Agent skill

Img2pptx

by Lancelot-Xie in Lancelot-Xie/img2pptx

Reconstruct raster reference images as one-slide editable, modular, auditable PPTX files containing a complete SVG.

Apache-2.0Auto-check passedDocuments & Office

Install Img2pptx

skills CLI
$ npx skills add Lancelot-Xie/img2pptx --skill img2pptx -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Lancelot-Xie/img2pptx img2pptx --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Lancelot-Xie/img2pptx.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/img2pptx .claude/skills/img2pptx && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
img2pptx
GitHub stars
163
Token cost
~5.9k tokens
SKILL.md length
2,997 words
Files
4 (incl. references)
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

Reconstruct raster reference images as one-slide editable, modular, auditable PPTX files containing a complete SVG.

  • Works in 12 steps: Model at the practical editing granularity → Handle complex visual motifs → Build the Component Manifest → …
  • The user asks to convert
  • SKILL.md covers Operating contract, Input normalization, Required outcome and 1. Model at the practical…, plus 17 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Img2pptx is an agent skill from Lancelot-Xie/img2pptx. Reconstruct raster reference images as one-slide editable, modular, auditable PPTX files containing a complete SVG. Use when the user asks to convert, reproduce, trace, vectorize, or rebuild a PNG, JPG/JPEG, WebP, TIFF, HEIC, screenshot, diagram, infographic, scientific figure, architecture figure, or workflow image into an editable PowerPoint slide.

Its SKILL.md is about 5.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `agents/openai.yaml`, `references/semantic-constraint-audit.md` and `references/visual-optimization.md`).

It sits in Documents & Office, covering PowerPoint presentations, Slides and decks and Data visualization. It works with Microsoft PowerPoint. The repository describes itself as: Turn AI-generated diagrams and raster references into editable, modular, audited PPTX slides. The licence is Apache-2.0.

When your agent uses it

  • The user asks to convert
  • Scientific figure
  • Architecture figure
  • Workflow image into an editable PowerPoint slide

Example prompts

  • “/img2pptx”

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Model at the practical editing granularity
  2. Handle complex visual motifs
  3. Build the Component Manifest
  4. Build the layout skeleton
  5. Draw each standalone module
  6. Use PowerPoint-friendly border layering
  7. Run the Standalone Module Integrity Audit
  8. Assemble the complete SVG
  9. Run the Parent-Child Containment Audit
  10. Run the Alignment and Spacing Audit
  11. Run the Border Layering Audit
  12. Run the Original-to-Render Visual Similarity Audit

What it can do on your machine

Read from SKILL.md and the folder at commit 64d0323. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json and xml).

    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

Img2pptx loads about 5.9k tokens when it runs, and up to ~9.4k if it reads all its reference files. Until then it costs about 90 tokens; SKILL.md has 2,997 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~90
When it runs · the whole SKILL.md, loaded when a task matches
~5.9k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.4k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from Lancelot-Xie/img2pptx at commit 64d0323, republished under its Apache-2.0 licence (© Lancelot-Xie). 2,997 words, ~5,922 tokens.

Download SKILL.mdSave it as .claude/skills/img2pptx/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
img2pptx
description
Reconstruct raster reference images as one-slide editable, modular, auditable PPTX files containing a complete SVG. Use when the user asks to convert, reproduce, trace, vectorize, or rebuild a PNG, JPG/JPEG, WebP, TIFF, HEIC, screenshot, diagram, infographic, scientific figure, architecture figure, or workflow image into an editable PowerPoint slide.

Img2Pptx

Reconstruct an input raster reference as a one-slide PPTX that is editable, decomposable, reusable, and auditable. Treat this Skill as an execution protocol; do not reduce the task to drawing an image that merely looks similar.

