CD infographic
Generate modern operator-style social-media infographics (Twitter, LinkedIn, Instagram) using OpenAI gpt-image-2. Use this skill whenever the user wants to make an infographic, design a Twitter or LinkedIn visual, draft a cheat sheet, create a comparison graphic, build a branded image post, ship a content carousel, or produce a recurring weekly visual series. The skill owns the full pipeline: idea selection, layout choice, asset enrichment via Google favicons, copywriting refinement through targeted questions, and final rendering via the OpenAI images.edit endpoint with reference logos and avatar. Trigger on: "make an infographic", "design a Twitter visual", "draft a cheat sheet", "create a social graphic", "branded image post", "comparison graphic", "before/after visual", "ranked list image", "process flow infographic", "hero chart for tweet", "framework graphic", "carousel post", "weekly social series", "LinkedIn carousel", "Instagram graphic", "twitter image", "social card". Also trigger when a user asks to render any kind of designed image with text + structured layout for social distribution, even if they don't say "infographic" specifically — for instance "I want to share these 5 lessons as a visual" or "turn this comparison into a graphic." This skill is designed to avoid the generic AI-image look and produce graphics that read as intentional, branded, and on-trend for product/founder/operator content.
Generate modern operator-style social-media infographics (Twitter, LinkedIn, Instagram) using OpenAI gpt-image-2.
As a process D 49/100 · Unfinished process — References files that are not bundled: assets/avatar.png
How to improve
- Shorten the description to 1024 characters.
- The text references files that are not there: add them or drop the references.
- 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: 6. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1433 chars, limit 1024 - warning
missing-refreference to a missing file: assets/avatar.png
Process rating: all ten parameters 49/100
- 0Tools and files. 1 referenced file(s) missing: assets/avatar.png
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 40Consistency. Frontmatter name (infographic) differs from the folder (infographic-creator)
- 70When it triggers. States when to use, but not when not to
- 100Steps. 56 steps
- 100Failures and branches. 3 branches, has a failure section
- 100Execution cost. Instruction body is 2861 tokens
- 100Running it twice. Mutating operations check current state
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 10 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (3 tags): a typed call is more reliable
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1432: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 20 example trigger phrases
- +4Structure: 16 headings
- +3Step-by-step instructions: 56 items
- +4Has examples (4 code blocks)
- +4Reference files are cited in the instructions (2 of 2)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.