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AB image-to-editable-ppt

Recreate one flat slide image, screenshot, or AI-rendered presentation page as one faithful editable PowerPoint slide. Use for image-to-PPT or screenshot-to-PPT reconstruction where text must be editable, simple containers must be native PowerPoint shapes, and complex visuals should be extracted through iterative layer decomposition. Do not use for text-to-deck authoring, ordinary presentation writing, or image generation.

inclusionAI/ling-cookbook Agent Skills author: inclusionAI 20 files · 10 scripts body ≈ 2 846 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Recreate one flat slide image, screenshot, or AI-rendered presentation page as one faithful editable PowerPoint slide.

As a process B 69/100 · Nearly there — weak spots: result and completion, inputs and preconditions, progress reporting

GeneratorPowerPointSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
B
69/100
Nearly there
Progress reporting w 2
0
Inputs and preconditions w 11
30
Result and completion w 14
40
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 18. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 69/100

    • 0Progress reporting. Says nothing while it works
    • 30Inputs and preconditions. Does not say what the process needs to start
    • 40Result and completion. Does not say what the result is
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (bash, web, python) that frontmatter does not declare
    • 100Steps. 33 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2846 tokens
    • 100Running it twice. Mutating operations check current state

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +3Output format is not stated: the model decides each time
    • -32 of 7 scripts are never mentioned in SKILL.md
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 426: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 33 items
    • +4Has examples (9 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.