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Content & Media Creation · dontbesilent2025/dbskill

dbs-spread

Decodes resonance mechanisms, audience emotions, effective stances, and communication motives using theories from communication studies and social psychology that match the given content. Use when users ask why a piece of content resonates, what emotions it taps into, or what else the audience wants to hear.

L1 Basic · Source registration onlyV1 Commit-PinnedDual-pass Audit
Author dontbesilent2025GitHub dontbesilent2025/dbskill ↗Stars 10121License CC BY-NC 4.0（非商业授权）：仓库根 LICENSE 为 Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)，Copyright (c) 2026 dontbesilent；GitHub API license.spdx_id = NOASSERTION （CC BY-NC 4.0 非 SPDX 标准文本，GitHub 无法自动识别），不得用于商业用途Commit 8b8e33f1ec
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

Use "mechanism identification" first to determine the theory: For each segment of content, first identify whether it primarily shifts the audience's sense of identity, problem framing, emotional appraisal, content utility, or willingness to share, and then select the theory that explains that shift.

skills/dbs-spread/SKILL.md
每段内容先回答：它主要改变了受众的身份感、问题解释、情绪评价、内容用途，还是传播意愿？理论必须解释这个主要变化。
What is happening here: Transforming "theory-hunting" into "identify mechanism first, match theory second," preventing at the source the common mistake of forcibly shoehorning celebrity theories onto content.

The primary theory pool consists of 5 communication/social psychology theories with structured cards; each card specifies core sources, explanatory tasks, triggering evidence, diagnostic questions, and boundaries.

skills/dbs-spread/SKILL.md
- **核心来源**：Berger 与 Milkman，〈What Makes Online Content Viral?〉，2012，DOI：10.1509/jmr.10.0353。
Five mechanism categories: Social Identity and Self-Categorization (Tajfel/Turner), Cognitive Appraisal Theory of Emotion (Lazarus; Smith & Ellsworth), Framing Theory (Entman), Uses and Gratifications (Katz et al.), and Emotional Arousal and Online Sharing (Berger & Milkman).

Retain only one primary theory at a time; secondary theories are allowed only when the primary theory cannot cover a new mechanism, and three strict criteria must be met.

skills/dbs-spread/SKILL.md
只有满足以下全部条件时才能增加辅助理论：
Three criteria: Explains a new mechanism uncovered by the primary theory, explicit triggering evidence exists in the source text, and removing it loses a crucial and actionable conclusion.

A separate "conditional theory pool" is set, which can only be invoked if specific triggering conditions are met, clearly detailing what problems it is forbidden from substituting (to prevent misuse).

skills/dbs-spread/SKILL.md
内容涉及意见气候、孤立恐惧和公开表达意愿 | 泛化成“说出受众所有不敢说的情绪” |
Only three conditional theories: Spiral of Silence, Cognitive Dissonance, and Two-Step Flow. The table's third column lists eligible triggering conditions, and the fourth column lists "forbidden substitution problems."

Conclusions must self-report explanatory boundaries and confidence levels to avoid presenting inferences as facts.

skills/dbs-spread/SKILL.md
- 判断的置信度：高／中／低。
Each mechanism judgment card consistently includes: theory name, source-text triggering evidence, psychological mechanism explained, "what it cannot explain," and confidence level.

Three-tier evidence discipline: Textual facts / Mechanistic inferences / Facts pending verification; these three must never be conflated.

skills/dbs-spread/SKILL.md
- 文本事实：原文明确写了什么；
Accompanying requirement: Whether audiences actually experienced the reaction requires confirmation via comments, interviews, or behavioral data.

Decouple emotion, stance adoption, and sharing into three separate outcomes to evaluate individually, and explicitly forbid using theories to forecast platform metrics.

skills/dbs-spread/SKILL.md
内容让人愤怒，不等于受众会接受观点；受众接受观点，也不等于会分享。分析时分别判断。
The boundary section explicitly lists out-of-bounds tasks such as "predicting completion rates, CTRs, and algorithmic impressions," preventing psychological mechanism analysis from being packaged as traffic forecasting.

