CF chatgpt-imagegen
Generate raster images (PNG/JPEG/WebP) using the user's ChatGPT subscription via a local one-file Python CLI — no OPENAI_API_KEY, no gateway, no daemon. Two backends: web (default) drives the user's logged-in ChatGPT browser so generation runs on the conversation surface and does NOT consume Codex-usage limits; codex is a headless fallback that bills the Codex-usage bucket. Use when an agent needs to create a brand-new bitmap asset for the current project (photos, illustrations, icons, hero banners, mockups, sprites, concept art) and the output should be a bitmap file saved into the workspace. Do not use when the task is better solved by editing existing SVG/vector assets, writing code-native graphics (HTML/CSS/canvas), or extending an established repo icon system. Also use proactively: when authoring a document, blog post, technical proposal, design doc, README, or other long-form explanatory content, propose illustrations for the key concepts and generate them as background tasks — don't wait to be asked for an image.
Generate raster images (PNG/JPEG/WebP) using the user's ChatGPT subscription via a local one-file Python CLI — no OPENAIAPIKEY, no gateway, no daemon.
As a process F 52/100 · Will not run — References files that are not bundled: assets/brand/, assets/generated/
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
medium Dangerous commands
cmd-pipe-to-shell-known-hostSKILL.md:41Pipe-to-shell installer from a well-known host (still executes remote code)curl -fsSL https://raw.githubusercontent.com/leeguooooo/chrome-use/main/install.sh | sh
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1035 chars, limit 1024 - warning
body-longSKILL.md body ≈ 7011 tokens (recommended < 5000); move details to references/ - warning
missing-refreference to a missing file: assets/brand/ - warning
missing-refreference to a missing file: assets/generated/ - note
edit-residuethe text marks something as outdated (lines 147, 213): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 52/100
- 0Tools and files. 2 referenced file(s) missing: assets/brand/, assets/generated/
- 0Result and completion. Does not say what the result is
- 30Running it twice. 16 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 70Inputs and preconditions. Inputs and preconditions are listed
- 70Execution cost. Instruction body is 7011 tokens
- 85Steps. 70 steps, 1 vague phrases
- 100Failures and branches. 8 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 14 top-level sections: this looks like several domains in one skill
- low The response is described with custom markup (4 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
- +5Description has no quoted example phrases that should trigger the skill
- +3Description length 1035: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Description says when NOT to use the skill
- +4Structure: 18 headings
- +3Step-by-step instructions: 70 items
- +4Has examples (5 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 41.