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paper-figure

Generate publication-quality figures and tables from experiment results. Use when user says \"画图\", \"作图\", \"generate figures\", \"paper figures\", or needs plots for a paper.

Quality

76%

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tessl review fix ./skills/skills-codex/paper-figure/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

63%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.

A highly actionable, well-sequenced workflow for generating publication figures, with concrete code, explicit render-level verification, and a strong correctness checklist. Its weaknesses are redundancy (repeated rules and a duplicated decision-tree table, plus tangential reviewer-routing boilerplate), and a monolithic structure with no working bundle references.

Suggestions

Deduplicate the body: state the no-titles and render-then-verify rules once, and merge the 'Figure Type Reference' table into Step 3's decision tree to save tokens.

Make paper_plot_style.py copy-paste ready by defining the constants inline (FONT_SIZE = 10, DPI = 300, FORMAT = 'pdf', FIG_DIR = 'figures/') instead of referencing undefined names, and replace Step 7 placeholders like [VENUE] with concrete fill-in instructions.

Add an explicit error-recovery loop after Step 5's render-then-verify (e.g., 'if labels clip or the legend covers data, adjust the script and re-run') to upgrade the batch workflow's validation to a full feedback loop.

DimensionReasoningScore

Conciseness

The body is mostly efficient and actionable but contains clear duplication: the no-titles rule appears three times (Step 8 checklist, Key Rules), the Step 3 decision-tree table is repeated nearly verbatim in 'Figure Type Reference', render-then-verify is stated in both Step 5 and Step 8, and the opening reviewer-routing blockquote is dense boilerplate tangential to figure generation. This fits anchor 3 ('could be tightened') rather than anchor 2, since it never explains basic concepts or pads heavily.

3 / 5

Actionability

Concrete, near-executable guidance throughout: a full matplotlib rcParams style script, runnable per-figure Python for line and bar charts, a bash run loop, and complete LaTeX table/include snippets. Minor gaps keep it below anchor 5: paper_plot_style.py uses undefined constants (FONT_SIZE, DPI, FORMAT, FIG_DIR) so it isn't copy-paste ready as written, and Step 7 contains unfilled placeholders ([VENUE], [list all figures...]).

4 / 5

Workflow Clarity

A clear 8-step sequence with explicit validation checkpoints — verify outputs exist and are non-empty, render-then-verify self-check with specific criteria (no clipped labels, legend not covering data), and a partitioned correctness/guidance checklist. It falls short of anchor 5 only because there is no explicit error-recovery loop (e.g., 'if the render check fails, fix the script and re-run') for this batch operation.

4 / 5

Progressive Disclosure

The file is well-sectioned with clear headers, but it is a ~320-line monolith with no bundle files at all: the quality checklist and figure-type reference tables are inlined content that could live in separate files, and the one reference given (../shared-references/reviewer-backends.md) plus reviewer_route.py point outside the bundle and don't resolve. This matches anchor 3 (some structure, references not clearly resolvable, separate-worthy content inline) rather than anchor 4's mostly-appropriate placement.

3 / 5

Total

14

/

20

Passed

Description

78%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.

A strong description in third-person voice with an explicit 'Use when...' trigger clause covering both English and Chinese phrases. It clearly states what the skill does and when to use it; the main gaps are limited action granularity and a few missing natural trigger variants.

DimensionReasoningScore

Specificity

"Generate publication-quality figures and tables from experiment results" names the domain plus two concrete actions (figures, tables) but stops there — no mention of plot types, LaTeX tables, or style presets, matching anchor 3 rather than the 'several specific actions' of anchor 4.

3 / 5

Completeness

It explicitly answers both questions with concrete trigger phrases — "Generate publication-quality figures and tables from experiment results" (what) and "Use when user says ... or needs plots for a paper" (when) — structurally identical to the anchor-5 example, and clearer than anchor 4's weaker 'when'.

5 / 5

Trigger Term Quality

Natural triggers "画图", "作图", "generate figures", "paper figures", "needs plots for a paper" give good bilingual coverage, but common variations like "make plots", "visualize results", or "charts" are missing, so it falls short of anchor 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

"paper figures" and "publication-quality ... for a paper" carve a mostly distinct niche with minor overlap risk against general plotting/dataviz skills triggered by the broader "generate figures"/"画图" phrases; not anchor 5 because those generic triggers could fire for a generic charting skill.

4 / 5

Total

16

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository

wanshuiyin/Auto-claude-code-research-in-sleep

Path

skills/skills-codex/paper-figure/SKILL.md

Reviewed

Table of Contents

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