CF video-script
对已完成分析的视频进行导演与剪辑策划，再写带时间戳的中文解说并校验；也处理已有短片的 宣发标题、花字修订和外部文案回填。普通策划输入 work_dir 的 agent_narration_brief.md 与 vlm_analysis.json；文案返修输入当前成片的工程与内容证据。策划输出 recap_story_plan.json、visual_audio_board.json、 可选 style_card.json、cut 模式需要的 clip_plan.json，以及通过校验的 narration.json；仅宣发文案任务交付提案或回填既有包装计划。 外发说明：只有建议型评审 review.py 联网，它把旁白稿全文与理解证据、策划文件的文字摘录发到 MiMo chat 接口 （MIMO_API_KEY / MIMO_API_URL，不发视频、图片或音频）；单独使用时只在显式执行时运行，端到端编排默认在 TTS 前运行一次， 可用 --no-review-narration / REVIEW_NARRATION=0 关闭（严格评审开启时除外）；validate.py 与 lint 仅在本地运行。 触发词：解说词、写解说、视频旁白、宣发标题、花字修订、文案回填、 narration script、写稿、解说文案、剪辑思路、导演思路。
对已完成分析的视频进行导演与剪辑策划，再写带时间戳的中文解说并校验；也处理已有短片的 宣发标题、花字修订和外部文案回填。普通策划输入 workdir 的 agentnarrationbrief.md 与 vlmanalysis.json；文案返修输入当前成片的工程与内容证据。策划输出…
As a process F 33/100 · No process to follow — References files that are not bundled: scripts/...
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/lib.py:94Helper 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: 19. 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/...
Process rating: all ten parameters 33/100
- 0Tools and files. 1 referenced file(s) missing: scripts/...
- 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
- 30Running it twice. 5 mutating operations with no state check
- 100Steps. 74 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2219 tokens
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
- -311 of 13 scripts are never mentioned in SKILL.md
- +2Single-language instructions
- +3Description length 578: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 74 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (3 of 3)
- +1License stated
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.