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 baidu-paddle-wenxin-operationgit 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/baidu-paddle-wenxin-operation)<a href="https://agentmods.dev/skills/agenticaiplan/agenticaiskills/baidu-paddle-wenxin-operation"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/baidu-paddle-wenxin-operation/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/baidu-paddle-wenxin-operation"><img src="https://agentmods.dev/badge/skills/agenticaiplan/agenticaiskills/baidu-paddle-wenxin-operation.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 | $0.00106 | $0.01262 |
| Opus 5 | $0.00053 | $0.00631 |
| Sonnet 5 | $0.00021 | $0.00252 |
| Haiku 4.5 | $0.00011 | $0.00126 |
Grade A, and why
baidu-paddle-wenxin-operation 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
Baidu Paddle Wenxin Operation
适用场景
当用户需要围绕百度飞桨、文心大模型及厦门本地 AI 生态开展日常运营信息搜集和线索整理时,使用本 Skill。
典型场景包括:
- 跟踪文心大模型、飞桨框架的最新发布、价格调整、活动和案例动态
- 汇总国内外大模型竞品的版本更新、推广动作和行业趋势
- 搜集厦门本地 AI 政策、补贴、活动和场景机会清单
- 挖掘厦门本地与 AI、数据、数字化转型相关的潜在客户并整理优先级
输入要求
- 业务目标:需要执行的模块范围,例如仅做资讯搜集、仅做客户挖掘,或四个模块全部执行
- 时间范围:当日动态、近 3 日动态、周度汇总等
- 重点关注对象:可指定企业、政策、活动、竞品或行业方向
- 输出形式:简报文档、周报、Excel 清单或结构化表格
执行步骤
- 先确认本次执行范围,对齐需要覆盖的模块、时间范围和重点关注对象。
- 按模块联网检索信息,并优先使用
references/source-map.md中的高优先级来源:- 模块一:百度飞桨与文心大模型官方动态、开发者生态、运营相关活动
- 模块二:国内外大模型及竞品动态,重点关注版本、价格、推广和行业趋势
- 模块三:厦门本地 AI 政策、补贴、产业园区动态、供需活动与机会清单
- 模块四:厦门本地潜在客户,优先识别有明确 AI 需求信号的企业
- 对采集结果做筛选和结构化整理:
- 保留权威、近期、与运营工作直接相关的信息,二手转载需尽量回溯原始来源
- 为每条资讯补充核心解读和运营参考,并标注来源链接、发布日期和抓取日期
- 为每个潜在客户补充需求方向、匹配度、优先级和明确的线索来源
- 输出整理结果:
- 资讯类内容按模块分类,标注信息类型、发布时间、抓取日期、来源 URL、核心要点和运营价值
- 潜在客户清单按优先级排序,保留企业名称、需求方向、线索来源、信号强弱和跟进建议
- 结果自查:
- 去重并剔除过期或无直接相关性的内容
- 检查资讯来源是否清晰、客户线索是否有依据,无法核实的信息必须标注为
待确认 - 对价格、政策、报名时间、客户信号等易过期信息,明确写出“发布时间”或“抓取日期”
- 对需要后续跟进的信息补充待确认项,不得把无来源内容写成既成事实
输出要求
- 资讯汇总:按模块组织,至少包含资讯标题、信息类型、发布时间、抓取日期、来源名称、来源 URL、核心解读、运营参考、待确认项
- 竞品动态:与文心和飞桨相关的竞品信息应单独标识,便于对比阅读
- 厦门政策活动清单:标明信息类型、发布单位、来源 URL、发布时间、实施时间或活动时间、报名截止时间(如有)
- 潜在客户清单:建议使用表格结构,至少包含企业名称、需求方向、匹配度、优先级、线索来源、来源 URL、抓取日期、待确认项
- 周度总结:提炼本周核心动态、对运营工作的价值以及建议跟进事项,并明确哪些结论仍需补充验证
实时信息约束
- 本 Skill 处理的是会随时间变化的运营信息,默认必须联网检索,不依赖记忆直接给出“最新动态”。
- 任何涉及发布时间、价格、政策补贴、活动安排、竞品版本、企业线索的内容,都必须带来源 URL。
- 无法确认原始来源、发布时间或真实性时,不得写成确定事实,应明确标注
待确认。 - 对二手媒体、转载文章、摘要号内容,优先回溯到官方公告、企业官网、原始活动页或原始报道。
- 对潜在客户线索,至少提供一个明确信号来源,例如官网公告、招聘页、招投标信息、活动名单或政府清单。
参考资料
references/source-map.md:四个模块的建议信息源和筛选重点references/output-template.md:资讯汇总、政策活动清单和潜在客户清单的推荐输出格式evals/evals.json:建议用于校验来源、日期、线索强弱标注是否完整的最小测试集
What ships with it
3 files 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.
- 12d ago First seen · 68 lines · 106 tokens per session scan A 14ea31167612
baidu-paddle-wenxin-operation is a skill published in the GitHub repository AgenticAIPlan/AgenticAISkills (11 stars, last pushed 3mo ago), licensed MIT. It adds 106 tokens to every session and 1,262 once invoked, about $0.0005 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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