Install the "xiaobei-skill-image-to-vba" agent skill from https://github.com/xiao24bei/xiaobei-skill/tree/main/skills/xiaobei-skill-image-to-vba into .claude/skills/xiaobei-skill-image-to-vba/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "xiaobei-skill-image-to-vba", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "xiaobei-skill-image-to-vba" agent skill from https://github.com/xiao24bei/xiaobei-skill/tree/main/skills/xiaobei-skill-image-to-vba into .agents/skills/xiaobei-skill-image-to-vba/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "xiaobei-skill-image-to-vba", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "xiaobei-skill-image-to-vba" agent skill from https://github.com/xiao24bei/xiaobei-skill/tree/main/skills/xiaobei-skill-image-to-vba into .cursor/skills/xiaobei-skill-image-to-vba/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "xiaobei-skill-image-to-vba", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "xiaobei-skill-image-to-vba" agent skill from https://github.com/xiao24bei/xiaobei-skill/tree/main/skills/xiaobei-skill-image-to-vba into .gemini/skills/xiaobei-skill-image-to-vba/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "xiaobei-skill-image-to-vba", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "xiaobei-skill-image-to-vba" agent skill from https://github.com/xiao24bei/xiaobei-skill/tree/main/skills/xiaobei-skill-image-to-vba into .github/skills/xiaobei-skill-image-to-vba/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "xiaobei-skill-image-to-vba", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "xiaobei-skill-image-to-vba" agent skill from https://github.com/xiao24bei/xiaobei-skill/tree/main/skills/xiaobei-skill-image-to-vba into .opencode/skills/xiaobei-skill-image-to-vba/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "xiaobei-skill-image-to-vba", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
xiaobei-skill-image-to-vba
GitHub stars
586
Token cost
~6.9k tokens
SKILL.md length
3,386 words
Files
15 (incl. scripts, references, assets)
Skills in repo
3
Repo updated
First seen
Licence
Apache-2.0
At a glance
A skill your agent uses when users want XiaoBei skill / xiaobei-skill / 小北在读研 style academic image-to-VBA reconstruction: convert academic figures, scientific diagrams, slides, screenshots, or other…
Works in 8 steps: Input Recognition → Image Parsing → Coordinate Modeling → …
SKILL.md covers Output Language, Purpose, Default Deliverable Contract and Hybrid Preservation Mode, plus 3 more sections
Runs Python and PowerShell scripts from its folder
What it does
Xiaobei Skill Image To Vba is an agent skill from xiao24bei/xiaobei-skill. Use when users want XiaoBei skill / xiaobei-skill / 小北在读研 style academic image-to-VBA reconstruction: convert academic figures, scientific diagrams, slides, screenshots, or other images into VBA, Office drawing code, PowerPoint/Excel/Word shapes, editable shape reconstruction, 1:1 recreation, pixel-like approximation, or hybrid editable Office shape reconstruction.
Its SKILL.md is about 6.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 18 other files, including scripts, reference files and assets (for example `agents/openai.yaml`, `references/output-template.md` and `references/reconstruction-checklist.md`).
It sits in Documents & Office, covering PowerPoint presentations, Excel spreadsheets and Slides and decks. It works with Microsoft PowerPoint and Microsoft Excel. The repository describes itself as: 小北在读研开源 Codex Skills 合集:Image to VBA、Academic Paper to PPT 等 AI + 科研工作流。 The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 1b9fe1d. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 7 files in scripts/ (Python and PowerShell), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Xiaobei Skill Image To Vba loads about 6.9k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 3,386 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~99
When it runs· the whole SKILL.md, loaded when a task matches
~6.9k
With references· SKILL.md plus every file in references/, read only if the agent opens them
~11k
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
Download SKILL.mdSave it as .claude/skills/xiaobei-skill-image-to-vba/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.
name
xiaobei-skill-image-to-vba
description
Use when users want XiaoBei skill / xiaobei-skill / 小北在读研 style academic image-to-VBA reconstruction: convert academic figures, scientific diagrams, slides, screenshots, or other images into VBA, Office drawing code, PowerPoint/Excel/Word shapes, editable shape reconstruction, 1:1 recreation, pixel-like approximation, or hybrid editable Office shape reconstruction.
