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research-literature-radar

发现、筛选并长期归档重要研究论文;当用户要求按主题寻找经典、rising star、社区精选、热点或顶会/顶刊论文时使用。采用分层发现策略,调用 research-literature-search 完成其中的关键词/数据库检索,再由本 skill 负责多渠道汇总、idea-level 价值判断、论文类型分类、跨轮次跟踪和论文库归档。

68

Quality

83%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

75%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 well-structured, actionable orchestration skill body with clear sequencing, validation checkpoints, and concrete file/ID/score contracts. It is efficient and appropriately references real bundle scripts, with only minor tightening and CLI-example gaps.

Suggestions

Add a one-line executable example or CLI usage for scripts/catalog.py (as is done for validate_layout.py) so the ID-generation/dedup path is copy-paste ready.

Trim the verbatim common-constraints block or summarize it, since the duplicated content competes with the context window without adding skill-specific value.

Provide a compact inline checklist or numbered sequence for the main flow so the multi-step pipeline reads as a single ordered workflow rather than scattered subsections.

DimensionReasoningScore

Conciseness

Mostly efficient and assumes competence without teaching basics, though the duplicated common-constraints block and a few repeated boundary statements could be tightened.

4 / 5

Actionability

Concrete and specific — names scripts (catalog.py, validate_layout.py), exact catalog.jsonl fields, ID format, scoring dimensions, and hash-conflict rule — though exact CLI invocations for catalog.py are not shown.

4 / 5

Workflow Clarity

Clear sequenced flow from catalog load through search-bundle consumption, hard-filter, scoring, quota fill, dedup, run output, to a 交付前确认 checklist, with explicit validation and failure/recovery checkpoints.

4 / 5

Progressive Disclosure

Body is well-structured with clear headers and inline, one-level-deep references to real bundle scripts at their points of use; only minor organization gaps since most detail lives inline rather than in separate reference files.

4 / 5

Total

16

/

20

Passed

Description

92%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, third-person description that states concrete capabilities and an explicit use-when trigger with five paper-type cues. It clearly distinguishes the skill from a sibling search skill.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 发现/筛选/归档 plus 多渠道汇总、idea-level 价值判断、论文类型分类、跨轮次跟踪、论文库归档 — covering the skill's domain comprehensively.

5 / 5

Completeness

Explicitly answers both 'what' (发现、筛选、归档、汇总、判断、分类、跟踪) and 'when' ('当用户要求按主题寻找…时使用') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural user phrasing is present ('按主题寻找经典、rising star、社区精选、热点或顶会/顶刊论文') with five paper-type synonyms, though a few additional natural variants could be named.

4 / 5

Distinctiveness Conflict Risk

Explicitly carves a niche apart from research-literature-search (keyword/db retrieval only), with distinct triggers and minimal overlap risk.

5 / 5

Total

19

/

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.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
huangwb8/ChineseResearchLaTeX
Reviewed

Table of Contents

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