AC dlazy-jimeng-i2v-first-tail
Generate coherent transition videos using Jimeng's first and tail frame models. 使用即梦 (Jimeng) 首尾帧生视频模型，通过提供的第一帧和最后一帧图片生成连贯的过渡视频。
As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, running it twice
GeneratorInfrastructureMedia and videotype 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: 3. 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 62/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 1 mutating operations with no state check
- 60Tools and files. Uses tools (bash, node) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 100Steps. 13 steps
- 100Failures and branches. 2 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1637 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)
- +1No license
- +2Single-language instructions
- +3Description length 128: enough signal without eating the budget
- +4Structure: 12 headings
- +3Step-by-step instructions: 13 items
- +3Output format is stated explicitly
- +4Has examples (6 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 75.
External checks
ClawHub: suspicious
This skill appears purpose-built for cloud video generation, but it asks agents to run a third-party npm CLI, upload user media to dLazy, store an API key locally, and follow overly forceful billing/authentication instructions.
LLM: suspicious (high) · VirusTotal: · 10 Sept 2026