XiaoBei Image to VBA
小北在读研出品的 academic image-to-vba reconstruction skill. The workflow focuses on editable Office Shapes first, with carefully labeled raster crops only when complex scientific artwork should be preserved.
Output Language
All analysis, manifest tables, self-check reports, run reports, and conversational responses produced by this skill MUST be written in Simplified Chinese (简体中文). This includes:
Convert a reference image into a complete, runnable Office VBA macro that reconstructs the visual using editable Shapes, TextBoxes, Lines, Freeforms, fills, gradients, transparency, shadows, and ZOrder. When the image contains complex, distinctive graphic elements that would become noisy or low-value if rebuilt as hundreds of shapes, preserve those elements as cropped local image assets and reconstruct the surrounding structure with editable VBA Shapes. The core loop is: image -> environment detection -> visual decomposition -> editable-vs-preserved element plan -> Office coordinate model -> VBA Shapes code and cropped assets -> run or prepare the macro in the available presentation app -> self-check -> iterative correction.
Prefer editable Office Shapes for structure, labels, arrows, boxes, chart scaffolds, and readable text. Preserve complex graphic elements only as local cropped assets when that improves fidelity and keeps the VBA maintainable. Do not embed the full source image as a shortcut unless the user explicitly permits it or chooses the background-image-assisted option for complex photos. A PNG/JPEG/PDF preview is never the final deliverable for this skill; it is only allowed as a diagnostic screenshot after an editable Office reconstruction has been produced or attempted.
Default Deliverable Contract
When the user provides an image and asks for reconstruction, the default target is a presentation deck unless another Office host is explicit. Prefer Microsoft PowerPoint automation when available, but support WPS users and no-local-office users with a truthful fallback path. The agent must produce:
A complete VBA macro file or code block that reconstructs the image with editable Office Shapes.
Any preserved local image assets needed for hybrid reconstruction, with clear labels showing they are not editable Shapes.
A presentation file created from that macro when local automation is available, or a clear statement that local presentation automation was blocked or unsupported.
The generated deck opened for the user when local PowerPoint/WPS opening is available.
A short run report that says whether the macro was executed, whether the deck opened, and where the generated .bas / .pptx / .pptm files are located.
Do not satisfy an image-to-VBA request by generating only a PNG image, raster preview, static screenshot, or visual mockup. If a preview image is useful, create it only in addition to the editable VBA/PPT deliverables.
Hybrid Preservation Mode
Use hybrid preservation when any of the hard triggers below fire. Do not rely on subjective judgment about whether the result "looks cluttered" — model self-assessment is biased toward editable reconstruction, which causes complex artwork to be redrawn poorly. The goal is to preserve high-complexity artwork while keeping the diagram's editable structure editable.
Hard preservation triggers (hit any one → the element MUST be preserved as a raster crop):
The element is a microscopy image, 3D render, real photograph, or photo-realistic illustration.
The element contains photo-grade gradients, textures, noise, or organic shading that cannot be matched by a few solid fills or simple gradients.
The element is a logo, trademarked mark, or branded artwork.
A faithful editable reconstruction would require more than ~15 Shapes for that single element.
The element is hand-drawn, painterly, or has stroke-width variation that cannot be matched by simple Line/Freeform.
The user explicitly named the element as "keep as image", "保留", "不拆", or equivalent.
If none of the triggers fire, treat the element as editable. If a trigger fires but the user demanded "all editable", explain the fidelity tradeoff first and get permission before redrawing.
