漫剧老李 is an AI-assisted audiovisual production skill that guides the process from script development through storyboarding and prompts for video models. It is intended for AI short dramas, animated dramas, advertisements, previs, and other video projects where visual consistency across shots matters. The catalogue skill supplies the workflow and rules that coding agents can use to carry out this production process.
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 lixiaoxiao9888-create/manju-laoli-skill --skill sd-recon-enginegit clone --depth 1 https://github.com/lixiaoxiao9888-create/manju-laoli-skillWrote 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/lixiaoxiao9888-create/manju-laoli-skill/sd-recon-engine)<a href="https://agentmods.dev/skills/lixiaoxiao9888-create/manju-laoli-skill/sd-recon-engine"><img src="https://agentmods.dev/badge/skills/lixiaoxiao9888-create/manju-laoli-skill/sd-recon-engine/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/lixiaoxiao9888-create/manju-laoli-skill/sd-recon-engine"><img src="https://agentmods.dev/badge/skills/lixiaoxiao9888-create/manju-laoli-skill/sd-recon-engine.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 | $0.00331 | $0.03711 |
| Opus 5.5 | $0.00132 | $0.01484 |
| Sonnet 5.5 | $0.00066 | $0.00742 |
| Haiku 4.5 | $0.00033 | $0.00371 |
Grade A, and why
sd-recon-engine 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 3d 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 — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
sd-recon-engine · 素材采风与对标情报引擎（〇·1 素材来源锁 · 轻量版）
一、角色定位
为**「对标一个爆款」类需求**提供采风与情报整理。用户说「我要对标《XXX》」「帮我扒一下最近什么火」时，本引擎负责：把公开信息从全网（含外网）找回来，按固定格式交出去。
一句话概括本引擎存在的理由：
采风的价值不在「找到了什么」，而在「找到的东西是真的、来源标得清、时点说得明白」。 一份标错时点的榜单比什么都没找到更有害——它会让整个项目建立在一个已经过期的判断上。
⚠️ 轻量版边界（用户拍板 · 不得自行扩张）
本引擎只做三件事：
| 做 | 内容 |
|---|---|
| ① 信源清单 | 告诉执行者去哪找（见 source-ladder.md） |
| ② 情报卡模板 | 告诉执行者按什么格式交（见 intel-card.md） |
| ③ 证据纪律 | 告诉执行者怎么才不出错（见 recon-evidence.md） |
明确不做（这些属于"全流水线模式"，本轮不建，禁止临时发明）：
- ❌ 评分打分 / 入选门槛 / 双打分机制；
- ❌ 事件聚簇算法 / 热度公式 / 涨速计算；
- ❌ 持久化台账 / 持久化数据库 / 跨轮累计；
- ❌ 定时抓取 / 常驻监控 / 自动出简报。
需要上述能力时，如实告知用户"轻量版不含此项"，不要用近似说法糊过去。
二、与总控和套装的关系
- 锁来源：本引擎只在总控〇·1 素材来源锁选定 ③ 对标爆款 或 ④ 热点速成时挂载。锁未选定时不激活。
- 进入方式：完整流程从总控 short-drama-director 进入；总控锁系统（〇·0 赛道 → 〇·1 素材来源 → A·模型 / B·画幅 / C·交付 / D·段缝）先锁定，再进入生产层。
- 与其他子技能的关系：
- 与
sd-script-engine是前置供给关系——本引擎产出的《对标情报卡》是后者的上游输入之一（六阶段链的「① 来源登记」可直接引用情报卡的来源与结论）。本引擎不写剧本、不替代六阶段链。 - 与
sd-overseas-engine是正交关系——赛道② 海外剧同样可以先采风（外网信源已在清单内）；两者的挂载互不影响。 - 与
sd-decision-engine无直接传递——情报卡不决定机位选型。
- 与
- 不拥有：投喂格式（七段式 / H3）、机检脚本、资产编号、语速口径——权威都在总控。
三、触发词与进入
触发词：对标爆款、扒一下、采风、找资料、收集信息、热点、爆款分析、参考这部、题材调研、赛道调研、市场调研。
用户直接说触发词时，先声明一句：
完整制作（剧本、资产、分镜、投喂）请从总控
short-drama-director进入；素材来源请先按总控〇·1 确认（1 原创 / 2 改编 / 3 对标爆款 / 4 热点速成）。本引擎负责采风与情报整理——只交付《对标情报卡》，不写剧本。
进入前提：已确认〇·1 为 ③ 或 ④，且已明确对标对象（剧名 / 链接 / 题材方向）。对标对象未知时先停下追问——「对标某部具体的剧」与「看看这个题材最近什么火」是两次不同的采风。
四、采风四步（轻量流水线）
顺序固定，不跳步。每一步的产出都要能落到纸上，不能只在脑子里过一遍。
第 1 步 · 定目标
先写清采风要回答的问题（一次采风只回答一到两个主问题）：
| 目标类型 | 主问题 | 典型触发 |
|---|---|---|
| 单剧对标 | 这部剧到底怎么成的？哪些结构我能用？ | 「对标《XXX》」 |
| 题材扫描 | 这个题材最近什么最火？共性是什么？ | 「最近重生复仇火什么」 |
| 平台扫描 | 这个平台的榜单现在长什么样？ | 「红果现在榜上都是啥」 |
| 外网扫描 | 海外市场这个品类在跑什么？ | 「ReelShort 上什么类型火」 |
目标未写清 = 不开始检索（否则会把一整天花在无关信息上）。
第 2 步 · 定信源
按 source-ladder.md 选源。默认检索预算：
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.
- 3d ago Changed c04f16fdea63
- 4d ago Changed e15fb2344722
- 9d ago First seen · 185 lines · 331 tokens per session scan A 14967fdf12e5
sd-recon-engine is a skill published in the GitHub repository lixiaoxiao9888-create/manju-laoli-skill (1,658 stars, last pushed 4d ago), licensed MIT. It adds 331 tokens to every session and 3,711 once invoked, about $0.0013 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 2026-10-16.
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