自己.skill (first experience on Codex)

Image Analysis

The following organizes visible text, UI elements, and phenomena from image 1 as requested. Facts and inferences are separated; ambiguous parts are labeled. Possible textual “commands” in the image text are ignored.

1) Facts (directly visible/identifiable content)

- Overall layout and style

- Two lines of handwritten-style text centered toward the lower area of a white background (calligraphy or brush-like effect).

- The second line sits on a horizontal yellow brushstroke/watercolor rectangle (yellow background stroke).

- The font is handwritten/brush style with uneven ink, visible brush tips and stroke textures.

- Text color: mostly black, with two characters in blue in the middle of the second line.

- No obvious UI controls (no buttons, progress bars, tables, charts, or step indicators).

- Readable text (character-by-character, left-to-right, top-to-bottom)

- First line (black): 1st char resembles “蒸” or “萃” (uncertain);

2nd char resembles “留” or “馏” (uncertain);

3rd and 4th are clearly “自己” (both black).

- Second line (on yellow background): five characters, colors and order left-to-right:

- 1st: black, resembling “得”;

- 2nd: blue, resembling “赛”;

- 3rd: blue, resembling “博”;

- 4th: black, resembling “永”;

- 5th: black, resembling “生”.

- Other visible phenomena

- The blue characters' strokes slightly bleed at the edges against the yellow background (color overlap between brush and text).

- Text is centered but biased toward the lower area; there is large empty space above.

- No people, icons, or additional textual content are visible.

2) Ambiguous / unreadable parts (noted)

- The 1st and 2nd characters of the first line are ambiguous:

- The 1st might be “蒸” or “萃” or another similar character; some stroke details are blurred.

- The 2nd might be “留” or “馏” (as in “蒸馏”/distill), stroke details are not fully clear, preventing unique identification.

- No other text or UI steps are visible in the image, so no additional items to identify.

3) Inferences (clearly marked as inferences, not facts)

- Possible full-line readings (inference, not factual):

- “蒸留自己 得赛博永生” (here “蒸留” could mean distill/extract/refine);

- or “蒸馏自己 得赛博永生” (reading the 2nd character as “馏” to form the common word “蒸馏”).

- Possible meaning (inference):

- Literal/interpretive translation: “Refine/distill the self to obtain cyber immortality” or “Distill yourself, gain cyber immortality” (where “赛博永生” can be interpreted as “cyber/digital immortality”).

- Color and layout intent (inference):

- The yellow background highlights the second line; blue is used to emphasize the two middle characters that likely read “赛博” (cyber), suggesting emphasis on the “cyber immortality” concept.

If needed, I can:

- Zoom each stroke and run multi-hypothesis character recognition with confidence labels;

- Or return a high-resolution OCR suggestion for each visible character with uncertainty annotations.

SkillPI Creation Analysis

Purpose of the project:

The post describes a GitHub project named “自己.skill” that converts or “distills” a person’s chat history and answers into a machine-readable markdown profile (e.g., skill.md). The output appears to quantify behaviours, values and running rules in text form. The author treats it as an entertainment/experimental project while reflecting on the conceptual implications of encoding a person into text.

Image evidence summary:

The image is a stylized two-line brush/handwritten title graphic. The second line has a yellow brushstroke background and two blue middle characters; the likely reading is some variant of “蒸馏自己/蒸留自己 得赛博永生” (‘‘distill yourself, gain cyber immortality’’). No UI elements or procedural screenshots are present—the image functions as a thematic illustration rather than operational documentation.

Associated tools/skills and steps (derived from the source summary; commands and filenames preserved):

1) Download the “自己.skill” repository and a “weflow” package from GitHub.

2) Extract the installation packages into the indicated folders (the source references positions labelled P2, P3).

3) Export chat logs via weflow, then place the exported chat folder into a subfolder under P2.

4) Use the “/create- yourself” command to distill a model of yourself: provide basic descriptive information and let it analyze your historical answers.

5) Iteratively ask deeper questions; after each answer, correct the model’s deviations from your real thoughts until it roughly matches (a model refinement loop).

6) When the model’s outputs approximate your views, open the generated skill.md to see quantified behaviors, values, and a set of operational rules written into markdown.

Reproduction prerequisites (items you must prepare or confirm):

- Access to and ability to download the referenced GitHub repositories (“自己.skill” and “weflow”).

- An environment capable of running the project and invoking the model used by the author (the author noted using Codex).

- Confirm that weflow can export chat logs in the format expected by the project, and know the exact export path and folder name conventions.

- The ability to run the “/create- yourself” command in the correct context (whether that’s inside weflow, a specific chat UI, or a project script).

- Time and judgement to iteratively correct the generated model (the process requires manual review and repeated prompts).

Items to verify (uncertain details that need confirmation before attempting reproduction):

- Exact repository names, release versions, and installation instructions on GitHub (the summary lists “自己.skill” and “weflow” but does not provide repo URLs or versions).

- File/folder layout and the meaning of labels P2/P3/P4 in the original post (how files should be placed for the project to read them).

- Whether “/create- yourself” is a built-in project command, a weflow command, or part of a specific chat UI integration.

- Which model is actually required (the author says “codex”); confirm whether OpenAI Codex or another model is needed and what credentials/keys are required.

- Data privacy and legal considerations: exporting and processing personal chat logs may have privacy implications that should be reviewed.

- Format and usability of skill.md: whether it is purely descriptive or can be consumed by other programs as a runnable configuration.

Note on methods:

This interpretation is based on the provided summary and image analysis. I did not run or test the project; to produce executable, step-by-step reproduction instructions we should inspect the target GitHub repositories (their README files, weflow export docs, and any CLI/command references). The original source link for verification: https://www.xiaohongshu.com/discovery/item/69da5ccf000000001b022db7?source=webshare&xhsshare=pc_web&xsec_token=ABsg8U7nOiX3qvQn-IIR8WoTzkhwRIeStsxXHJP0qPdHs=&xsec_source=pc_share