Classify every visible element into one of three buckets:
Preserved raster elements: distinctive illustrations, logos, scientific renderings, microscopy/photo crops, 3D objects, complex texture patches, dense molecular/mesh graphics, screenshots inside device frames, and hand-drawn/artistic elements whose shape-by-shape reconstruction would be noisy.
Background/base: plain solid/gradient backgrounds should be rebuilt as shapes; full-image background insertion is allowed only when the user explicitly asks for it or the source is photo-like.
Hybrid rules:
Preserve only the smallest useful crop around each complex element; do not insert the entire source image just to preserve a small object.
Put preserved assets behind or between editable layers according to the original z-order.
Recreate nearby labels, arrows, boxes, highlights, and callouts as editable VBA objects even when they overlap preserved artwork.
Name preserved image shapes with the generated prefix, for example AITVBA_Raster_Microscope_01.
Save cropped assets next to the generated VBA/deck, preferably under an assets/ subdirectory.
In the final response, list preserved elements separately from editable elements so the user knows which parts remain raster.
If the user requests "all editable", do not use preserved raster elements unless you first explain the fidelity tradeoff and get permission.
Before trying to materialize a deck, identify the user's local runtime. Use scripts/detect_office_environment.py when local shell access is available; otherwise infer from the user's stated OS and installed office suite.
Choose the delivery path in this order:
Windows + Microsoft PowerPoint: generate .bas, run scripts/vba_lint.py, then try scripts/run_powerpoint_vba_windows.ps1. Report if PowerPoint Trust Center blocks VBA import.
macOS + Microsoft PowerPoint: generate .bas, run scripts/vba_lint.py, then try scripts/run_powerpoint_vba_macos.py. Report if AppleScript automation or Office macro security blocks execution.
WPS Presentation / WPS Office only: generate conservative PowerPoint-compatible VBA and a .bas file. Do not assume automatic VBA import/run is available. If WPS can be opened locally, open it and provide WPS-specific manual import/run steps. If WPS macro support is absent or unverified, say that plainly.
No local presentation app or unsupported platform: still generate the .bas VBA source. When feasible, also generate an editable .pptx fallback from the same shape plan, clearly labeled as a non-VBA fallback. Do not substitute a PNG as the final output.
Use WPS-compatible mode when WPS is the only available app:
Avoid depending on advanced PowerPoint-only effects, complex TextFrame2 behavior, gradient stops, and macro security settings unless verified locally.
Save outputs in Microsoft-compatible formats (.bas, .pptx, .pptm) rather than WPS-only formats unless the user asks otherwise.
Label WPS results as compatibility-targeted, not fully PowerPoint-verified, unless they were actually opened and run in WPS.
Workflow
1. Input Recognition
Identify the target Office host:
Use PowerPoint when the user does not specify a host.
Use Excel when the user asks for a worksheet, dashboard, spreadsheet, chart sheet, grid, or Excel Shapes.
Use Word when the user asks for a document page, report, Word canvas, or inline/anchored drawing.
Ask a concise clarification only when the target host materially changes the solution and cannot be inferred. Otherwise proceed with the default presentation target, detect the available runtime, and attempt the best supported create/open path.
UI screenshot/poster: cards, bars, text, panels, tables, app screens. Aim for detailed reconstruction with editable text and shape groups.
Mixed scientific/academic figure with complex artwork plus labels: default to hybrid preservation for the complex artwork and editable reconstruction for text, arrows, boxes, connectors, legends, and callouts.
For detailed pattern examples, load references/vba-shape-patterns.md only when needed.
2.5 Element Manifest (mandatory)
Before writing any VBA, produce an explicit element manifest. This step is mandatory — do not skip to coordinate modeling or code generation without it. Skipping the manifest is the root cause of three frequent failures: missed preservation, drifted layout, and arrows pointing to wrong endpoints.
