AI Film Fully Automated: Full-Asset + H3 Prompt Creation Skill — Free Open Source, New Automated Skill Architecture

Image Analysis

Image evidence 1 — transcription

1. Readable text (approximate top-left to bottom-right order):

- 全自动 (Fully automatic)

- 全资产+ (Full assets +)

- MiniMax H3

- 提示词 skill (prompt skill)

- 开源免费分享 (open source free share)

2. Interface steps and chart data

- Interface steps: No obvious interactive UI steps are visible (no buttons, progress bars, step numbers, etc.).

- Chart data: No charts, axes, or numeric tables are visible in the image.

3. Observable facts (only direct visual observations)

- The image is a horizontal poster/advertisement combining illustration and photo elements, with a palette of gold, black, teal, and orange.

- Left side contains large headline text (see readable text above) using heavy, metallic 3D typography with splatter, wear, and glow effects.

- Upper-center background shows a conference room scene: a dark polished table (marble or similar) with glassware, documents, and pens; three adult men in suits sit facing left or conversing. A city skyline with multiple tall buildings (one resembling an Empire State–style skyscraper) is visible outside the window.

- Right side displays two stylized anime characters (illustrations):

- Upper character: white long hair, wearing glasses, calm expression, black military-style coat with gold cords, metal tassel epaulets and dangling earring.

- Lower character: pink short hair in loose double buns, small bandage on nose, playful tongue-out expression, wearing a black choker and teal jacket with orange lining over a white top.

- The text “MiniMax H3” highlights “H3” in a large gold 3D glowing style.

- The overall image includes sparks, light streaks, and spray-paint splatter effects to create motion and impact.

- The right-side characters, left conference scene, and central text are clearly composited (multiple layered elements).

4. Unreadable or incomplete items

- There may be small detail text or logos near the lower-right/borders that are not legible at the provided resolution/crop (no clear small-source text, copyright notice, or URL observed).

- Details of documents on the table and liquid in the glasses are not legible.

- Identities or names of the three suited men are not provided or legible.

5. Inferences (marked as inference, not direct observation)

- The image may be promotional for a product/project named “MiniMax H3,” emphasizing a “prompt skill” that is “open source free share” (inference based on visible text and common ad language).

- The white- and pink-haired anime characters may be mascot/persona designs for the brand/tool intended to attract a target audience (inference based on illustration prominence).

- The conference room and suited figures may be used to convey professionalism or business context in visual contrast to the anime characters (inference based on visual semantics).

- The poster style resembles promotional art for games, anime-related products, or AI prompt/tool promotions (inference, not stated in image).

6. Source info

- An image was provided without a source ID or URL — source information is incomplete and the original origin cannot be recorded from the provided crop.

SkillPI Creation Analysis

Intended use and deliverables:

- The provided item appears to advertise an open-source skill that claims to produce “fully automated” AI film outputs and generate H3 prompt sets. The summary includes two links for download/viewing: pan: https://pan.quark.cn/s/003f43212f85 and GitHub: https://github.com/AharaOoO/acheng-director-skill.

Key points from the image evidence:

- The poster clearly displays the phrases “全自动” (fully automatic), “全资产+” (full assets +), “MiniMax H3”, “提示词 skill” (prompt skill), and “开源免费分享” (open source free share). “MiniMax H3” and “H3” are visually emphasized, indicating a marketing focus rather than technical documentation.

Suggested steps to use the associated skill (generic open-source deployment workflow; specifics must be verified in the repository):

1) Download the source: visit https://github.com/AharaOoO/acheng-director-skill or the pan link https://pan.quark.cn/s/003f43212f85 and obtain the full package.

2) Read README/docs: locate README, installation guides, license information, and example configs in the repository.

3) Prepare runtime environment: install the required runtime (e.g., Python, Node.js — actual language and versions should be confirmed in the repo) and dependency manager.

4) Configure model/service credentials: if the skill calls external models or APIs, follow repo instructions to set API keys or local model paths (exact providers and interfaces must be checked in the code/docs).

5) Run sample scripts or the main entrypoint: use the example commands in README to execute the skill and inspect outputs (expected outputs per the poster are full asset bundles and H3 prompt files; confirm exact output names/formats in the repo).

6) Validate and tune: review generated assets and prompts, then adjust parameters or templates per repo guidance.

Prerequisites for reproduction:

- Ability to download the GitHub repository or the provided pan archive.

- A matching runtime environment and ability to install dependencies.

- Access to any external models or APIs required by the skill (accounts/API keys) if applicable.

- Basic development and debugging skills to read logs, resolve dependency issues, and inspect code.

Items requiring verification before attempting reproduction:

- Repository license and usage restrictions (commercial or other limitations).

- Exact dependency list (language, libraries, versions) and installation commands.

- Definition and implementation details of “H3” (the poster highlights “MiniMax H3” but does not explain what H3 denotes technically).

- What constitutes “full assets” in the project context and the output file formats.

- Whether the project requires specific closed-source models or can run with open-source/self-hosted models.

- Presence of example data, test scripts, or CI for result verification.

Caveats and limitations:

- This interpretation is based solely on the provided summary and image evidence; it does not validate internal repository code or runtime behavior. Follow the repository README and test in a controlled environment to confirm functionality. No claims of successful reproduction or effectiveness are made here.