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nature-polishing

Polish, restructure, or translate academic prose into Nature-leaning English using the paper-architecture and writing-strategy principles from Scientific English Writing & Communication, with phrase-level support from Academic Phrasebank. Use whenever the user asks to polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft for publication-quality English.

72

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

77%

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 a clear, validated workflow, but it is longer than necessary and has progressive-disclosure gaps — an orphaned bundle file and references to files not present in the bundle.

Suggestions

Tighten the Section responsibilities and Sentence/paragraph rules, which restate general academic-writing knowledge Claude already has; keep only the skill-specific framing (Nature-leaning, DeepScientist hygiene, Chinese-to-English mode).

Add references/writing-strategy.md to the "When to open extra files" table with an "Open when" trigger, or remove the file if it is not intended to be consulted.

Either bundle the cited Chapter1-Week1-7 notes and UPSTREAM_LICENSE.txt, or replace those references with the actual provided files so every body reference resolves to a real bundle path.

DimensionReasoningScore

Conciseness

The ~380-line body is dense and skill-specific, but it restates fairly standard academic-writing principles (hourglass structure, Introduction/Results/Discussion responsibilities, keep-sentences-short) that a capable model partly already knows and could be tightened.

2 / 3

Actionability

Provides concrete, actionable guidance for an instruction-only skill: hard word limits ("<= 30 words"), a forbidden-vague-phrase list, an explicit abstract structure, a failure-mode diagnosis list, and a defined output format.

3 / 3

Workflow Clarity

Defines a clear sequenced process (the 6-step core architecture plus a prioritization order), with validation checkpoints (diagnose failure mode before editing, overclaim check in the conclusion, proofreading checklist) and checklists for citation and AI-boundary decisions.

3 / 3

Progressive Disclosure

Has a well-signaled one-level-deep "When to open extra files" table with triggers, but references/writing-strategy.md exists in the bundle yet is not surfaced in that table, and the body cites Chapter1-Week1-7 and UPSTREAM_LICENSE.txt which are absent from the bundle.

2 / 3

Total

10

/

12

Passed

Description

100%

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, trigger-rich, and explicitly pairs capabilities with a "Use whenever" activation clause, covering what and when in third-person voice. It is a strong, low-conflict skill description.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Polish, restructure, or translate academic prose into Nature-leaning English" — and enumerates concrete section types, matching the anchor for multiple specific concrete actions.

3 / 3

Completeness

Clearly answers both what (polish/restructure/translate into Nature-leaning English) and when via the explicit "Use whenever the user asks to polish a manuscript paragraph..." trigger clause, satisfying the anchor for both what AND when.

3 / 3

Trigger Term Quality

Surfaces natural terms a user would actually say ("polish a manuscript paragraph, abstract, introduction, results, discussion, conclusion, title, methods section, or Chinese academic draft"), giving good coverage rather than jargon.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (Nature-leaning academic polishing, Chinese-to-English manuscript drafts, publication-quality English) with distinct triggers unlikely to fire for unrelated skills; uses third-person imperative voice.

3 / 3

Total

12

/

12

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
ResearAI/DeepScientist
Reviewed

Table of Contents

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