BD playlet-wechat-feed
短剧-公众号信息源 — 每日扫描公众号短剧爆款文章,按阅读量筛选热门内容,智能聚类题材方向后生成包含封面图、互动数据与创作洞察的HTML日报。支持按题材(穿越/霸总/重生等)、公众号、时间范围定向查询。⚠️数据每日15:00更新前一天数据,目标日期无数据时必须先告知用户并等待确认后才能调用接口,禁止自动获取。当用户需要短剧公众号日报、公众号短剧爆款、短剧热点、短剧创作趋势或自定义题材查询时使用。
短剧-公众号信息源 —…
As a process D 41/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
ProcedureSoftware developmentAI and agentstype and topics are labelled automatically from the skill text
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
For the model run — optional
- 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: 8. 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")
Process rating: all ten parameters 41/100
- 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 (playlet-wechat-feed) differs from the folder (playlet-gzh-feed)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 100Steps. 56 steps
- 100Execution cost. Instruction body is 3116 tokens
- 100Running it twice. No mutating operations
- low 10 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
- -4Absolute local paths (C:\Users, /home/…): not portable
- -237 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 199: enough signal without eating the budget
- +4Structure: 37 headings
- +3Step-by-step instructions: 56 items
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.
External checks
ClawHub: suspicious
The skill mostly does what it says, but it creates and auto-opens local HTML reports using unescaped external data, which makes installation worth review.
LLM: suspicious (high) · VirusTotal: · 23 Jun 2026