SKILLEMALL.ai

AD linkfox-aigc-imagegen

AI生图工具,根据提示词和参考图生成图片。支持多种模型(BANANA/BANANA_2/BANANA_PRO/GPT_2_IMAGE/AIDRAW_EDIT/WAN2_7/SEEDREAM5),可控制分辨率、宽高比、输出数量。用户说"生成图片"、"AI画图"、"AI生图"、"帮我画"、"图片生成"、"image generation"、"generate image"、"画一张图"、"做张图"、"图生图"时触发。

ClawHub Agent Skills author: linkfox-ai v1.2.2 MIT-0 7 files body ≈ 879 tokens Open the sourceclawhub.ai analyzed 2 d ago

AI生图工具,根据提示词和参考图生成图片。支持多种模型(BANANA/BANANA2/BANANAPRO/GPT2IMAGE/AIDRAWEDIT/WAN27/SEEDREAM5),可控制分辨率、宽高比、输出数量。用户说"生成图片"、"AI画图"、"AI生图"、"帮我画"、"图片生成"、"image…

As a process D 46/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

GeneratorAI and agentstype and topics are labelled automatically from the skill text
JSON
Technical rating
A
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
46/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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: 0. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 46/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 100Steps. 31 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 879 tokens
  • 100Running it twice. No mutating operations
  • low 10 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (9 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)
  • +3Output format is not stated: the model decides each time
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 2 example trigger phrases
  • +3Description length 208: enough signal without eating the budget
  • +4Structure: 13 headings
  • +3Step-by-step instructions: 31 items
  • +4Has examples (3 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
The skill can generate images as advertised, but it also handles login, API-token creation, and payment orders with limited scoping and confirmation controls.
LLM: suspicious (high) · 14 Aug 2026