Outputs follow a fixed template + self-check checklist, concluding uniformly with "chat room directions" (bridging with dbs-chatroom).

skills/dbs-spread/SKILL.md
置信度：[高 / 中 / 低] 【辅助机制】 [没有必要时写“无”。有时按主导机制的格式输出。] 【综合推导】 受众情绪假设：[具体情绪及其形成路径；无法确认时如实说明] 有效立场：[问题定义、归因和受众位置] 预期使用行为：[观看、收藏、评论、分享或行动的具体动机] 受众还想听什么：[2—3 个保持同一机制的话题] 【聊天室方向】 核心讨论焦点：[一个具体问题] 需要维持的机制：[身份、框架、情绪评价、用途或传播动机] 需要避开的推断：[当前证据无法支持的结论] ``` --- ## 自检 1. 是否先从文本识别机制，再选择理论？ 2. 是否只保留一个主理论？ 3. 辅助理论是否提供了新的解释？ 4. 是否把文本事实、机制推断和待验证事实分开？
The template includes five sections: Target of Analysis / Dominant Mechanism / Secondary Mechanism / Comprehensive Deduction / Chat Room Direction; the 7-question self-check covers mechanism priority, single primary theory, three-tier evidence, three-outcome separation, traffic prediction prohibition, and conditional theory gating.

2Core Capabilities

01Identification of content's dominant resonance mechanism (select 1 from 5: identity / framing / emotion / utility / sharing intent)
02Primary theory pool matching (5 theories, each with source, triggering evidence, and boundaries)
03Conditional theory gating (Spiral of Silence / Cognitive Dissonance / Two-Step Flow; must meet trigger conditions)
04Mechanism judgment cards: including triggering evidence, explanatory mechanism, explanatory boundaries, and confidence level
05Four-part comprehensive deduction: audience emotion hypotheses / effective stance / expected usage behavior / what else the audience wants to hear
06Chat room discussion direction output (core focus + mechanisms to maintain + inferences to avoid)
077-question self-check, including "avoiding the use of theories to predict platform traffic"

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; no script execution or external impact.
Audit Notes: Pure instruction-based skill: no script execution, no external network requests (no endpoints or retrieval commands in directory), no credential access, and no local file writing; assets consist solely of SKILL.md + agents/openai.yaml. The only considerations are the inferential nature of analytical conclusions (which might be consumed as fact) and risks of theoretical misapplication, neither of which constitutes a code-level risk.

5Second-Pass Verification

  • [ok] 目录仅 2 个文件、无脚本 — find 仅返回 SKILL.md 与 agents/openai.yaml。
  • [ok] 无网络外发 / 无凭证读取 / 无文件写入 — 全目录 token 扫描（http、curl、env、API_KEY、write、open( 等）零命中。
  • [ok] 5 个主理论及其来源、DOI 逐字存在 — A–E 五节与所列年份/DOI 均在源码中；DOI 仅作文本引用，不触发检索。
  • [ok] 条件理论池确有触发条件与"禁止代替的问题"两列 — 表格含"允许调用的条件""禁止代替的问题"两列，三个条件理论逐行核对无误。
  • [ok] "每次只保留一个主理论"与辅助三条件 — 核心原则第 2 条与"只有满足以下全部条件时才能增加辅助理论"整段存在。
  • [ok] 禁用场景（不预测平台指标）确实写在边界里 — "以下任务超出边界："下含"预测完播率、点击率、推荐量等平台指标"等 3 条。
  • [ok] 与 dbs-chatroom 的衔接说法是否有源码支撑 — SKILL.md 输出模板含【聊天室方向】段并在自述中写明"给出聊天室的讨论方向"，属 skill 自身声明的产出，非侦查推断。
  • [ok] 是否存在未声明的联网/检索能力 — 无任何 web/browser/search/fetch 指令；理论来源以静态文本内嵌。

6Verdict & Scenarios

  • Mechanism-first theory selection algorithm that systematically prevents forced theoretical shoehorning and celebrity bias.
  • Complete theoretical pool structure: incorporates all four elements—sources, triggering evidence, diagnostic questions, and boundaries—complete with DOIs for manual verification.
  • Counter-overinterpretation: separates textual facts, mechanistic inferences, and unverified facts, enforcing explicit confidence levels and explanatory boundaries.
  • Clear outcome stratification: emotion ≠ acceptance ≠ sharing, preventing simplistic equations like "anger" directly equating to "will share."
  • Zero side effects, directly actionable for content decisions: script-free and network-free, outputting structured Markdown ready for chat room or content topic ideation pipelines.
    • Best for: Suitable for content creators and operators answering "why does this resonate, what emotion does it strike, and what can we say next" prior to release or during post-mortems; also suitable for scenarios requiring discussion topic direction design for chat rooms or communities (outputs direct chat room directions).
    Not for: Not suitable for forecasting platform metrics such as views, impressions, or completion rates (explicitly demarcated as out of bounds by the skill); not suitable for quantitative effect evaluations that require empirical audience data; not suitable for users seeking a tactical checklist on "how to make viral hits" (it explains mechanisms, not ad-buying or growth-hacking strategies).
    Install Agent-Ready
    ① Verified Mirror 2026-09-15
    Option A · Direct DownloadDownload dbs-spread.tar.gz
    sha256: 961fd23b7eb2e607…
    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 8b8e33f1ec.