Operating contract

Apply the following rules to every task:

  1. Inspect the input file, working directory, and locally available tools.
  2. Create task-specific drawing, rendering, cropping, comparison, PPTX-generation, and audit scripts in the current task workspace as needed.
  3. Do not assume that scripts, component names, canvas dimensions, layouts, or thresholds from a previous task apply to the current task.
  4. Prefer tools already available in the environment. Do not bind the Skill to a specific programming language, browser path, or operating system.
  5. Keep task-specific implementation in the current task directory so the result remains reproducible, modifiable, and auditable.
  6. Continue through reconstruction, rendering, QA, correction, PPTX generation, and final audit. Do not stop after producing the first SVG draft.
  7. Do not modify the original input image.

Input normalization

Accept PNG, JPG/JPEG, WebP, and other common raster formats that local tools can decode.

For TIFF, HEIC, multi-frame images, color-profiled images, or formats with unreliable decoding support:

  1. Preserve the original file and convert the target frame to a standard PNG losslessly or at high quality.
  2. Normalize color space and orientation, then use the normalized PNG as the baseline for subsequent pixel comparisons.
  3. Record both the original and normalized files in the manifest.

Use the input image's actual dimensions and aspect ratio. Unless the user explicitly requests a standard slide ratio, make the PPTX page ratio match the input image.

Required outcome

The result MUST satisfy all of the following:

  • Produce a one-slide PPTX containing the complete full.svg; do not use a full-slide bitmap as the only embedded representation.
  • A PNG fallback may also be present, but SVG MUST remain the primary vector representation and should support PowerPoint Convert to Shape or Ungroup as far as reasonably possible.
  • Preserve text as editable SVG <text> wherever practical, and preserve graphics as vector shapes, paths, or vector groups wherever practical.
  • Make every required exported module self-contained, and complete structural audits, visual comparisons, PPTX audits, and automatic corrections.
  • Clearly distinguish "the SVG is embedded in full" from "all hierarchy survives conversion inside PowerPoint." The latter depends on the PowerPoint version and SVG importer; never claim it without verification.

1. Model at the practical editing granularity

Decompose content according to semantic integrity and real editing needs, not mechanically by geometric primitive.

An editable unit should, as far as practical:

  • remain complete when isolated, with a clear boundary, independent meaning, or visual function;
  • be movable, replaceable, or modifiable on its own;
  • avoid producing large numbers of meaningless fragments after ungrouping.

Do not treat half a border, half an icon, an isolated decoration, or a contextless line segment as a semantic module.

Semantic module: semantic-unit

Define a visual unit that independently expresses a complete concept or performs a clear function as a semantic module. Examples include a panel, flow submodule, report box, process node, structural module, relationship arrow, input box, output box, or annotation box. Identify modules from the actual input; do not force the content into a fixed type list.

Composite submodule: combination-submodule

Define a group of elements that jointly carries locally complete meaning as a composite submodule. Examples include:

  • icon + label;
  • title + divider;
  • icon row;
  • one row inside a report box;
  • structural formula + name;
  • arrow + annotation;
  • status icon + value.
Atomic element: atomic-element

Define the smallest element that has no practical need for further decomposition at the target editing granularity as an atomic element. Examples include:

  • editable text;
  • line, rect, circle, ellipse, polygon, or polyline;
  • SVG path;
  • basic icon;
  • small, complex vector motif;
  • logo or brand mark;
  • fragments of molecular structures, cells, and other scientific illustrations;
  • small illustrations or specialized symbols.

"Atomic" means that further decomposition has no practical editing value, not that the element is geometrically indivisible. A complex icon may use a <g> or <symbol> with its own id; the manifest may classify it as atomic while still allowing its internal paths to remain editable after PowerPoint conversion.

2. Handle complex visual motifs

For logos, complex icons, molecular structures, small illustrations, and similar content, use the following options in order:

  1. Reuse vector assets already present in the input materials, or use a reliable official SVG or specification-compliant asset when available.
  2. Redraw, trace, or vectorize the motif from the reference image.
  3. If necessary, generate the motif first and then convert it to vector form.
  4. Use an embedded raster image ONLY when reasonable vectorization is not possible.

