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BF nano-banana-image

图片生成与编辑应用，支持文生图、图生图和多规格模型选择。支持 创建图片任务、查询图片任务。包内含完整操作文档与零依赖客户端（`SKILL.md` + `references/`）。需要自备 api.a7w.cn 的 API Key，注册领 Key 见 https://api.a7w.cn/ 。遇到问题可加技术微信 9872659。

ClawHub Agent Skills author: 0人公司agent v1.0.7 MIT-0 9 files · 1 script body ≈ 226 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

图片生成与编辑应用，支持文生图、图生图和多规格模型选择。支持 创建图片任务、查询图片任务。包内含完整操作文档与零依赖客户端（SKILL.md + references/）。需要自备 api.a7w.cn 的 API Key，注册领 Key 见 https://api.a7w.cn/ 。遇到问题可加技术微信…

As a process F 34/100 · No process to follow — weak spots: steps, result and completion, when it triggers

IntegrationAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
B
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
74
Run on models
none yet
Process rating
F
34/100
No process to follow
Steps w 15
0
Result and completion w 14
0
Inputs and preconditions w 11
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: 9. 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")
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"

Process rating: all ten parameters 34/100

  • 0Steps. Prose only: no discrete steps
  • 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
  • 40Consistency. Frontmatter name (nano-banana-image) differs from the folder (sanjianke-nano-banana-image)
  • 100Tools and files. No external tools needed
  • 100Execution cost. Instruction body is 226 tokens
  • 100Running it twice. No mutating operations

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
  • +4Description does not say when NOT to use the skill (false activations)
  • +3No numbered steps or checklist
  • +3Output format is not stated: the model decides each time
  • +2Single-language instructions
  • +3Description length 166: enough signal without eating the budget
  • +4Structure: 5 headings
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (1 of 4)
  • +3All 1 scripts are documented
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.

External checks

ClawHub: suspicious
The skill appears to be a real a7w image-generation wrapper, but it also ships a broader generic account client that can use your API key to inspect and call other platform plugins.
LLM: suspicious (high) · 25 Sept 2026