Output the manifest as a Markdown table or JSON list with these fields per element:
id: stable short id, for example E01, R01, L01. Use E* for editable, R* for preserved raster, L* for lines/arrows/connectors, B* for background.
bucket: editable, preserved, or background. Apply the hard preservation triggers from "Hybrid Preservation Mode" — do not guess.
bbox_px: (x, y, w, h) in source-image pixels. Required for every element except pure connectors. Estimate visually but commit to numbers; do not write ? or "approx".
style: fill color (hex or RGB), stroke color, stroke width, font size, font weight, opacity, shadow, gradient endpoints, etc. Use null only when the element has no such property.
text: exact text content for textboxes; null otherwise. Mark uncertain readings with a trailing (?).
endpoints: for arrows/lines/connectors only. Mandatory and strict. Format must be from:(x1_px,y1_px) -> to:(x2_px,y2_px) [anchor:<id>.<side>=<id>.<side>]. Both absolute pixel coordinates AND the semantic anchor (which element's which side) are required when the line connects two elements. Reasons:
Manifest gate: do not generate VBA until every visible element appears in the manifest. The number of rows in the manifest is the lower bound on the number of Shapes the macro will create (preserved elements count as one AddPicture each). If a region of the image has no manifest row, you have not parsed that region — go back to step 2.
3. Coordinate Modeling
Model the image in Office points by default.
Preserve the original aspect ratio.
For PowerPoint, prefer a proportional custom slide size based on the image ratio. Use 960 pt as the long side unless the user requests a specific slide size.
If the user requires a standard slide size such as 16:9, fit the image uniformly within that canvas and add offset_x_pt / offset_y_pt; do not stretch the image independently on X and Y.
Only use independent X/Y scaling when the target canvas exactly matches the source aspect ratio or when the user explicitly accepts distortion.
Convert each image coordinate using the ratio-safe method:
Use stretched conversion only for a ratio-matched canvas:
x_pt = x_px * target_width_pt / image_width_px
y_pt = y_px * target_height_pt / image_height_px
w_pt = w_px * target_width_pt / image_width_px
h_pt = h_px * target_height_pt / image_height_px
When exact image dimensions are known, use scripts/coordinate_helper.py to calculate scale values and examples.
Use named constants for canvas width, canvas height, and repeated colors.
Keep related objects grouped in code sections matching visual regions.
Show full SKILL.md (1,270 more words)Show less
4. Code Generation
Generate a complete runnable VBA macro, not a fragment. For the default presentation target, also save the macro as a .bas or .vba file in the working directory so it can be run or pasted without copying from chat.
Use a two-pass generation strategy. The two-pass split exists because layout errors are cheapest to catch before any styling is applied; do not skip Pass 1 to save time.
Pass 1 — Skeleton: emit one macro that draws every manifest row as a flat gray rectangle (or thin gray line for connectors) at its mapped point coordinates, with the element id printed inside as a label. No fills, no gradients, no shadows, no fonts beyond a default 10pt. The skeleton's only job is to confirm bbox positions, sizes, and arrow endpoints match the source. If the skeleton is visibly wrong, fix the manifest first, not the styling.
Pass 2 — Styled reconstruction: only after the skeleton matches the source, regenerate the macro with real fills, strokes, fonts, gradients, shadows, transparency, and ZOrder. Preserved raster crops enter at this pass via Shapes.AddPicture.
You may emit both passes as two separate Sub procedures inside the same .bas file (for example Sub BuildSkeleton() and Sub BuildFinal()), so the user can run the skeleton first and the styled version second without regenerating code.
The macro must include:
A Sub ... End Sub wrapper.
Host-appropriate setup:
PowerPoint: create a new presentation or a new blank slide by default, set slide size, and clear only generated shapes if working inside an existing deck.
Excel: create or use a worksheet drawing area, clear shapes in the target area, optionally adjust cells behind it.
Word: create or use a document page/canvas, clear generated shapes by name prefix where possible.
Canvas cleanup code.
Canvas size setup code.
Background creation code.
Code for every visible object, in back-to-front order.