To preserve visual fidelity, recognizable icons, scientific symbols, and small visual motifs from the reference MUST retain their graphical identity and basic appearance. MUST NOT replace them with text, emoji, Unicode characters, a different icon, or a generic placeholder merely for implementation convenience or editability, unless the reference itself uses that representation. Prefer vector redrawing. ONLY when reliable redrawing is not possible and substitution would cause obvious visual distortion may the relevant source crop be preserved as an independent atomic raster image. In that case, record its source region, reason for use, and later replacement status in the manifest.

Do not use a source crop to replace any module that can reasonably be reconstructed as editable vector content merely to save drawing effort. Preserve a local raster crop only when the source content is inherently raster or vectorization would materially reduce visual fidelity or information accuracy, and crop only the minimum necessary region.

Do not evade the vector-reconstruction requirement by slicing the source into raster tiles and reassembling them. An allowed raster region MUST NOT unnecessarily include text, borders, arrows, connectors, or other graphics that can reasonably be reconstructed as separate editable vector elements.

Every independently identifiable icon or small visual motif MUST be cropped from the normalized source and inspected at increased scale before drawing. After reconstruction, render it independently and compare it with the enlarged source crop side by side and with an overlay or amplified diff. Verify silhouette, internal structure, orientation, stroke weight, color, negative space, and distinguishing features. Apply this even when reusing a vector asset. If the source is too ambiguous, require review and do not invent details.

Do not draw a brand logo from memory. Prefer the shape shown in the input, or use a reliable specification-compliant asset.

When using a raster image, record the following in the manifest:

  • representation: raster-image;
  • reason for use;
  • original source;
  • whether it can later be replaced with a vector.

Extract semantic constraints from the source (mandatory)

Before drawing, identify every component whose meaning depends on color, position, direction, order, count, connectivity, containment, sign, rank, or symbol choice. For each such component:

  1. Crop it from the normalized source and inspect it at increased scale.
  2. Record directly observed source_observations; keep inference separate from direct observation.
  3. Define executable visual_invariants and negative_constraints.
  4. Assign an audit_method and one unique audit_check to every hard constraint.
  5. Mark uncertain observations for human review. Do not fill gaps from common knowledge or fabricate data.

For charts, tables, rankings, flow diagrams, architecture diagrams, scientific figures, maps, timelines, or annotated sequences, MUST read and follow the Semantic Constraint and Audit Protocol. Activate only the rules relevant to the current component type; do not mechanically apply chart rules to an ordinary illustration.

Semantic correctness is a hard gate. Low MAE, structural completeness, or a PPTX that faithfully reproduces the generated SVG cannot override errors in color meaning, axis side, direction, topology, order, or mutual exclusivity.

3. Build the Component Manifest

MUST create component_manifest.json before drawing. Use it as the source of truth for subsequent drawing, module export, parent-child containment checks, alignment checks, and component crop diffs.

Record at least the following for every component:

json
{
  "id": "evidence_a_report",
  "label": "Structure report card",
  "parent": "panel_evidence",
  "bbox": {
    "x": 0,
    "y": 0,
    "width": 100,
    "height": 80
  },
  "level": "semantic-unit",
  "export": true,
  "editable_parts": ["title", "divider", "rows", "icons", "labels"],
  "representation": "svg-group",
  "render_strategy": "vector-reconstruction",
  "semantic_role": "structure report",
  "source_observations": [],
  "visual_invariants": [],
  "negative_constraints": [],
  "notes": "Keep outline as final child"
}

Prefer the following fields:

  • identity and hierarchy: id, label, parent, level;
  • geometry and export: bbox, export;
  • editing and representation: editable_parts, representation, render_strategy;
  • source and constraints: asset_source, constraints, notes;
  • semantics and audit: semantic_role, source_observations, visual_invariants, negative_constraints, audit_mapping.

