BD douyin-book-seeding-video
为抖音图书种草、卖书带货、读书书单、书页展示和图书短视频提供联网研究、灵魂命题提炼、人物矛盾洞察、创作者立场、导演级分镜、口播、声音、翻页动作、氛围设计、商品承接与数据复盘。用户只提供书名、封面、少量书页或商品截图时，主动联网核验作者、出版社、目录、版本、公开试读、同书内容和同品类视频表达方式，并明确区分用户素材、联网事实、市场观察、创作推断和待核验信息。适用于文学小说、社科历史、商业成长、心理疗愈、亲子教育、儿童绘本、教辅工具、艺术摄影、漫画互动和礼品典藏等品类。用户提出制作或优化读书种草视频、卖书脚本、书单号内容、翻页视频、氛围短片、图书分镜、书页口播、商品视频或发布后复盘时使用。
为抖音图书种草、卖书带货、读书书单、书页展示和图书短视频提供联网研究、灵魂命题提炼、人物矛盾洞察、创作者立场、导演级分镜、口播、声音、翻页动作、氛围设计、商品承接与数据复盘。用户只提供书名、封面、少量书页或商品截图时，主动联网核验作者、出版社、目录、版本、公开试读、同书内容和同品类视频表达方式，并明确区分用户素材、联…
As a process D 47/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - warning
body-longSKILL.md body ≈ 5485 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 47/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (douyin-book-seeding-video) differs from the folder (dushu)
- 70Execution cost. Instruction body is 5485 tokens
- 100Tools and files. No external tools needed
- 100Steps. 605 steps
- 100Running it twice. No mutating operations
- low 26 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 296: enough signal without eating the budget
- +4Structure: 141 headings
- +3Step-by-step instructions: 605 items
- +4Has examples (3 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.