Shapes.AddPicture code for each preserved local crop in hybrid mode, with LinkToFile:=msoFalse and SaveWithDocument:=msoTrue where the host supports it.
Named objects, for example shp.Name = "Header_Background".
Shared color helpers using RGB(...) or small helper functions.
Comments that label each visual region.
TextBox creation for legible image text.
Z-ordering when overlap matters, using ZOrder or creation order.
A stable generated-object prefix such as AITVBA_ for shape names and cleanup.
TextFrame / TextFrame2 font settings as appropriate for the host.
Shadow, GradientStops, PresetGradient, or layered translucent shapes to approximate effects.
5. Presentation Materialization
For the default presentation target, after generating the VBA:
Save the generated code to a local .bas or .vba file.
If hybrid mode is used, save preserved crop assets locally. Use scripts/crop_preserved_elements.py when crop coordinates are known.
Run scripts/vba_lint.py against the generated VBA file.
Detect the available local presentation environment:
Use scripts/detect_office_environment.py when possible.
Try to create/open the editable deck automatically when a supported path exists:
On Windows with Microsoft PowerPoint installed, use scripts/run_powerpoint_vba_windows.ps1.
On macOS with PowerPoint installed, use scripts/run_powerpoint_vba_macos.py when applicable.
With WPS only, do not assume automatic macro injection. Open WPS when possible, provide the .bas path, and give WPS-specific manual run steps.
If automation is blocked by Office macro security, AppleScript permissions, PowerPoint Trust Center, unsupported VBA injection, or WPS macro limitations, open the best available presentation app when possible and provide the exact macro file path plus concise manual steps.
Confirm in the final response which app was detected, which app was opened, whether the macro executed, which preserved assets were used, and whether a deck file was created. If it is not open, state the blocker directly.
The final answer must not imply that a PNG preview is the editable deliverable. It must distinguish between source image, preview screenshot, VBA source file, editable deck file, WPS-compatible file, and any non-VBA PPTX fallback.
6. Mandatory Self-Checks
Perform these self-check rounds before final output:
Structure check: verify no major object, region, text block, connector, or layer is omitted; verify back-to-front order.
Editability check: verify that text, arrows, boxes, connectors, and other structural elements were recreated as editable Shapes unless explicitly placed in a preserved crop.
Preservation check: if hybrid mode is used, verify that every preserved raster element has a crop asset, asset path, AddPicture placement, shape name, and reason for preservation.
Code check: verify VBA syntax, variable declarations, object references, Office host APIs, cleanup logic, shape names, generated-file path, and preserved asset paths. Use scripts/vba_lint.py as a lightweight smoke check when code is available as a file or can be copied into a temporary file; do not overstate it as a full VBA compiler.
Materialization check: verify that the macro was saved, that preserved assets were saved when needed, that the available office runtime was detected, that the appropriate PowerPoint/WPS path was attempted, and that the output deck is open or a concrete blocker is reported.
报告语言:每轮的差异分析、区域定位、修改说明都用简体中文(遵循文件顶部 Output Language 规则)。
仅在本机确实无法跑宏时(无 Office、Trust Center 拦截、沙箱环境),才允许跳过该闭环并降级为标注清楚的"人工目测估计",且必须在报告中说明为什么没跑、用户在哪里能自行运行该闭环。
If a check finds a gap, revise the VBA before responding. Mention unresolved uncertainty only after revising what can be revised.
7. Output Requirements
Use the structure in references/output-template.md:
Short explanation of the reconstruction strategy.
Artifact paths for the VBA file and deck file/open state.
Preserved raster asset paths and a short editable-vs-preserved element summary when hybrid mode is used.
Complete VBA code block.
Brief steps for running the VBA.
Self-check results.
Possible visual errors and why they remain.
Next-round optimization suggestions, especially if the user can provide a rendered screenshot.
Always include a short "How to run" section. Keep it host-specific and practical.
