multi-panel-figure-assembler

Assemble 6 sub-figures (A–F) into a high-resolution composite figure with consistent labels, padding, and publication-ready DPI.

Quality

74%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./scientific-skills/Other/multi-panel-figure-assembler/SKILL.md

Quality

Content

82%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 body is well-structured and highly actionable, with executable commands, a full parameter table, and strong up-front validation for a batch operation. Weaknesses are limited to light conciseness padding and under-signaling of the other bundled scripts.

Suggestions

Tighten the Fallback Template and Response Template blocks, or move one into a separate reference file, to reduce token weight.

Link to scripts/example.py (or note it) in the body so all bundle files are discoverable from SKILL.md.

Replace generic workflow steps 2–5 ("Confirm the user objective", "Return a structured result") with figure-assembly-specific actions to strengthen the feedback loop.

Dimension	Reasoning	Score
Conciseness	The body is efficient and avoids explaining concepts Claude already knows; the only minor padding is in the refusal message and the Fallback/Response templates, which could be trimmed slightly.	4 / 5
Actionability	Fully executable, copy-paste-ready commands in Usage and Quick Check, a complete Parameters table with defaults, and a concrete Prerequisites install line cover the common cases.	5 / 5
Workflow Clarity	Validation is emphasized as the absolute first action for this batch operation (avoiding the destructive/batch cap), but workflow steps 2–5 are somewhat generic and the error-recovery loop is report-and-correct rather than a full validate→fix→retry cycle.	4 / 5
Progressive Disclosure	Well-organized single-file SKILL.md with clear section headers and a reference to the real scripts/main.py; minor gap is that example.py and __init__.py exist in the bundle but are not signaled or linked in the body.	4 / 5
	Total	17 / 20 Passed

Description

66%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 is specific and well-scoped to a clear niche, with concrete feature terms and natural publishing vocabulary. Its main weakness is the absence of an explicit "Use when..." trigger clause, which limits completeness.

Suggestions

Add an explicit "Use when..." clause naming natural triggers, e.g. "Use when combining exactly 6 image panels (A–F) into a publication-ready composite figure, multi-panel figure, or figure grid."

Include common synonyms and file extensions (multi-panel figure, .png, .tif) to broaden trigger-term coverage.

Consider naming a second distinct action (e.g. "standardize label fonts and DPI across panels") to push specificity toward comprehensive coverage.

Dimension	Reasoning	Score
Specificity	Names the domain and several concrete features ("consistent labels, padding, and publication-ready DPI") but uses a single primary action verb ("Assemble") with attributes rather than multiple distinct actions, so it falls short of comprehensive coverage.	4 / 5
Completeness	It clearly answers "what" (assemble 6 sub-figures into a composite figure) but provides no "Use when..." clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric.	3 / 5
Trigger Term Quality	Good natural keywords ("sub-figures", "composite figure", "DPI", "publication-ready") that a user would say, but it omits common variations like "multi-panel" and file extensions (.png/.tif).	4 / 5
Distinctiveness Conflict Risk	The "exactly 6 sub-figures (A–F)" constraint carves a clear niche with distinct triggers, though there is minor overlap risk with general image/figure manipulation skills.	4 / 5
	Total	15 / 20 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
Path: scientific-skills/Other/multi-panel-figure-assembler/SKILL.md
Commit: 63c61d3

Reviewed: 11 hours ago

Table of Contents

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