BF astock-video-report
A股每日复盘视频自动生成。完整工作流：拉取非凸科技真实行情数据 → 抓取热点新闻 → AI 归因分析 → 生成横屏 PPT 幻灯片 → 合成视频+封面图。当用户说「生成今日A股复盘视频」「A股日报」「出今天的复盘」或触发定时任务时使用。
As a process F 35/100 · Will not run — References files that are not bundled: scripts/fetch_news.py, assets/bgm/eliveta-technology-474054.mp3, assets/fonts/NotoSansSC-Regular.ttf
ProcedureMedia and videoInfrastructureData and analyticstype 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.
- The text references files that are not there: add them or drop the references.
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") - warning
missing-refreference to a missing file: scripts/fetch_news.py - warning
missing-refreference to a missing file: assets/bgm/eliveta-technology-474054.mp3 - warning
missing-refreference to a missing file: assets/fonts/NotoSansSC-Regular.ttf
Process rating: all ten parameters 35/100
Will not run. References files that are not bundled: scripts/fetch_news.py, assets/bgm/eliveta-technology-474054.mp3, assets/fonts/NotoSansSC-Regular.ttf
- 0Tools and files. 3 referenced file(s) missing: scripts/fetch_news.py, assets/bgm/eliveta-technology-474054.mp3, assets/fonts/NotoSansSC-Regular.ttf
- 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
- 100Steps. 82 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2293 tokens
- 100Running it twice. No mutating operations
- low 11 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 tags): a typed call is more reliable
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)
- +3Description length 118: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 23 headings
- +3Step-by-step instructions: 82 items
- +4Has examples (12 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 4 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.
External checks
ClawHub: clean
This skill coherently generates A-share recap videos, with disclosed dependency installs and asset downloads that users should review before running.
LLM: benign (high) · VirusTotal: · 29 May 2026