8. Error and Fidelity Policy
Do not promise perfect pixel-level reconstruction for complex photos, textures, real people, dense raster effects, or highly complex gradients. Explain that Office Shapes can approximate these but cannot fully reproduce raster detail.
Unless the user explicitly allows full-image insertion, do not place the original image on the slide/sheet/document and claim it is reconstructed. This restriction does not prohibit small local preserved crops in hybrid mode, as long as they are clearly labeled. If using a full background image is appropriate, label it clearly as the background-assisted option and keep editable overlays separate.
Never replace the editable deliverable with a PNG, screenshot, or generated raster image. A raster image may be used only for source analysis, validation, optional preview, or explicitly labeled local preserved elements in hybrid mode.
For "1:1" requests:
Increase detail and object count.
Preserve aspect ratio, palette, and layer order.
Avoid inventing hidden or unreadable details.
Mark uncertain text or shapes with comments in the VBA.
Bundled Resources
scripts/vba_lint.py: lightweight checks for generated VBA.
scripts/detect_office_environment.py: detect likely Microsoft PowerPoint/WPS runtimes and recommend a materialization path.
scripts/crop_preserved_elements.py: crop local preserved raster elements from the source image for hybrid reconstruction.
scripts/run_powerpoint_vba_macos.py: attempt to run generated PowerPoint VBA through macOS PowerPoint automation and bring PowerPoint forward.
scripts/run_powerpoint_vba_windows.ps1: attempt to import and run generated VBA through Windows Microsoft PowerPoint COM automation.
scripts/compare_images.py: compare source image and rendered VBA screenshot.
scripts/coordinate_helper.py: convert image pixels to Office point coordinates.
references/vba-shape-patterns.md: common Office Shapes patterns.
Xiaobei Skill Image To Vba next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
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How do I install Xiaobei Skill Image To Vba in Claude Code?
Run `npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a claude-code`. Or copy the skill folder (skills/xiaobei-skill-image-to-vba in xiao24bei/xiaobei-skill) into .claude/skills/xiaobei-skill-image-to-vba in your project. Claude Code loads it when a task matches its description.
How do I install Xiaobei Skill Image To Vba in Codex?
Run `npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a codex`. Or copy the skill folder (skills/xiaobei-skill-image-to-vba in xiao24bei/xiaobei-skill) into .agents/skills/xiaobei-skill-image-to-vba in your project. Codex loads it when a task matches its description.
Can I use Xiaobei Skill Image To Vba in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add xiao24bei/xiaobei-skill --skill xiaobei-skill-image-to-vba -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/xiaobei-skill-image-to-vba, .gemini/skills/xiaobei-skill-image-to-vba, .github/skills/xiaobei-skill-image-to-vba and .opencode/skills/xiaobei-skill-image-to-vba in your project.
What does Xiaobei Skill Image To Vba need to run?
Going by SKILL.md and its folder, Xiaobei Skill Image To Vba needs Python and PowerShell for the scripts in its folder. Our summary lists: Python 3; PowerShell.
Does Xiaobei Skill Image To Vba access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Xiaobei Skill Image To Vba safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Xiaobei Skill Image To Vba use?
Xiaobei Skill Image To Vba is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Xiaobei Skill Image To Vba use?
About 6.9k tokens (SKILL.md is roughly 28k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.7k tokens, read only when the agent opens those files.
What are the alternatives to Xiaobei Skill Image To Vba?
Skills that share tags, products or a category with Xiaobei Skill Image To Vba: Sn Da Non Spreadsheet Analysis (OpenSenseNova/SenseNova-Skills, 5.7k stars), Anydoc (magnus919/agent-skills, 115 stars), Officecli Commonly Templates (Team-Commonly/commonly, 1.4k stars) and PDF (zai-org/ZCode, 7.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Xiaobei Skill Image To Vba?
xiao24bei (a GitHub user) maintains it in xiao24bei/xiaobei-skill, which has 586 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on August 27, 2026.
Source: xiao24bei/xiaobei-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.