Medical-research-skills short-video-script-generator
Generate popular science short video scripts based on topic, duration, and style. Invoke when the user needs to create scripts for short science videos.
install
source · Clone the upstream repo
git clone https://github.com/aipoch/medical-research-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/aipoch/medical-research-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/scientific-skills/Other/short-video-script-generator" ~/.claude/skills/aipoch-medical-research-skills-short-video-script-generator && rm -rf "$T"
manifest:
scientific-skills/Other/short-video-script-generator/SKILL.mdsource content
When to Use
- Use this skill when the request matches its documented task boundary.
- Use it when the user can provide the required inputs and expects a structured deliverable.
- Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.
Key Features
- Scope-focused workflow aligned to: "Generate popular science short video scripts based on topic, duration, and style. Invoke when the user needs to create scripts for short science videos.".
- Packaged executable path(s):
.scripts/validate_skill.py - Structured execution path designed to keep outputs consistent and reviewable.
Dependencies
:Python
. Repository baseline for current packaged skills.3.10+
:Third-party packages
. Add pinned versions if this skill needs stricter environment control.not explicitly version-pinned in this skill package
Example Usage
cd "20260316/scientific-skills/Others/short-video-script-generator" python -m py_compile scripts/validate_skill.py python scripts/validate_skill.py --help
Example run plan:
- Confirm the user input, output path, and any required config values.
- Edit the in-file
block or documented parameters if the script uses fixed settings.CONFIG - Run
with the validated inputs.python scripts/validate_skill.py - Review the generated output and return the final artifact with any assumptions called out.
Implementation Details
See
## Workflow above for related details.
- Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
- Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
- Primary implementation surface:
.scripts/validate_skill.py - Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
- Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.
Validation Shortcut
Run this minimal command first to verify the supported execution path:
python scripts/validate_skill.py --help
Short Video Script Generator
Generate short video scripts based on input topic, duration, and language style.
Inputs
- Topic: Subject of the video (Text, Required)
- Time: Duration (Options: 15-30s, 30-60s, 1-2min, 3-5min, 6-8min)
- Style: Script Structure (Options: Problem Description, Myth Busting, Benefit Delivery, Hazard Phenomenon, Industry Reveal, Golden Quote Sharing, Explosive Opening, Trending Topic)
- type: Script Type (Options: Spoken Script, Storyboard Script)
Outputs
- output: The complete generated short video script
Workflow
- Branch based on script type
- Generate script outline for the specific type
- Refine script details
- Output final script
Use Cases
- Science content creators needing quick video scripts
- Adjusting script style for different platforms and audiences
- Batch production of popular science short video content
When Not to Use
- Do not use this skill when the required source data, identifiers, files, or credentials are missing.
- Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
- Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.
Required Inputs
- A clearly specified task goal aligned with the documented scope.
- All required files, identifiers, parameters, or environment variables before execution.
- Any domain constraints, formatting requirements, and expected output destination if applicable.
Output Contract
- Return a structured deliverable that is directly usable without reformatting.
- If a file is produced, prefer a deterministic output name such as
unless the skill documentation defines a better convention.short_video_script_generator_result.md - Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.
Validation and Safety Rules
- Validate required inputs before execution and stop early when mandatory fields or files are missing.
- Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
- Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
- Keep the output safe, reproducible, and within the documented scope at all times.
Failure Handling
- If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
- If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
- If partial output is returned, label it clearly and identify which checks could not be completed.
Quick Validation
Run this minimal verification path before full execution when possible:
No local script validation step is required for this skill.
Expected output format:
Result file: short_video_script_generator_result.md Validation summary: PASS/FAIL with brief notes Assumptions: explicit list if any
Deterministic Output Rules
- Use the same section order for every supported request of this skill.
- Keep output field names stable and do not rename documented keys across examples.
- If a value is unavailable, emit an explicit placeholder instead of omitting the field.
Completion Checklist
- Confirm all required inputs were present and valid.
- Confirm the supported execution path completed without unresolved errors.
- Confirm the final deliverable matches the documented format exactly.
- Confirm assumptions, limitations, and warnings are surfaced explicitly.