Also record the canvas, normalized input file, default padding, outline parameters, and visual-optimization parameters. Every hard semantic constraint MUST map to an audit check that is actually executed. If a constraint is unmapped, unexecuted, or lacks evidence, the constraint-coverage audit MUST fail.

4. Build the layout skeleton

Reconstruct these large-scale relationships first:

  • canvas dimensions, aspect ratio, and main-title position;
  • bounding boxes of major panels and cards, plus the direction of primary arrows;
  • module spacing, column widths, row heights, and overall visual center of mass.

At this stage, establish only the structure and large-scale relationships. Do not handle complex icons or fine details yet.

Run a layout-skeleton audit and check:

  • whether major panels align at the top and bottom, and whether their widths and heights are close to the source;
  • whether major column gaps are reasonable and submodules visibly stay within bounds;
  • whether primary arrows connect correctly and the overall visual balance is close to the source.

Proceed to detailed drawing only after the skeleton audit passes. Never hard-code the layout audit as passing.

5. Draw each standalone module

Draw semantic modules one by one from the input image and manifest. Possible examples include a query card, retrieval card, report card, decision bucket, LLM input, final prediction, arrow, or annotation box. These are examples, not a fixed component list.

Every independently exported module MUST:

  • carry complete meaning and retain safe padding;
  • use its own <g id="...">, preserve text as SVG <text> wherever practical, and use SVG vector elements for graphics wherever practical;
  • contain complex icons in self-contained <g> or <symbol> elements;
  • render correctly without depending on elements outside the module.

Avoid SVG features that compromise PowerPoint conversion. Prefer text, rect, line, circle, ellipse, polygon, polyline, and path. Avoid foreignObject, unnecessary filters, external-resource dependencies, and complex CSS. When <defs>, gradients, clipPath, or symbols are necessary, ensure that every standalone module carries all of its dependencies and verify the PowerPoint preview.

6. Use PowerPoint-friendly border layering

Important container borders MUST use:

text
fill-only background + top-layer outline

Apply this rule to panels, cards, report boxes, buckets, input cards, final prediction cards, and similar containers:

  • The background shape supplies only the fill and uses stroke="none".
  • Use a separate outline shape as the last visual child of the corresponding semantic-module group, with fill="none".
  • Use a suggested stroke-width of 1.4px–1.8px.
  • Inset outline coordinates by 0.5px–1px.
  • Do not apply a shadow or filter to the outline. The background and outline layers MUST NOT draw the same border twice.
  • Treat the outline as an atomic element of its container, not as an independent semantic-module export.

7. Run the Standalone Module Integrity Audit

Generate a standalone SVG for every module with export: true, then check each one for:

  • clipping or content within 2 px of an edge;
  • overflowing text, incomplete icons, or incomplete borders;
  • clipped shadows or decorations;
  • semantic completeness when isolated;
  • complete inclusion of dependencies such as <defs>, gradients, clipPath, and symbols.

MUST correct missing text, missing edges, clipping, unsafe edge proximity, or missing dependencies.

Show full SKILL.md (1,175 more words)Show less

8. Assemble the complete SVG

After all standalone modules pass, assemble them into full.svg according to the bounding boxes in the manifest.

Preserve the actual parent-child hierarchy, for example:

xml
<g id="panel_evidence">
  <g id="evidence_a_unit">
    <g id="capsule_a">...</g>
    <g id="arrow_a">...</g>
    <g id="structure_report_card">...</g>
  </g>
</g>

Do not flatten every element into sibling SVG nodes. Preserve hierarchy to support:

  • PowerPoint ungrouping;
  • moving complete modules;
  • further decomposition of submodules;
  • independent editing of atomic elements;
  • QA localization and automatic correction.

9. Run the Parent-Child Containment Audit

Check that every child-module bounding box lies entirely within its parent bounding box. Preserve 6–10 px of inner padding by default; document any exceptionally compact layout in the manifest.

