BF video-workflow-builder
视频创作工作流生成器。当用户想为自己的账号定制一套完整的视频创作流程（选题、文稿、标题、封面），或说"帮我做个账号工作流""定制视频流程""我想在抖音/B站/小红书/视频号/百家号做XX内容"时使用。它只问三件事（平台、垂类、人设），其余靠联网研究补齐，先给出账号定位诊断供确认，再生成一套可安装使用的专属工作流 skill。
视频创作工作流生成器。当用户想为自己的账号定制一套完整的视频创作流程（选题、文稿、标题、封面），或说"帮我做个账号工作流""定制视频流程""我想在抖音/B站/小红书/视频号/百家号做XX内容"时使用。它只问三件事（平台、垂类、人设），其余靠联网研究补齐，先给出账号定位诊断供确认，再生成一套可安装使用的专属工作流…
As a process F 35/100 · Will not run — References files that are not bundled: scripts/xxx.py, references/platforms/<平台>.md, references/skill-template/
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".
If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.
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.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Exfiltration
net-redirectable-api-keyscripts/generate_cover.py:69Helper sends the API key to a host configured by an environment variable — the key can be redirected to another serverAPI key + configurable base URL from environment
Files scanned: 33. 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/xxx.py - warning
missing-refreference to a missing file: references/platforms/<平台>.md - warning
missing-refreference to a missing file: references/skill-template/ - warning
missing-refreference to a missing file: references/platforms/*.md - warning
missing-refreference to a missing file: references/script-writing.md - warning
missing-refreference to a missing file: references/script-review.md - warning
missing-refreference to a missing file: references/skill-template/script-review.md.tmpl
Process rating: all ten parameters 35/100
- 0Tools and files. 7 referenced file(s) missing: scripts/xxx.py, references/platforms/<平台>.md, references/skill-template/
- 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. 64 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3280 tokens
- 100Running it twice. No mutating operations
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -37 of 15 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +5Description quotes 3 example trigger phrases
- +3Description length 163: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 64 items
- +4Has examples (4 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.