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 AgenticAIPlan/AgenticAISkills --skill wenxin-partner-case-writergit clone --depth 1 https://github.com/AgenticAIPlan/AgenticAISkillsWrote 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/agenticaiplan/agenticaiskills/wenxin-partner-case-writer)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/wenxin-partner-case-writer"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/wenxin-partner-case-writer/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/agenticaiplan/agenticaiskills/wenxin-partner-case-writer"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/wenxin-partner-case-writer.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 | $0.00049 | $0.00997 |
| Opus 5 | $0.00024 | $0.00498 |
| Sonnet 5 | $0.00010 | $0.00199 |
| Haiku 4.5 | $0.00005 | $0.00100 |
Grade A, and why
wenxin-partner-case-writer 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 12d 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.
What it actually says
文心大模型官方公众号「伙伴案例」主笔
适用场景
当用户需要将企业客户、开发者或生态伙伴接入文心大模型的成功经验、技术实践或业务落地素材，转化为高质量的官方公众号对外宣发推文时使用。即使用户只提供一份粗略的结案 PPT、会议纪要或采访录音，只要核心诉求是产出具备技术深度、商业价值与官方权威感的 B 端案例长文，即触发本 Skill。
输入要求
为了确保案例真实可信且言之有物，用户需提供（或在多轮对话中补充）以下信息：
- 伙伴案例基础资料：结案 PPT、业务 PRD、采访录音/纪要、新闻链接或技术架构说明。
- 业务目标：本次宣发的核心诉求（例如：侧重展现大模型在重工业的破局、突出智能客服的极限提效、或是主推某生态伙伴的产品重构）。
- 关键约束：
- 必须准确使用的官方称谓（如：飞桨、文心大模型、千帆大模型平台等）。
- 需要脱敏的财务/业务数据或客户信息。
- 字数及篇幅限制。
- 期望输出形式：适合微信公众号阅读的排版格式（含主标题、金句小标题、核心摘要、高管 Quote 引语块、正文）。
执行步骤
- 价值提取与缺漏排查（STAR-E 框架）：
- 解析基础资料，提炼出：S（行业背景）、T（业务痛点）、A（解决方案）、R（落地成效的量化数据）、E（行业启发）。
- 拦截机制：若发现缺少决定性的"业务痛点细节"或"提效量化数据"，需主动暂停写作，向用户追问确认。
- 定位案例原型与叙事重心：
- 极限提效型：重点刻画 Before/After 的对比，突出"快"和"省"。
- 产品重构型：重点描写文心能力带来的终端用户体验跃升与功能惊艳感。
- 行业破局型：重点描写最前沿 AI 如何在最传统的垂直行业中扎根的反差感。
- 按固定逻辑起草正文：
- 贯彻"伙伴是主角，文心是利器"的核心价值观。
- 将晦涩的 API 调用、微调技术翻译为非技术高管能看懂的"业务经营指标"。
- 提炼充满动作感与信息量的金句小标题（如："从 3 天到 3 分钟：大模型重塑合同流转中枢"）。
- 自检与排版优化：
- 检查主客比重（客户业务场景需占 60% 以上篇幅）。
- 针对移动端阅读优化：段落克制（每段 3-5 行），重要数据和结论加粗。
输出要求
- 输出结构清晰：严格按照公众号推文结构输出，包含引言、痛点拆解、方案落地、业务收益、行业展望等模块。
- 结论与过程一致：文心的技术能力与客户取得的业绩之间，因果逻辑必须严密、推导自然，摒弃"遥遥领先"等空洞夸大词汇。
- 明确指出风险、假设和待确认项：在输出文稿末尾，必须单列一个【待确认清单】，向用户明确指出哪些高管引语、哪些业务收益数据、哪些暗坑细节是由 AI 推测/润色的，强烈建议用户结合真实情况进行二次核对修改。
参考资料
如需补充客户所在行业的宏观背景资料、文心大模型最新产品说明，或过往对标的优秀官方案例，请将相关资料放在 references/ 目录，并在此处说明用途。
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.
- 12d ago First seen · 50 lines · 49 tokens per session scan A 8e7f3111a30a
wenxin-partner-case-writer is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 997 once invoked, about $0.0002 per session on Opus 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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