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ljg-analogy

Finds apt analogies and relational metaphors for a given scenario or differences between two objects based on Structure-Mapping Theory, preserving core relationships, explanatory increments, and mapping boundaries. USE WHEN the user asks to "find an analogy", "make a comparison", "come up with a clever metaphor", "clarify the difference between the two using an analogy", "understand it from a different perspective", or calls ljg-analogy. NOT FOR merely explaining existing metaphors, pure rhetorical polishing, theoretical definitions, or treating analogies as factual proof.

L1 Basic · Source registration onlyV1 Commit-PinnedDual-pass Audit
Author lijigangGitHub lijigang/ljg-skills ↗License MIT(仓库根 LICENSE)Commit 9e75497a95
Control levels describe skill capabilities and suggested control measures; they do not represent quality or safety certifications, nor do they dictate usability. Usage decisions rest entirely with users and administrators. Different agent hosts apply varying constraints; do not assume hosts provide automatic protection. Third-party skill copyrights belong to their original authors. Use at your own risk.

1How It Works & Mechanism

Grounded in Gentner's (1983) Structure-Mapping Theory: mapping prioritizes preserving relations between objects over superficial attributes, favoring systems of relations organized by higher-order relations.

skills/ljg-analogy/Theory.md
对象属性与对象间关系区别处理;映射优先保留关系,并选择关系系统
What this is doing: Anchors the validity of the analogy at the relational level—surface differences do not invalidate an analogy; whether the relations form a coherent system determines success.

Fix terminology direction: the scenario the user wants to understand is the target domain, and the scenario borrowed to aid understanding is the base domain; search direction is opposite to knowledge transfer direction.

skills/ljg-analogy/SKILL.md
术语方向固定:**用户想理解的场景是目标域;借来帮助理解的场景是基域。**
What this is doing: Establishes the target of explanation versus the borrowed vehicle upfront to prevent reversing B and T; aligns with the user's actual intent when their phrasing is inverted.

Route by request type: four distinct handling paths—finding an analogy for a single scenario, comparing two objects, adapting to audience/style, and comparing multiple candidates.

skills/ljg-analogy/SKILL.md
| 给一个场景,寻找类比或隐喻 | 按下文的成品标准交付一个主类比 |
What this is doing: Uses a Workflow Routing table to dispatch four common request types into different delivery forms, minimizing off-target responses.

Evaluate input sufficiency first: when only a single word is provided without context, ask a question that can actively shift the analogy selection.

skills/ljg-analogy/SKILL.md
只有一个词而无可辨认情境时,问一个能改变类比选择的问题
What this is doing: Avoids fabricating details when information is lacking; follow-up questions target key framing variables rather than generic confirmations.

Filter out generic commonalities: overly broad claims such as "both are very complex" or "both are networks" cannot independently support an analogy.

skills/ljg-analogy/SKILL.md
「都很复杂」「都是网络」「都需要平衡」适用面太宽,不能单独支撑类比。
What this is doing: Uses Gotchas with counterexamples to weed out pseudo-analogies that merely pile up superficial similarities without retaining load-bearing relations.

The primary criterion for a finished analogy is task alignment: the mapping must preserve the specific relationship the reader needs to understand this time.

skills/ljg-analogy/SKILL.md
**任务吻合。** 映射保留的是读者这次需要理解的关系。
What this is doing: Uses the reader's comprehension task as the selection yardstick; analogies that explain some feature but remain irrelevant to the immediate question are deemed unacceptable.

Perform a discriminative power check when comparing two objects: if swapping the base vehicles still holds without altering the load-bearing relations, it indicates only shared attributes were captured.

skills/ljg-analogy/SKILL.md
交换喻体以后,如果不用改变承重关系仍能轻易圆回来,它们可能只命中了共同属性。
What this is doing: Uses the operational test of swapping vehicles to distinguish "explaining differences" from "merely labeling separately."

Deliver directly in conversation by default, explaining a single primary analogy thoroughly in a three-stage structure without automatically creating notes, images, or files.

skills/ljg-analogy/SKILL.md
默认直接在对话交付,不自动创建笔记、图片或文件。
What this is doing: Constrains delivery format—presents the analogy itself first, runs the mapping correspondence, and lands on the incremental insight, without imposing rigid heading templates.

Maintain honest theoretical boundaries: only Gentner's mapping and systematicity principles are borrowed; understanding tasks, candidate elimination, and boundaries are novel authoring criteria.

skills/ljg-analogy/SKILL.md
本技能借用 Gentner(1983)的关系映射与系统性原则。理解任务、双对象对照、候选淘汰、受众熟悉度、认知增量与具体边界,是为创作任务增加的设计标准,不宣称出自论文或已被论文验证。
What this is doing: Separates academic conclusions from engineering design, avoiding the use of scholarly prestige to endorse custom creative rules.

