "Names the domain but actions are minimal or generic" than to the 1-2 concrete actions of the anchor above.

2 / 5

Completeness

Has only a truncated 'what' ("Map spatial transcriptomics data from 10x Genomics Visium/Xenium onto.") and no 'Use when...' clause or equivalent trigger guidance, which caps completeness at 3; the cut-off sentence keeps the 'what' short of the clear 'what' required for score 3.

2 / 5

Trigger Term Quality

Contains the natural platform keywords users would say ("spatial transcriptomics", "Visium/Xenium"), but misses common variations and synonyms such as "spatial gene expression", "tissue mapping", "Space Ranger output", or file formats like .h5. Not score 2 because the platform names are genuine natural trigger terms; not score 4 because coverage of synonyms and extensions is absent.

3 / 5

Distinctiveness Conflict Risk

The named platforms (Visium/Xenium) carve a distinct niche with low conflict risk, but the missing object of "onto" and the generic verb "Map" leave minor overlap risk with other bioinformatics mapping or general data-visualization skills.

4 / 5

Total

11

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

14

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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