360 Secure SkillHub
360 安全技能中心

Kb Literature Review

核心功能：从指定个人/团队知识库筛选相关文档，生成含综述、方法对比、研究缺口等的结构化结果，支持将综述保存至知识库。典型场景：撰写专题综述、对比研究方法、梳理领域研究缺口等。输入为指定格式的任务JSON，输出含答案、引用等的标准结果JSON，若知识库相关内容不足将明确提示，不编造内容。

myd2002
myd2002
热度 16.02
最近更新 2026-06-26 03:30:27
分类：知识依赖：读写文件 / MCP 服务 / 内部调用大模型应用场景：摘要总结 / 研究 / 报告撰写

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add kb-literature-review
Metadata
name
kb_literature_review
description
Produce a focused literature/knowledge review using only selected Research KB contents. Use for query-page tasks asking to write a review, synthesize a topic, compare multiple papers/projects, summarize methods, identify research gaps, or produce a source-grounded thematic survey; accepts Java backend research_kb_agent_task JSON with taskType kb_query or kb_literature_review and returns query-compatible answer/citations.

Skill: kb_literature_review

Scope

Use this skill when the user wants a cross-document synthesis from the selected personal/team knowledge bases, not a single fact lookup.

Typical triggers:

  • 写一篇/一份关于 X 的综述
  • 梳理知识库里关于 X 的资料
  • 对比几种方法/路线
  • 总结主流方法、优缺点、研究缺口
  • 基于知识库内容做专项报告

Do not use it for:

  • simple lookup like "有没有 X"
  • one document's conclusion
  • open-source repository usefulness evaluation
  • ingestion or source scanning

Input

Accept the Java backend query-page envelope:

  • protocol = research_kb_agent_task
  • taskType = kb_query or kb_literature_review
  • kbTargets[] contains one or two repositories
  • payload.question is the user's natural-language request
  • Optional: payload.topic, payload.options.writeReview

Only read repositories listed in kbTargets.

Workflow

  1. Validate the task JSON.
  2. Determine the review topic from payload.topic or payload.question.
  3. Read repository Markdown trees and collect candidate pages, excluding source_files/.
  4. Score candidates by topic terms, title, path, headings, and content.
  5. Read a focused set of relevant pages. Prefer concept/review/summary pages before low-level archive pages.
  6. If fewer than two relevant pages exist, say the knowledge base is insufficient and do not fabricate a review.
  7. Generate a Chinese review with:
    • scope
    • topic overview
    • method/category map
    • comparison of strengths and limitations
    • contradictions or disagreements
    • research gaps
    • implications for the selected KB context
    • source list
  8. If payload.options.writeReview is not false, write the review to reviews/<topic>-专项综述.md in the first selected target repository and cite it.
  9. Return one query-compatible JSON result.

Evidence Rules

  • Every knowledge-base fact must come from pages actually read.
  • Do not fill missing areas with general knowledge unless explicitly marked as non-KB background.
  • Citations must be repository-relative .md paths and must not point to source_files/.
  • The answer body should be readable as a concise executive summary; detailed source list belongs in citations[].

Output

Return only one JSON object. Do not use Markdown fences.

{
  "protocol": "research_kb_agent_result",
  "protocolVersion": "1.0",
  "taskId": "...",
  "taskType": "...",
  "success": true,
  "result": {
    "answer": "...",
    "citations": [],
    "usedScopes": ["personal", "team"],
    "readPages": [],
    "mode": "literature_review",
    "generatedPage": ""
  },
  "errors": []
}

Helper

Prefer the bundled deterministic helper:

python3 scripts/run_task.py --stdin
python3 scripts/run_task.py --task-json <path>