Evidence Chain Builder（AI 论断有证证据链）

Decompose AI claims into verifiable evidence chains (LGD-II): each item tagged by source type (official, paper, data, internal, assertion) with independent verifiability status. 当用户要『验证 AI 论断 / 防幻觉 / 给结论找证据 / 判断信源可信度』时用。把论断拆成可验证证据链：每条证据标来源类型(official/paper/data/internal/assertion)、是否可独立验证、可信度，输出『证成度』与未支撑论断清单。对齐 EIFP 不编造原教旨——本工具不判定论断真假，只评估证据质量；缺可验证证据的论断明确标『勿作结论』。这是 LGD-II 有证的落地执行器。触发词：证据链、论断验证、防幻觉、信源可信、有证、claim 证据、论断举证。

zhaoxinghua09-cell@zhaoxinghua09-cell

Install

openclaw skills install @zhaoxinghua09-cell/evidence-chain-builder

凡自治之物 · LGD 治理学 · 创造术家族｜评测协议：见平台质量门禁规范

English

When to use

When the user presents an unverified AI claim, opinion summary or news item and needs to prevent hallucination while finding supporting evidence.
When verifying conclusions or assessing source credibility, needing to be explicit about the evidence quality of each source kind (official / paper / data, etc.).
When running the LGD-II "evidenced" executor, making sure every conclusion is traceable and EIFP-compliant.
When trigger words such as "evidence chain", "anti-hallucination" or "claim evidence" demand a structured decomposition of the verification process.

Usage

Call the Python script evidence_chain.py from the CLI or API, passing the claim text to be analyzed as the core input.
Optionally configure the source types (e.g. official / paper) and verification depth; by default the system runs the EIFP no-fabrication logic.
To get a detailed evidence-chain report, enable --verbose to surface the unsupported-claim list in full.
After reading the input, the script returns structured JSON: each evidence item's id, source and credibility score.

Workflow

Step 1: receive the target claim and extract the core assertion, scoping what must be verified.
Step 2: decompose complex claims into atomic evidence fragments, identifying each fragment's type and independence.
Step 3: match candidate evidence sources; assess how credible and independently verifiable the information is.
Step 4: per the EIFP no-fabrication principle, flag missing evidence or information gaps.
Step 5: aggregate all evidence quality into an overall justification score and generate a structured verification report.
Step 6: emit the result; claims that cannot be supported are explicitly marked "do not conclude" together with the gap list.

Evidence & safety statement

Evidence: TBD (no evaluation / badge link yet; update here once it is produced)
Version: 1.0.1
Security: no independent security scan has been performed (TBD); the conclusion is pending and no endorsement is given until it is completed.

中文

何时用

当用户提出未经证实的 AI 论断、观点摘要或新闻信息，需防止幻觉并寻找支撑证据时。
进行结论验证或信源可信度评估，需明确各类来源（官方/论文/数据等）的证据质量时。
执行 LGD-II 有证落地执行器任务，确保所有结论均有据可查且符合 EIFP 原则时。
当触发「证据链」「防幻觉」或「论断举证」等关键词，要求结构化拆解验证过程时。

用法

通过命令行或 API 调用 Python 脚本 evidence_chain.py，指定待分析论断文本作为核心输入参数。
可选配置源信源类型（如 official/paper）及验证深度，系统默认按 EIFP 标准执行不编造逻辑。
若需输出详细证据链报告，需在脚本调用中开启 --verbose 模式以获取未支撑清单细节。
脚本读取输入后，将返回结构化 JSON 数据，包含每条证据的标号、来源及可信度评分。

流程

步骤 1：接收用户输入的目标论断，提取核心主张并明确待验证的范围。
步骤 2：将复杂论断拆解为原子级证据片段，识别每个片段的类型与独立性。
步骤 3：匹配潜在证据库或来源，评估信息的真实可信度与是否可独立验证。
步骤 4：依据 EIFP 不编造原教旨原则，标记是否存在缺位证据或缺口信息。
步骤 5：综合所有证据质量计算整体证成度数值，生成结构化验证报告。
步骤 6：输出结果，对无法得到支持的论断明确标注『勿作结论』及缺失清单。

证据与安全声明

证据：TBD（暂无评测/徽章链接；产生后在此更新实际链接）
版本：1.0.1
安全：未做独立安全扫描（TBD），结论待补；补全前不作推荐背书。

Ecosystem / 生态入口

This skill is one door of the LGD ecosystem — every entry below is publicly reachable. 本技能是 LGD 生态 的一个入口，下列地址均对公网可达。

Ecosystem hub / 生态总入口: https://zhaoxinghua09-cell.github.io/lgd-hub/
LGD theory (canonical) / 理论正本: https://github.com/zhaoxinghua09-cell/LGD
Formal paper (DOI) / 形式化论文: https://doi.org/10.5281/zenodo.22456647
Protocol & reference implementation / 协议与参考实现: https://github.com/zhaoxinghua09-cell/uibc-core
Source of this skill / 本包源码: https://github.com/zhaoxinghua09-cell/agent-skills/tree/main/skills/evidence-chain-builder
All published skills / 全部已发布技能: https://github.com/zhaoxinghua09-cell/agent-skills
AI-readable index / AI 说明书: https://github.com/zhaoxinghua09-cell/agent-skills/tree/main/skills/evidence-chain-builder/llms.txt

Looking for something else? / 还想要别的？

Tell your AI assistant: "Find me an LGD skill that can " — the hub lists every published skill with a one-line purpose. 跟你的 AI 助手说一句「去 LGD 生态超市找能……的技能」，总入口按用途列全了所有已发布技能。