Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add chuwu57/Chuwu-PR-OS --skill media-narrative-analysisgit clone --depth 1 https://github.com/chuwu57/Chuwu-PR-OSWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/chuwu57/chuwu-pr-os/media-narrative-analysis)<a href="https://agentmods.dev/skills/chuwu57/chuwu-pr-os/media-narrative-analysis"><img src="https://agentmods.dev/badge/skills/chuwu57/chuwu-pr-os/media-narrative-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/chuwu57/chuwu-pr-os/media-narrative-analysis"><img src="https://agentmods.dev/badge/skills/chuwu57/chuwu-pr-os/media-narrative-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.02827 |
| Opus 5.5 | $0.00048 | $0.01131 |
| Sonnet 5.5 | $0.00024 | $0.00565 |
| Haiku 4.5 | $0.00012 | $0.00283 |
Grade A, and why
media-narrative-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
稿件分析
归属说明:本Skill由初五维护,属于初五的个人Skill体系。分享或再分发时请保留本归属说明及已有来源、作者和许可声明。
定位
从原文的选材、措辞、结构和信源判断它可能建立什么认知,再评估对我们的影响。文本可以支持叙事判断,但通常不足以确认作者或机构的真实动机。
本 Skill 处理三类问题:
- 这篇稿有哪些可观察的叙事选择,可能产生什么认知效果;传播意图有多少证据支持。
- 它对我们有没有影响,影响哪类公关资产。
- 我们需要不应对、观察,还是进入判断中枢拍板。
不要把它做成「软文识别器」。软文只是其中一种可能,真正要判断的是:这篇稿是否改变了行业认知、竞品位置、媒体关系、话语体系或我们的解释成本。
知识调用
默认按本文件完成稿件分析。遇到竞品叙事、行业标准争夺、政策协作稿、媒体关系、新闻价值或是否投入资源的问题时,读取 references/knowledge-map.md。涉及媒体动机、机构号、商业信号、新闻稿依赖、企业信源主导或同一事件多个媒体版本时,同时读取Domains/PR/35-Frameworks/Framework_Media-Signal-Calibration.md。
知识只用于校准来源、发布时间、表达选择和业务影响。不要把传播学概念替代具体原文依据,也不要用理论或历史印象补出未证实的幕后推动者。
先做事实核验
先区分任务模式:
- 用户已提供全文并要求评价时,默认基于原文完成叙事判断;把关键外部主张标记为待核验,不自动扩大为网页调查。
- 用户明确要求事实核验、最新情况、传播矩阵判断,或关键事实真假会改变行动建议时,只检索会改变结论的部分。
- 需要检索时,先形成基于原文的初步判断,再补最小必要核验,不能让检索替代文章分析。
分析前先确认:
- 标题、作者、平台、发布时间、原始链接。
- 区分原创、转载等来源关系,以及通稿、访谈、评论、研究文章、政策通报等体裁。商业合作或投放另看明确标识和公开证据,不能从体裁直接认定。
- 是否有同题材稿件同步出现。必要时搜索标题关键词、核心事件和关键句,判断它是不是矩阵传播的一部分。
- 关键事实是否来自单一信源,信源能证明什么、哪些主张缺少独立核验。内部数据或独家场景可能来自采访准入、材料可得性或报道范围,单方受益不能单独证明策划或付费关系。
不能确认的内容要写清楚「未确认」,不要把猜测当结论。
校准来源与编辑加工
把媒体身份当作研究先验,不当作文章真假或立场的最终判断。只要任务涉及「媒体为什么这样写」「是不是软文」或传播矩阵,必须补做四项校准:
- 判断来源角色及其接近事实的路径;
- 标出核心事实来自企业、监管、客户、员工、专家、媒体现场、独立测试还是作者体验;
- 判断编辑加工层级:L1承载/转载、L2技术注释、L3编辑采访、L4多方调查;
- 分开写商业结构、企业影响和付费证据。没有明确公开证据时,不判断具体文章属于付费合作。
加工层级不是可信度总分。L4仍受样本和匿名信源限制;L1可以准确承载一手声明,但只能证明声明本身。
判断顺序
1. 先给结论
第一段直接回答:
- 原文最明显的叙事选择及其可能建立的认知;证据不足时保留意图未知。
- 对我们是无关、观察,还是需要动作。
- 影响的是短期声量,还是长期信任、话语体系、媒体关系、业务解释成本。
2. 分开观察、效果与意图
分析时保留三层,不要求正文逐条填写固定表格:
- 原文可观察选择:写了哪些事实、引用谁、如何排序和对比、明确省略了哪些与结论有关的条件。每项判断连接原文片段或可定位的表现;不能把自己未见到的信息一律认定为作者刻意回避。
- 可能认知效果:这些选择可能让哪类读者形成什么理解,说明从文本到理解的路径。未取得受众反馈时,只能判断潜在效果,不能把预期效果写成已经发生的舆论变化。
- 传播意图假设:只有意图判断会改变分析或建议时才展开,说明支持线索、合理替代解释和会削弱判断的证据。单方受益、语气正面、同日发稿或企业信源占比高,都不足以独立证明协调传播、作者动机或付费合作。
按原文相关性考察以下问题:
谁获得叙事优势
看谁被突出、谁受到批评、采用了谁的评价标准。区分「某方受益」与「某方推动发布」;后者需要发布安排、公开合作说明等额外证据。没有证据时不补出幕后推动者。
发布时间有什么解释
如有可靠时间信息,可对照财报、政策、行业事件或产品节点。也应考虑常规排期、新闻时效、转载延迟和偶合。只知道发布时间时,不硬写时机意图;不同发布时间或独立采编记录可能削弱协调传播假设。
表达选择有什么作用
分析标题、体裁、数据和信源如何支撑论点。普通编辑取舍、篇幅限制、专业分工、可取得的材料以及真实新闻价值,都可能解释单一角度或正面语气。专访、评论、研究稿等体裁提示信息获取与表达方式,不能直接推定控制度。若原文保留反例、不利事实或独立核验,应相应降低单方操控的判断强度。
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago Changed · +1 lines · +18 tokens per session 15024f428971
- 1mo ago Changed · +16 lines · -6 tokens per session 8ceb3d35040b
- 1mo ago First seen · 149 lines · 109 tokens per session scan A e8ea050824cf
media-narrative-analysis is a skill published in the GitHub repository chuwu57/Chuwu-PR-OS (84 stars, last pushed 13d ago), licensed MIT. It adds 121 tokens to every session and 2,827 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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