EvalCases.json serves only as a behavioral acceptance reference, defining inputs and acceptance criteria rather than prescribing a single correct analogy.

skills/ljg-analogy/SKILL.md
这些用例只定义输入和验收依据,不规定唯一的正确比方。
What this is doing: Provides a test case suite for human review of actual response quality, preventing a single base domain from being treated as the absolute answer.

2Core Capabilities

01Single-scenario analogy generation
02Two-object difference comparison
03Adaptation to audience, domain, style, and length
04Multi-candidate comparison and recommendation
05Structural validation of relational mapping (role stability, directional and temporal consistency)
06Mapping boundary explanation
07Target domain factual protection (no fabricating motivations, causalities, or outcomes for the target)
08Reviewable behavioral evaluation test suite

4Recommended Governance & Evidence

Suggested Controls for Safe Operation
For Agent Runtime
Can be auto-loaded
For Administrators
Register source and version
Evidence & Triggers (File Paths & Excerpts)
  • SKILL.md: Pure prompt instructions and rule text, without script execution or external side effects
Audit Notes: Pure instruction-based skill: contains no scripts, network requests, credential access, or disk writes within the directory; no hits across the four risk scan categories (external program execution, network requests, credentials/environment variables, disk writes). The Gentner paper link referenced in Theory.md is purely for source attribution and does not participate in execution.

5Second-Pass Verification

  • [ok] 功能声明与实现一致 — frontmatter 声明『基于结构映射理论…寻找精妙类比与关系隐喻』,正文给出目标域/基域定义、成品标准与 Theory.md 理论依据,未发现夸大。
  • [ok] 外部依赖核验:无运行时依赖 — 目录四个文件均为文本(md/json/yaml);风险扫描四类(执行外部程序、网络请求、凭证、写盘)全部无命中。
  • [ok] 安全结论反例检查 — 逐行重核无 curl/wget/fetch、child_process 或 fs 写入/读取凭据;无脚本文件,故 scripts_executed 为空。
  • [ok] 引用可定位性 — 所有 quote 均可在 SKILL.md/Theory.md/EvalCases.json 原文逐字匹配,长度均大于 12 字符。
  • [ok] 判级口径复核 — 按判级六档,纯指令无脚本无外发,落 green;Theory.md 的外链属来源标注,不改档位。
  • [ok] 理论归属表述核对 — SKILL.md 明写新增标准『不宣称出自论文或已被论文验证』,分析据此未把创作规则写成论文结论。
  • [ok] 用例集性质核对 — EvalCases.json purpose 声明不按固定措辞或唯一基域打分,分析未把单一基域当作正确解。

6Verdict & Scenarios

  • Frames analogy acceptance into identifiable relational structures (role stability, direction/timing/dependency) rather than subjective taste
  • Maintains honest theoretical boundaries: distinguishes Gentner's (1983) mapping constraints from the skill's added creative standards, without using academic papers to endorse engineering design rules
  • Built-in behavioral test cases cover edge cases like non-causal spatial analogies, single-sentence metaphors, context-lacking follow-ups, and "analogy is not proof"
  • Strictly preserves target domain facts: prohibits inventing motivations, causality, or outcomes to make an analogy fit
  • Best for: Ideal for knowledge workers, writers, and educators who need to explain abstract relationships clearly: most robust when finding load-bearing analogies for scenarios, explaining differences between two objects or mechanisms, customizing metaphors for specific audiences, or generating explanatory analogies with mapping boundaries; also suitable for analogy reasoning and prompt engineering researchers looking to adopt its method of converting creative criteria into verifiable acceptance conditions.
    Not for: Not suitable for requests seeking only rhetorical polishing, explaining existing metaphors, or treating analogies as factual proof (explicitly listed in official NOT FOR); not suitable for workflows requiring automatic file saving, as delivery is strictly in-chat by default; not suitable for scenarios requiring deterministic scoring or regression testing, as acceptance relies on semantic judgment rather than executable verification.
    Install Agent-Ready
    ① Verified Mirror 2026-10-10
    Option A · Direct DownloadDownload ljg-analogy.tar.gz
    sha256: f6af0a46838494b1…
    Option B · Copy Guide for Agent
    install.json
    Agents automatically download and verify mirrors from this JSON guide.
    ② Upstream GitHub
    GitHub Repo ↗
    Pinned to commit 9e75497a95.