Baoyu Cover ImageSAFE
Overview
An agent skill published by jimliu.
ae9966d431c4OBSERVED · 2026-10-23Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| codex | mentioned | |
| cursor | mentioned | |
| openclaw | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: baoyu-cover-image
description: Generates article cover images with 5 dimensions (type, palette, rendering, text, mood) combining 11 color palettes and 7 rendering styles. Supports cinematic (2.35:1), widescreen (16:9), and square (1:1) aspects. Use when user asks to "generate cover image", "create article cover", or "make cover".
version: 1.117.5
metadata:
openclaw:
homepage: https://github.com/JimLiu/baoyu-skills#baoyu-cover-image
---
# Cover Image Generator
Generate elegant cover images for articles with 5-dimensional customization.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent.
2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Image Generation Tools
When this skill needs to render an image, resolve the backend in this order:
1. **Current-request override** — if the user names a specific backend in the current message, use it.
2. **Saved preference** — if `EXTEND.md` sets `preferred_image_backend` to a backend available right now, use it.
3. **Auto-select** (when the preference is `auto`, unset, or the pinned backend isn't available):
- **Codex (`imagegen`)** — first, inspect your available-skills / tool inventory. If a skill named `imagegen` is listed, you are running inside Codex and MUST use it: invoke via the `Skill` tool with `skill: "imagegen"`, passing the saved prompt file's content (plus output path and aspect ratio per Codex `imagegen`'s own args). Codex `imagegen` is the official raster backend in that runtime and outranks any non-native skill (e.g., `baoyu-image-gen`) unless the user has explicitly pinned a different `preferred_image_backend`.
- **Codex via `codex exec` (`codex-imagegen`)** — if the current runtime exposes no native `imagegen` skill but the `codex` CLI is on `PATH` with an active `codex login`, route through `baoyu-image-gen --provider codex-cli` (preferred), or — if baoyu-image-gen is unavailable — invoke the bundled wrapper directly. Details, parameters, and the runtime-discovery procedure live in [references/codex-imagegen.md](references/codex-imagegen.md) — load that file only when this branch is selected.
- **Cursor (`GenerateImage`)** — if the runtime exposes a native `GenerateImage` tool, you are running inside Cursor and it outranks any non-native skill the same way Codex `imagegen` does. Two hard caveats: (a) it has no aspect-ratio parameter — state the target aspect ratio / dimensions explicitly in the prompt text passed as `description`; (b) it does not accept an output directory — it saves to a tool-managed location, so after generation copy/move the file to the skill's expected output path (e.g., `outputs/.../NN-xxx.png`). Reference images go in `reference_image_paths`.
- **Other runtime-native tools** — if the runtime exposes a different native image tool (e.g., Hermes `image_generate`), use it the same way.
- Otherwise, if exactly one non-native backend is installed (e.g., `baoyu-image-gen`), use it.
- Otherwise (multiple non-native backends with no runtime-native tool), ask the user once — batch with any other initial questions.
4. **If none are available**, tell the user and ask how to proceed.
**⛔ Never substitute SVG, HTML, canvas, or other code-based rendering for raster image generation.** Codex `imagegen`'s own description says it should be used "when the output should be a bitmap asset rather than repo-native code or vector." If you cannot resolve a raster backend via step 3, fall through to step 4 and ask the user — do **not** silently emit SVG, write inline `<svg>` markup, or produce HTML/CSS art as a substitute. This applies even if the article/section seems "diagram-like": the consumer skill calling this rule has already decided that a raster image is what it needs.
**⛔ Never repair rendered text by painting over a generated bitmap.** Do not use ImageMagick, Pillow, Canvas, SVG, HTML/CSS, OCR scripts, or any other programmatic overlay to cover, rewrite, erase, stroke, or replace title/subtitle text inside an already generated cover image. If text is wrong or unclear, regenerate from a corrected prompt, switch to a lower-text or no-title variant, or ask the user which imperfect candidate to keep.
Setting `preferred_image_backend: ask` forces the step-3 prompt every run regardless of available backends. Users change the pinned backend via the `## Changing Preferences` section below.
**Prompt file requirement (hard)**: write each image's full, final prompt to a standalone file under `prompts/` (naming: `NN-{type}-[slug].md`) BEFORE invoking any backend. The backend receives the prompt file (or its content); the file is the reproducibility record and lets you switch backends without regenerating prompts.
Concrete tool names (`imagegen`, `GenerateImage`, `image_generate`, `baoyu-image-gen`) above are examples — substitute the local equivalents under the same rule.
## Confirmation Policy
Default behavior: **confirm before generation**.
- Treat explicit skill invocation, a file path, matched keywords/presets, `EXTEND.md` defaults, and any documented auto-selection as **recommendation inputs only**. None of them authorizes skipping confirmation.
- Do **not** start Step 3 or Step 4 until the user confirms the dimensions / aspect / language / backend choices.
- Skip confirmation only when the current request explicitly says to do so, for example: `--quick`, "直接生成", "不用确认", "跳过Trust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (1)
If content involves sensitive or copyrighted figures, create stylistically similar alternatives - DO NOT refuse to generate
Gates applied: no_behavioural_pass.
ae9966d431c4full audit observations/trust-audit/skill/jimliu__baoyu-cover-image.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-23 | ae9966d431c4 | SAFE | B | 89 | first audit |
Questions
Is baoyu-cover-image — jimliu/baoyu-skills safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can baoyu-cover-image — jimliu/baoyu-skills access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does baoyu-cover-image — jimliu/baoyu-skills work with?
Its documentation mentions codex, cursor and openclaw. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (ae9966d431c4), read on 2026-10-23. The repository is watched, and a new audit runs when it changes — this is the first audit.
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