BC local-video-ad-pipeline-v05-public
Local Video Ad Pipeline v0.5 is a public OpenClaw skill for producing short commercial videos and YouTube Shorts with local AI models. It uses a local LLM as the full film director: concept bible, story intent, visual arc, beats, shot direction, shotlist, image prompts, Korean subtitle script, and subtitle-based timing. Keyframes are generated with Qwen-Image or SDXL through ComfyUI, shots are animated sequentially with Wan2.2, optional BGM can be created with ACE-Step, and final MP4 assembly is handled with ffmpeg. Designed for local GPU workflows where models must be loaded one at a time. Includes character consistency rules, prompt-level identity locking, direct Qwen-Image keyframe generation, Korean subtitle wrapping, no-slow native-speed assembly, contact-sheet QA, and practical GPU coexistence guidance.
As a process C 62/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
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 skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
-
medium Dangerous commands
cmd-execpolicy-bypassSKILL.md:274Runs PowerShell with execution policy bypassedpowershell -ExecutionPolicy Bypass -File scripts/clea…ps1
-
low Secrets in code
secret-high-entropy-tokenreferences/preproduction.md:37High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)Recommended local model: `gemm…F16` when an uncensored concept writer is useful.
quoted
Files scanned: 22. 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
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 2 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 85Steps. 16 steps, 1 vague phrases
- 100Tools and files. No external tools needed
- 100Failures and branches. 11 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3882 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)
- +3Description length 820: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -2localhost URLs: will not work for another user
- +1No license
- +2Single-language instructions
- +4Structure: 14 headings
- +3Step-by-step instructions: 16 items
- +4Has examples (19 code blocks)
- +4Reference files are cited in the instructions (5 of 6)
- +3All 14 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.