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BD xianyu-auto-fulfillment

闲鱼自动发货框架 - 一个可扩展的闲鱼虚拟商品自动化发货系统。提供核心的付款检测逻辑，发货流程完全可自定义。 - 核心功能：自动检测买家付款（系统卡片识别） - 可扩展：支持任意发货方式（秘钥、链接、图片、文件、自定义API等） - 灵活配置：通过脚本或配置文件自定义发货逻辑 - 内置模板：提供多种常见发货场景的模板 - 使用 agent-browser 进行网页自动化

modbender/skill-library-mcp Agent Skills author: modbender MIT 21 files · 16 scripts body ≈ 4 705 tokens Open the sourcegithub.com↗ analyzed 2 d ago

闲鱼自动发货框架 - 一个可扩展的闲鱼虚拟商品自动化发货系统。提供核心的付款检测逻辑，发货流程完全可自定义。 - 核心功能：自动检测买家付款（系统卡片识别） - 可扩展：支持任意发货方式（秘钥、链接、图片、文件、自定义API等） - 灵活配置：通过脚本或配置文件自定义发货逻辑 -…

As a process D 42/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

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
87/100
safety, quality, tests
Safety 60%
99
Quality 40%
69
Run on models
none yet
Process rating
D
42/100
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 · 1

✓ No critical or high findings

Medium and low: 1
  • low Exfiltration exfil-webhook-url SKILL.md:796
    Webhook / callback URL commonly used for exfiltration (verify the destination) (placeholder value)
    curl -s -X POST "https://api.telegram.org/botYOUR_BOT_TOKEN/sendMessage" \
    placeholder

Files scanned: 21. 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 "read_when"

Process rating: all ten parameters 42/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 40Consistency. Frontmatter name (xianyu-auto-fulfillment) differs from the folder (xianyu-auto-saler)
  • 60Tools and files. Uses tools (bash) that frontmatter does not declare
  • 70Execution cost. Instruction body is 4705 tokens
  • 100Steps. 42 steps
  • 100Running it twice. No mutating operations
  • 100Progress reporting. Reports progress
  • low 14 top-level sections: this looks like several domains in one skill

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)
  • +3Output format is not stated: the model decides each time
  • -216 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 186: enough signal without eating the budget
  • +4Structure: 47 headings
  • +3Step-by-step instructions: 42 items
  • +4Has examples (31 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.