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hum-discourse嗡嗡声话语

Agent Skill

hum-discourse 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

376

周安装

16

GitHub Stars

125

下载量

132
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hum-discourse(嗡嗡声话语)
来源仓库:https://github.com/asgard-ai-platform/skills
仓库路径:skills/hum-discourse
安装命令:
npx skills add https://github.com/asgard-ai-platform/skills --skill hum-discourse
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/asgard-ai-platform/skills --skill hum-discourse

简介

hum-discourse 用于查找、检索和筛选相关信息,支持基于关键词快速定位结果。

  • 适用于信息搜集、任务场景匹配和研究线索梳理场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围。
  • 使用前建议核实是否会触发联网或文件读写操作。
  • 可结合原始 README 继续核验具体功能和使用限制。

SKILL.md

Discourse Analysis

Overview

Discourse analysis examines how language shapes (not just reflects) reality. It reveals how texts construct identities, power relationships, and social norms through word choice, framing, and what is left unsaid. Especially valuable for analyzing media, corporate communications, policy documents, and political speech.

Framework

IRON LAW: Language Constructs Reality, Not Just Describes It

The choice of words is never neutral. "Restructuring" vs "layoffs",
"enhanced interrogation" vs "torture", "undocumented workers" vs
"illegal aliens" — same events, different realities constructed.

Discourse analysis examines WHAT language does, not just what it says.

Key Analytical Dimensions

  1. Framing: How is the issue defined? What metaphors are used? What's included/excluded?
  2. Subject positions: Who is positioned as agent (active doer) vs patient (passive receiver)?
  3. Presupposition: What is taken for granted without being stated?
  4. Intertextuality: What other texts/discourses does this reference or draw upon?
  5. Power relations: Whose voice is amplified? Whose is silenced?

Analysis Steps

  1. Select the text: What specific communication are you analyzing?
  2. Context: Who produced it? For whom? In what setting? What's the purpose?
  3. Lexical analysis: What word choices are notable? What alternatives were available?
  4. Structural analysis: How is the text organized? What comes first? What's emphasized?
  5. What's absent: What is NOT said? Who is NOT represented?
  6. Power mapping: Who benefits from this particular framing?

Output Format

# Discourse Analysis: {Text/Document}

## Context
- Producer: {who created this text}
- Audience: {intended recipients}
- Purpose: {stated and unstated goals}
- Genre: {press release / policy doc / speech / ad}

## Framing Analysis
| Element | In the Text | Alternative Framing | Effect |
|---------|------------|-------------------|--------|
| {key term} | "{actual language}" | "{what could have been said}" | {how this shapes perception} |

## Subject Positions
- Agent (active): {who does things}
- Patient (passive): {who has things done to them}
- Absent: {who is not mentioned}

## Presuppositions
- {what the text assumes without stating}

## Power Analysis
- This framing benefits: {who}
- This framing disadvantages: {who}

## Key Findings
{What the discourse analysis reveals that a surface reading misses}

Examples

Correct Application

Scenario: Analyzing a tech company's layoff announcement

Text: "We are making the difficult decision to right-size our organization to better position ourselves for long-term growth."

ElementTextAlternativeEffect
"right-size"Implies current size is wrong"lay off 500 employees"Euphemism hides human impact
"our organization"Company as abstract entity"our colleagues"Removes personal connection to affected people
"difficult decision"Positions management as suffering"decision that will displace 500 families"Redirects sympathy toward decision-makers
"long-term growth"Forward-looking justificationNo mention of what caused over-hiringSkips accountability for the situation

Subject positions: Management = agents making "difficult decisions" (sympathetic). Employees = completely absent as subjects. ✓

Incorrect Application

  • "This press release is biased" → Too vague. Which words? What framing? Bias toward what? Discourse analysis requires specific textual evidence. Violates Iron Law: analyze what language DOES.

Gotchas

  • All language is "constructed": Discourse analysis doesn't mean the text is "lying." Even honest communication makes framing choices. The question is what those choices reveal and conceal.
  • Analyst's own discourse: Your analysis is also a discourse with its own framing and assumptions. Be reflexive about your own position.
  • Context is everything: The same words mean different things in different contexts. "We need to move fast" in a startup vs in a hospital has very different implications.
  • Don't over-read: Not every word choice is strategic. Sometimes "right-size" is just corporate jargon the writer learned, not a deliberate framing strategy. Consider intentionality.
  • Discourse analysis is not fact-checking: It examines how meaning is constructed, not whether claims are true. Pair with evidence-based analysis for a complete picture.

References

  • For Fairclough's Critical Discourse Analysis framework, see references/cda-framework.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

32.24%
按下载量换算43

Claude

29.16%
按下载量换算38

Cursor

20.2%
按下载量换算27

Gemini CLI

9.95%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

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来源信息

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