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research-paper-writing

Improve academic paper writing quality for ML/CV/NLP-style papers with clear section structure, paragraph flow, and reviewer-facing presentation. Use when drafting or revising Abstract, Introduction, Related Work, Method, Experiments, or Conclusion; polishing figures/tables; checking claim-support alignment; or performing self-review before submission.

79

Quality

100%

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SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-3

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

The body is a tight overview that delegates detail to clearly signaled, verified reference files, with concrete workflows, validation checkpoints, and a defined output contract. It satisfies the top anchor on all four content dimensions.

DimensionReasoningScore

Conciseness

The body is lean and assumes competence — it never explains what a paper or a paragraph is, and every line gives actionable instruction rather than padding; it sits at the 'every token earns its place' anchor.

3 / 3

Actionability

As an instruction-only skill it provides concrete, specific guidance — a reverse-outlining procedure, a paragraph-clarity checklist, and a copy-ready output contract ('Claim: ... | Evidence: ... | Status: supported/needs evidence'); the instruction-only note means absence of code is not penalized.

3 / 3

Workflow Clarity

The Core Workflow is a clear numbered sequence with an explicit validation checkpoint ('Check every major claim in Abstract/Introduction against experimental evidence') and a feedback loop (adversarial self-review -> revise), satisfying the clear-sequence-with-checkpoints anchor.

3 / 3

Progressive Disclosure

The SKILL.md body is an overview that signals one-level-deep references to per-section guides and an examples bank index; referenced files (e.g. references/examples/index.md and the section guides) exist and are organized for discovery, matching the well-signaled-reference anchor.

3 / 3

Total

12

/

12

Passed

Description

100%Weight 40%Scale 1-3

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 concise, concrete, and complete: it states what the skill does, when to use it via an explicit 'Use when' clause, and targets a distinct academic-writing niche. It matches the strongest rubric anchors on all four dimensions.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'clear section structure, paragraph flow, and reviewer-facing presentation', 'polishing figures/tables', 'checking claim-support alignment', and 'self-review before submission' — matching the multi-action anchor rather than the single-action level below.

3 / 3

Completeness

Explicitly answers both 'what' ('Improve academic paper writing quality...') and 'when' ('Use when drafting or revising...'), with an explicit 'Use when' clause rather than only implied timing.

3 / 3

Trigger Term Quality

Natural user-facing terms are well covered ('Abstract, Introduction, Related Work, Method, Experiments, or Conclusion', 'polishing figures/tables', 'self-review before submission'), with good variation rather than a single keyword.

3 / 3

Distinctiveness Conflict Risk

A clear niche (ML/CV/NLP academic paper writing) with distinct section-based triggers makes it unlikely to fire for unrelated skills.

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

referenced_paths_exist

Referenced path issues: 1 deeper-than-1-level

Warning

Total

15

/

16

Passed

Repository
Master-cai/Research-Paper-Writing-Skills
Reviewed

Table of Contents

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