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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。
Passed 17 of 19 test cases with the skill, and 7 of 19 without it.
and 11 more in the full report
10 fixed7 passed either way2 still failing0 broke3 errored
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
Before finalizing a radar run, we want to run a quality check to ensure that no temporary run files or report artifacts were accidentally written into the root `docs/papers/` directory. Which script should be called for this verification?
| Checked | Without skill | With skill |
|---|---|---|
| Invokes scripts/validate_layout.py. | Missed | Passed |
| Verifies that docs/papers/ root contains zero run-level files. | Passed | Passed |
The instructions your model reads when the skill loads.
把来自不同发现渠道的候选论文转成可持续维护的研究雷达。research-literature-search 只是本 skill 的一个检索子步骤，负责基于显式关键词的数据库召回、字段规范化、canonical 去重和 provenance；本 skill 仍负责分层发现、跨渠道汇总、价值判断、分类、跟踪与归档。
本 skill 负责：
用户提出“找值得读的论文”“建立某主题论文雷达”“按经典/热点/顶会等类型推荐论文”或类似发现与学习需求时触发。
必填：用户选题和目标数量。可选：领域/子主题、五类论文配额（classic、rising-star、community、hot、top-venue）、时间窗、作者/venue 白名单、排除项、是否下载公开 PDF、笔记深度。
运行前读取 .bensz-api/research-literature-radar/catalog.jsonl（不存在则创建），并保留用户原始请求和运行日期。
按用户请求和配置文件提供必要输入；缺失信息应明确列出并停止依赖该输入的步骤。
~/.bensz-skills/bugs/，当前任务继续；只有用户明确要求公开上报时，才使用本机 gh api 直传，不 clone 仓库。版本唯一来源为同目录 config.yaml:skill_info.version；本文件只描述稳定工作契约，不重复易变配置。
不要把论文发现简化成单一关键词检索。根据用户选题和目标数量，组合以下五类渠道；每类都可以使用联网检索、研究者脉络或社区信号，但必须记录其来源和用途：
test cases passed, vs 7 / 19 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.