Video Thumbnail Generator

Generate thumbnail candidates from video frames so creators, ecommerce teams, and operators can choose cleaner covers for social, storefronts, and internal s...

Security Scan

The skill is an instruction-only thumbnail-selection helper and its requests and instructions are coherent with that purpose; it does not ask for credentials, installs, or unrelated system access.

Purpose & Capability

Name, description, inputs, and outputs all describe extracting and evaluating frames from a source video. The skill does not require unrelated credentials, binaries, or config paths.

Instruction Scope

The SKILL.md stays within the thumbnail-generation domain (identify moments, extract frames, return candidates and rationale). It explicitly expects access to a source video file — which is reasonable — but does not declare which tools or commands (e.g., ffmpeg) will be used to extract frames. That leaves implementation choices to the agent and may result in running system commands or using external services at runtime.

Install Mechanism

No install spec and no code files are present, so nothing new is written to disk. This is the lowest-risk form for a skill of this type.

Credentials

The skill requests no environment variables, credentials, or config paths. The only required input is a source video file (appropriate for the stated purpose).

Persistence & Privilege

always is false and the skill is user-invocable; it does not request permanent presence or elevated privileges. Autonomous invocation is allowed by platform default but not uniquely enabled by this skill.

Assessment

This skill is instruction-only and internally consistent with its described purpose. Before installing or invoking it, confirm how the agent will extract frames (e.g., local ffmpeg vs. an external service) and whether you'll allow the agent to run system commands or upload video data. Do not feed sensitive or private video content unless you trust the execution environment; if you need tighter control, require the agent to show planned commands or run the extraction yourself and provide only the extracted frames.

Turn video frames into usable thumbnail candidates.

Problem it solves

A strong preview image often determines whether a video gets clicked, watched, or even noticed. But teams usually grab random frames manually. This skill helps extract and evaluate better thumbnail candidates from the video itself.

Use when

• A social or product video needs a better cover image
• A team wants several frame options instead of one random grab
• A storefront, gallery, ad, or internal review asset needs a clearer preview
• The user wants a simple thumbnail workflow without full design work

Do not use when

• The user needs full graphic design for a polished thumbnail
• The source video is too low quality to produce usable stills
• The better answer is a custom static image, not a frame grab

Inputs

• Source video file
• Target platform or use case
• Preferred frame qualities: face, product, motion-free, readable text, bright frame, etc.
• Optional desired count of thumbnail candidates

Workflow

1. Identify what makes a useful thumbnail for the target platform.
2. Extract candidate frames from visually strong moments.
3. Prefer frames with clarity, focus, and clean composition.
4. Avoid blur-heavy, transition, or awkward-expression frames.
5. Return a shortlist of thumbnail candidates with rationale.

Output

Return:

1. Candidate thumbnail frames
2. Why each is viable
3. Best recommended option
4. Risks if the video is weak for frame-based thumbnails

Quality bar

• Avoid motion blur, half-blinks, and awkward facial expressions
• Prefer clear product visibility or recognizable subject framing
• Match the thumbnail style to the platform use case
• Don’t oversell mediocre candidates as strong

Resource

See references/output-template.md.