kkkirito-123/zlagent/paper-search
Claude Code and agent skill by kkkirito-123/zlagent
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Checking that the SKILL.md file is still in the repository.
Find a small list of academic papers on demand — "给我 N 篇目标检测领域 顶刊 / 顶会 / SOTA 论文 / 综述" — using the multi-source chain arxiv API → Semantic Scholar → web_search. Distinct from `daily-paper-digest` (scheduled daily delivery) and `arxiv` (single-day category dump): this one is the on-demand "find me N papers about X" surface that the user usually triggers in chat.
Install
npx vskill@latest install kkkirito-123/zlagent/paper-searchSKILL.md
paper-search
Trigger
Use this skill when the user asks for a small ad-hoc list of academic papers, typically:
- "给我目标检测领域的 5 篇顶刊论文,要最新的"
- "AI agent 方向最近半年的 SOTA 论文有哪些"
- "推荐 3 篇关于 RAG 评估的综述"
- "Find me 5 recent papers on diffusion video generation"
Do NOT use this skill for:
- Scheduled daily / weekly digests →
daily-paper-digest. - "Today's cs.AI listing on arxiv" (category dump, not topic-targeted)
→ arxiv.
- Reading / summarising a single paper the user already linked →
web-summary + read_url.
Inputs
Resolve from the user message before fetching:
topic— the research area in plain words ("目标检测 / object
detection", "RAG evaluation"). Required; ask one short follow-up if truly ambiguous.
count— how many papers, default 5, hard cap 8.recency— "最新 / latest" → last 12 months; "近年 / recent" → last
3 years; explicit window like "2024 以来" → respect verbatim.
kind— empirical / SOTA / survey / benchmark / methods. Default:
whichever the user phrased; if silent, prefer SOTA + 1 survey when both are obviously useful.
Steps
- Source priority (cheapest + highest signal first):
- arxiv API —
https://export.arxiv.org/api/query?search_query=ti:<topic>+OR+abs:<topic>&start=0&max_results=20&sortBy=submittedDate&sortOrder=descending
via read_url. Returns Atom XML; parse for title / authors / summary / arxiv id. Best for ML / CS / EE.
- Semantic Scholar Graph API —
https://api.semanticscholar.org/graph/v1/paper/search?query=<topic>&limit=20&fields=title,authors,year,venue,citationCount,abstract,url
via read_url. Better venue + citation metadata than arxiv. If it returns 429, wait and retry once with a 60s gap; then move on without it.
- web_search — only as a last fallback when arxiv + S2 both
yielded fewer than count candidates. Query template: "<topic>" survey 2024 site:arxiv.org then site:openreview.net.
- Filter + rank:
- Drop preprints whose abstract is empty / "Withdrawn".
- Prefer top-tier venues when the user asked for 顶刊 / 顶会 (CV:
CVPR / ICCV / ECCV / TPAMI; ML: NeurIPS / ICML / ICLR; NLP: ACL / EMNLP / NAACL; speech: INTERSPEECH; systems: SOSP / OSDI; security: S&P / USENIX). Surface arxiv-only entries only when no venued match exists.
- Sort: recency desc → citation desc → venue tier.
- Dedupe by arxiv id / DOI / canonical URL.
- Render (one bullet per paper, newest first):
- Title (in original language).
- Primary authors (max 3 then
et al.). - Year + venue if known.
- One-line plain-language takeaway (≤ 80 chars).
- Source URL (arxiv abs preferred over PDF).
- Tool budget: aim for ≤ 3 tool calls total. List-task
adaptive budget already grants up to 10 — reserve the headroom for retries, not for browsing every candidate.
Verification
- Every paper has a real source URL.
- Title / authors / year are never invented; if unknown, omit the
field and say so plainly.
- If the result set is thin (<
countsolid hits), say "找到 N 篇
够稳的,剩下的来源都不太可信,先给你这 N 条" — do not pad.
- Do NOT ask the user to "确认是否保存到知识库" unless they signalled
long-term storage intent. Default is in-chat output only.
Pitfalls
- Semantic Scholar 429 is common; honour the
Retry-Afterheader
and degrade silently to arxiv-only.
- DDG / Bing captcha will trigger the v0.45 provider chain in
web_search; if all 3 web providers fail, fall back to whatever arxiv + S2 produced even if < count.
- "顶刊" sometimes means journal (TPAMI / TMLR) and "顶会" means
conference (CVPR / NeurIPS); when the user uses both, include at least one of each.
- Don't translate paper titles — keep the originals so the user can
search them as-is.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingworkspace/skills/paper-search/SKILL.md
Popularity
- 7-day trend score
- 0
Not refreshed yet.
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