Check that:

  • no submodule crosses its parent's boundary;
  • no submodule touches an edge without justification;
  • no submodule intrudes into an adjacent panel;
  • every parent-child relationship is correct;
  • cards, capsules, buckets, and similar elements stay inside their assigned panels;
  • each module's actual rendered bounds substantially match its manifest bounding box.

Treat every failure as a structural error and correct it.

10. Run the Alignment and Spacing Audit

Check:

  • top and bottom alignment of panels;
  • consistent left and right edges for cards of the same type;
  • correct title alignment;
  • correct arrow-to-module connections;
  • even spacing between modules in the same column;
  • consistent sizing of like elements;
  • whether submodules are overcrowded or excessively sparse;
  • consistent border weights;
  • visual-center alignment between icons and text;
  • clear text readability: no opaque shape unintentionally covers text, and no border, arrow, connector, or decorative line passes through readable glyph areas; allow intentional source-faithful cases;
  • absence of doubled or misaligned outlines.

11. Run the Border Layering Audit

Specifically check:

  • whether every important container uses a fill-only background;
  • whether a separate top-layer outline exists;
  • whether duplicate strokes exist;
  • whether the outline is the last visual element in its group;
  • whether the outline is inset;
  • whether the outline is free of filters and shadows;
  • whether borders remain stably visible while grouped;
  • whether borders remain present after ungrouping;
  • whether any border appears doubled, thickened, misaligned, or clipped.

Run the Semantic Constraint and Coverage Audit

Audit every component whose meaning depends on visual encoding, and produce:

text
qa/semantic_constraint_audit.json
qa/constraint_coverage_audit.json
qa/semantic_review_sheet.png

Check only the invariants applicable to each component type. For charts, focus on series colors, legends, axis sides, positive and negative direction, peaks/grouping, order, mutually exclusive regions, and forbidden overlaps. For flow diagrams, focus on nodes, edges, arrow direction, ports, branch merging, and topology. For tables, rankings, and sequences, focus on order, association, span, length relationships, duplication, and omission. For scientific figures, focus on symbols, labels, connections, direction, and color semantics.

Also check elements, colors, connections, overlaps, orders, or regions that MUST NOT appear. Prefer direct audits of SVG groups, IDs, attributes, and geometric relationships; supplement these with color masks, foreground comparisons, or human review.

Generate a constraint-coverage table confirming that every hard source observation has a constraint, every hard constraint has an audit mapping, every check was actually executed, and the evidence is relevant. The aggregate hard gate MUST fail if any hard semantic constraint fails, lacks coverage, or requires review that was not performed. See the Semantic Constraint and Audit Protocol for the complete rules.

12. Run the Original-to-Render Visual Similarity Audit

After structural audits pass, compare the source and reconstruction and produce:

  • normalized original PNG;
  • rendered SVG;
  • 50/50 overlay;
  • amplified diff;
  • original crop for each component;
  • rendered crop for each component;
  • diff crop for each component;
  • component_diff_sheet.png.

Calculate both whole-image MAE and component-level MAE. Do not allow large areas of flat background to conceal local errors. MAE is a localization and optimization signal; it does not replace containment, standalone integrity, border layering, or semantic visual checks.

For semantically dense components, also calculate applicable foreground-weighted, per-color, per-region, per-axis-side, or mask-based metrics. Inspect at increased scale every region with a hard semantic constraint, an uncertain observation, or high component error. An improvement in whole-image MAE cannot override a semantic-constraint failure.

Never hard-code passed: true before calculating and evaluating the relevant metrics. Record actual values, thresholds, attempt counts, and target status for every visual-optimization result.

13. Generate and audit the PPTX

Generate a one-slide PPTX containing the complete full.svg.

