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research-refine

Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan via iterative GPT-5.6-Sol review. Use when the user says "refine my approach", "帮我细化方案", "decompose this problem", "打磨idea", "refine research plan", "细化研究方案", or wants a concrete research method that stays simple, focused, and top-venue ready instead of a vague or overbuilt idea.

66

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Critical

Do not install without reviewing

SKILL.md
Quality
Evals
Security

Quality

Content

77%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.

An exceptionally actionable and clearly sequenced orchestration skill with concrete MCP calls, validation gates, and a robust review–revise feedback loop. Its weaknesses are length/redundancy (inlined reviewer prompt and four full report templates) and the absence of any reference bundle, leaving a monolithic file where progressive disclosure is limited to internal sectioning.

Suggestions

Move the large inlined reviewer rubric (the Phase 2 bundle contents block) and the full FINAL_PROPOSAL / REFINEMENT_REPORT templates into reference files under references/ and point to them, reducing SKILL.md to an overview and improving progressive_disclosure.

De-duplicate the Problem Anchor / proposal scaffold, which is restated in Step 1.6, Phase 3 revision output, and the final report templates; reference a single canonical template once.

Trim the four near-complete report templates (REVIEW_SUMMARY, FINAL_PROPOSAL, REFINEMENT_REPORT, score-history) to concise skeletons, keeping only the fields that differ, to lift conciseness toward the lean anchor.

DimensionReasoningScore

Conciseness

At ~770 lines the body is mostly process-specific and earns much of its length, but it inlines the full ~60-line reviewer prompt and four complete report templates (REVIEW_SUMMARY, FINAL_PROPOSAL, REFINEMENT_REPORT, score-history) with notable repetition of the Problem Anchor / proposal scaffold, fitting the "mostly efficient but could be tightened" anchor rather than the lean score 4.

3 / 5

Actionability

Provides copy-paste-ready MCP invocation blocks (model, config, prompt), concrete checkpoint JSON, exact file paths, an explicit 7-dimension reviewer scoring rubric, and fully specified markdown templates — matching the fully-executable-with-concrete-examples anchor.

5 / 5

Workflow Clarity

Phases 0–5 are explicitly sequenced with a checkpoint after every phase, an Anchor Check / Simplicity Check validation gate, a review→revise→re-evaluate feedback loop with a concrete stop condition (score >= 9 or MAX_ROUNDS), and a checkpoint-resume table for error recovery — matching the clear-sequence-with-explicit-validation-and-feedback-loops anchor.

5 / 5

Progressive Disclosure

No bundle files exist (references/scripts/assets absent), so the entire detailed procedure lives in one monolithic SKILL.md; it has clear section headers and signaled external links (Output Protocols → ../shared-references/*.md) but bulk content that belongs in separate files is inlined, fitting the "some structure but content that should be separate is inline" anchor.

3 / 5

Total

16

/

20

Passed

Description

86%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 with explicit trigger phrases (including bilingual synonyms) and a clear what-and-when structure; voice is correctly third-person/imperative with no first/second-person penalty. It is held back only by describing one qualified action rather than several discrete concrete actions, and by acknowledged overlap with sibling research skills.

DimensionReasoningScore

Specificity

Names the domain and one concrete action — "Turn a vague research direction into a problem-anchored, elegant, frontier-aware, implementation-oriented method plan" — but the heavy adjective stack describes a single output rather than listing several discrete actions, so it does not reach the multi-action coverage of score 4.

3 / 5

Completeness

Explicitly answers both "what" (turn a vague direction into a concrete method plan via iterative GPT-5.6-Sol review) and "when" (Use when the user says [concrete trigger phrases] or wants a concrete simple focused method), matching the explicit what-and-when-with-triggers anchor.

5 / 5

Trigger Term Quality

Provides comprehensive natural trigger phrases a user would actually say — "refine my approach", "decompose this problem", "refine research plan" — plus bilingual synonyms ("帮我细化方案", "打磨idea", "细化研究方案"), matching the comprehensive-synonyms anchor.

5 / 5

Distinctiveness Conflict Risk

The niche (iterative reviewer-driven research method refinement) and triggers are clearly distinct from generic skills, but it overlaps with closely related sibling skills the body itself names (/idea-creator, /experiment-plan), so it sits at the "mostly distinct, minor overlap risk" anchor rather than a clear standalone 5.

4 / 5

Total

17

/

20

Passed

Validation

81%

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

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (771 lines); consider splitting into references/ and linking

Warning

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

relative_links

Relative link issues: 3 suspicious

Warning

Total

13

/

16

Passed

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

Table of Contents

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