d-molecule-ray-tracer

Generate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.

Quality

61%

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Data Analysis/3d-molecule-ray-tracer/SKILL.md

Quality

Content

65%

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

The body is highly actionable with concrete commands and parameter documentation, but it is padded with generic boilerplate, contains contradictory and broken navigation references, and points to a missing references/ directory.

Suggestions

Remove the generic template sections (Risk Assessment, Security Checklist, Lifecycle Status, Response Template) and the contradictory 'data analysis' When-to-Use line; keep only rendering-specific content.

Fix the broken 'See ## Features / Usage / Workflow above' pointers — those sections appear below, not above — or remove the cross-references.

Either create the referenced references/ files (PyMOL techniques, ChimeraX lighting, colorblind palettes, journal guidelines) or remove the 'See references/ for' section so navigation is not broken.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with concrete parameter tables and command examples, but padded with generic template sections (Risk Assessment, Security Checklist, Lifecycle Status, Output Requirements, Response Template) and contradictory 'When to Use' boilerplate about 'data analysis tasks' that does not belong in a rendering skill.	2 / 3
Actionability	Provides copy-paste-ready executable commands (e.g. 'python scripts/main.py --pdb 1mbn --preset cover'), a detailed parameters table, advanced-usage flag combinations, and a presets table — fully concrete and executable.	3 / 3
Workflow Clarity	A sequenced workflow with a py_compile validation checkpoint and an error/fallback path exists, but the steps are generic project-management boilerplate rather than a rendering-specific sequence, and overlapping 'Workflow', 'Example run plan', and 'Implementation Details' sections plus broken 'See ## X above' navigation muddy the sequence.	2 / 3
Progressive Disclosure	Section structure is present and scripts/main.py is a real bundled file, but the body is a monolithic ~320-line document and the 'See references/ for ...' pointer references a references/ directory that does not exist, so navigation is partly broken and content that could be split stays inline.	2 / 3
	Total	9 / 12 Passed

Description

57%

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 is specific and clearly niche-targeted, but it only states what the skill does without any explicit when-to-use trigger guidance, which limits completeness and trigger-term coverage.

Suggestions

Add a 'Use when...' clause naming concrete triggers, e.g. 'Use when creating publication-quality or cover molecular images in PyMOL or UCSF ChimeraX.'

Expand trigger terms to include natural user phrasings like 'molecular visualization', 'ray tracing', or 'journal figure'.

List more than one concrete action (e.g. ray-traced rendering, depth-of-field, ambient occlusion setup) to raise specificity.

Dimension	Reasoning	Score
Specificity	Names the domain and a concrete action — "Generate photorealistic rendering scripts for PyMOL and UCSF ChimeraX" — but lists only one action (script generation) rather than multiple specific actions, matching the anchor that names domain and some actions but is not comprehensive.	2 / 3
Completeness	Clearly states what the skill does but provides no "Use when..." trigger clause or equivalent explicit guidance on when to invoke it; per the guidelines a missing Use-when clause caps completeness at 2.	2 / 3
Trigger Term Quality	Includes relevant natural terms a user would say ("photorealistic rendering", "PyMOL", "UCSF ChimeraX", "rendering scripts") but misses common variations like "molecular visualization", "ray tracing", or "publication figures", so coverage is partial.	2 / 3
Distinctiveness Conflict Risk	Targets a clear niche — photorealistic rendering scripts for two specific molecular-visualization tools — with distinct triggers unlikely to collide with other skills.	3 / 3
	Total	9 / 12 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Commit: 7cc5680

Reviewed: 3 days ago

Table of Contents

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