Check:

  • that the PPTX package contains an SVG;
  • that a full-slide PNG is not used as the sole replacement for the SVG;
  • that the embedded SVG matches full.svg, preferably by content hash;
  • that the PPTX preview matches the rendered SVG;
  • that borders are clear while grouped;
  • that text is neither corrupted nor displaced;
  • that the same text-readability check passes in the rendered PPTX preview, including after any font substitution or displacement;
  • that the content is reasonably prepared for PowerPoint Convert to Shape or Ungroup;
  • that nested groups remain present in the embedded SVG bytes;
  • that no critical unsupported PowerPoint SVG features are present;
  • that SVG fallback and relationships are correct;
  • that the PPTX contains exactly one slide.

Report "embedded SVG integrity," "conversion readiness," and "fidelity after actual conversion" separately. Claim complete preservation of hierarchy after conversion ONLY after performing and inspecting the conversion in PowerPoint.

14. Complete the mandatory correction loop

Do not deliver the first version without correction. Whenever a hard failure is found, execute:

text
detect issue
→ locate component id
→ classify issue
→ modify bbox / coordinates / dimensions / padding / font size / path / arrow / outline
→ re-export module
→ reassemble full.svg
→ re-render
→ rerun QA
→ update audit results

Continue correcting until none of the following hard constraints has an unresolved issue:

  • layout skeleton;
  • standalone integrity;
  • parent-child containment;
  • alignment and spacing;
  • border layering;
  • semantic constraints and negative constraints;
  • constraint coverage and required human review;
  • SVG/PPTX package embedding;
  • structure and readability of the PPTX preview.

Do not ignore a failed hard audit merely because final files have been generated. Establish an aggregate gate; if any hard audit fails, MUST NOT claim that the final result passed in full.

15. Perform bounded, reversible, non-degrading MAE optimization

Begin visual optimization ONLY after all structural, semantic, constraint-coverage, and PPTX-compatibility hard audits pass. Read and follow Visual Similarity Optimization.

Attempt at most three iterations by default, targeting a 10% relative MAE improvement against the first valid baseline. Start every attempt from a complete copy of the current best, make only local and explainable changes, and rebuild the modules, full.svg, PPTX, preview, semantic masks, and all QA.

Accept a candidate ONLY if it still passes every hard gate, introduces no semantic or local regression, and improves the metrics; otherwise, roll it back. A verified semantic correction takes precedence over global MAE, but record the failed constraint, correction evidence, and metric tradeoff. The 10% improvement is a soft target; structure, semantics, coverage, and embedding integrity always remain hard gates.

16. Final delivery

MUST deliver:

text
final.pptx
full.svg
component_manifest.json
modules/*.svg

qa/layout_skeleton_audit.json
qa/standalone_integrity_audit.json
qa/containment_audit.json
qa/alignment_audit.json
qa/border_layering_audit.json
qa/semantic_constraint_audit.json
qa/constraint_coverage_audit.json
qa/semantic_review_sheet.png
qa/semantic_masks/*
qa/visual_similarity_audit.json
qa/full_overlay_diff.png
qa/amplified_diff.png
qa/component_diff_sheet.png
qa/pptx_slide_preview.png
qa/pptx_preview_audit.json

Semantic-audit files and masks are mandatory ONLY when the source contains components whose meaning depends on visual encoding. For all other tasks, record not_applicable in the aggregate report; do not fabricate an empty passing result.

The file intended for actual use is final.pptx. QA files demonstrate whether the reconstruction is reliable, complete, decomposable, editable, and auditable.

Before delivery, confirm:

  • the final files come from the complete best state;
  • final.pptx, full.svg, the manifest, modules, and QA are mutually consistent;
  • all structural, semantic, constraint-coverage, and PPTX hard audits pass;
  • every item requiring human semantic review has a genuine review status;
  • visual-optimization status is reported truthfully;
  • if the 10% soft target was not reached, the actual stopping reason is stated and the best valid version is delivered.

© Lancelot-Xie, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in skills/img2pptx of Lancelot-Xie/img2pptx.

