surface-assumptions

使用方法

复制安装命令，在自己的智能体环境安装前先检查源码包。
从原始文档核对所需工具、凭据和支持的宿主。
说明输入材料与期望交付物，并对照来源检查输出。

npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill surface-assumptions

开始前需了解

安装不包含模型订阅、API 额度或访问文件的权限。
仓库星数和安装量反映活跃情况，不等于独立质量或安全测试。

仓库原始内容

按源仓库内容呈现，保留标题、案例、代码、表格、链接以及原文引用的演示图片。

Purpose

Enumerate explicit and implicit assumptions in a claim, model, method, decision, or design and expose their evidential status.

Input contract

yaml

required: [artifact, claim_or_decision, context]
optional: [causal_claims, evidence, stakeholder_views, assumption_taxonomy]
constraints: [separate explicit from implicit assumptions; preserve the artifact's wording; attach evidence strength and criticality to each assumption]

Procedure

Parse the artifact into claims, dependencies, conditions, and unstated background requirements.
Enumerate assumptions and classify each as explicit or implicit and by type.
Attach supporting or contradicting evidence and rate assumption strength and criticality.
Mark assumptions whose failure would change the conclusion and return the assumption register.

Output contract

yaml

produces: [assumption_register, evidence_assessments, critical_assumptions, dependency_notes]
delta_fields: [findings, evidence_updates, uncertainties, recommended_jumps]

Quality gates

Every assumption has a type, explicit/implicit status, evidence assessment, and criticality rating.
The register distinguishes load-bearing assumptions from decorative assumptions and preserves interaction effects when supplied.
Do not replace enumeration with a generic risk paragraph.

Parameterization

The caller must provide the artifact or claim, the context and intended conclusion, any known causal claims, the assumption taxonomy, evidence sources, and the rating scale for strength and criticality.

Failure and counterexamples

Reject when the artifact or conclusion is missing, assumptions are asserted without relation to the claim, or contradictory evidence is silently omitted.