  • SKILL.md
  • agents/openai.yaml
  • references/semantic-constraint-audit.md
  • references/visual-optimization.md

Open the folder on GitHubat commit 64d0323

Compare with similar skills

Img2pptx 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.

Img2pptx compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
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PPTX Generatorcoleam00/ai-transformation-workshop147—~9.9kAutomated safety check: PassNone
Linkedin Carousel Generatordmccreary/ibook-skills105—~3.7kAutomated safety check: PassCC-BY-NC-4.0
Create PresentationJetBrains/youtrackdb439—~1.8kAutomated safety check: PassApache-2.0
Deck Studiostaruhub/ClaudeSkills728—~1.7kAutomated safety check: PassMIT

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    PPT 生产 Agent:理解场景 → 推荐风格 → 先出大纲 → 定义页面 → 双通路交付(PPT 内容稿 / 逐页视觉图 / 信息图组图)。当用户要做汇报、路演、培训课件、提案、咨询报告的演示文稿,或要把大纲/文章做成 slides、deck、PPT、信息图、小红书图文、可视化传播图时使用。支持指定风格或从风格库推荐,支持 image 模型逐页出视觉稿。前身为…

    728 GitHub stars~1.7k tokensUpdated 1 mo ago
    Documents & OfficeAuto-check passed
  • Data Viz Deck

    thatrebeccarae/claude-marketing

    Transform audit data, performance reports, and structured analyses into polished visual deliverables.

    161 GitHub stars~1.8k tokensUpdated 4 mo ago
    Documents & OfficeAuto-check passed

Questions about Img2pptx

What does Img2pptx do?

Reconstruct raster reference images as one-slide editable, modular, auditable PPTX files containing a complete SVG. Img2pptx is an agent skill from Lancelot-Xie/img2pptx. Reconstruct raster reference images as one-slide editable, modular, auditable PPTX files containing a complete SVG.

When should I use Img2pptx?

Img2pptx fits situations like: the user asks to convert; scientific figure; architecture figure; workflow image into an editable PowerPoint slide.

How do I install Img2pptx in Claude Code?

Run `npx skills add Lancelot-Xie/img2pptx --skill img2pptx -a claude-code`. Or copy the skill folder (skills/img2pptx in Lancelot-Xie/img2pptx) into .claude/skills/img2pptx in your project. Claude Code loads it when a task matches its description.

How do I install Img2pptx in Codex?

Run `npx skills add Lancelot-Xie/img2pptx --skill img2pptx -a codex`. Or copy the skill folder (skills/img2pptx in Lancelot-Xie/img2pptx) into .agents/skills/img2pptx in your project. Codex loads it when a task matches its description.

Can I use Img2pptx 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 Lancelot-Xie/img2pptx --skill img2pptx -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/img2pptx, .gemini/skills/img2pptx, .github/skills/img2pptx and .opencode/skills/img2pptx in your project.

What does Img2pptx need to run?

SKILL.md names no scripts, command-line tools or credentials: Img2pptx is instructions for the agent only.

Does Img2pptx 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 Img2pptx 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. Review the folder before installing.

What licence does Img2pptx use?

Img2pptx 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 Img2pptx use?

About 5.9k tokens (SKILL.md is roughly 24k 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 3.5k tokens, read only when the agent opens those files.

What are the alternatives to Img2pptx?

Skills that share tags, products or a category with Img2pptx: Ppt Visual Replica (ZhiweiWei-NAMI/PPT-Visual-Replica, 135 stars), PPTX Generator (coleam00/ai-transformation-workshop, 147 stars), Linkedin Carousel Generator (dmccreary/ibook-skills, 105 stars) and Create Presentation (JetBrains/youtrackdb, 439 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Img2pptx?

Lancelot-Xie (a GitHub user) maintains it in Lancelot-Xie/img2pptx, which has 163 GitHub stars. The repository was last updated on August 13, 2026.

Source: Lancelot-Xie/img2pptx on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.