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BD donguan-interactive-login

动环综合网管（温湿度监控平台）交互式登录工具。自动识别图片验证码(RSA-OAEP-SHA256加密密码)并触发短信下发，用户仅需手动输入手机短信验证码即可完成登录，保存Cookie供脚本/定时任务复用。触发场景：登录动环系统、获取动环Cookie、动环网管2FA登录、刷新动环Session、动环登录验证码、dh login、动环综合网管登录。

ClawHub Agent Skills author: Antarctic-penguin971 v1.0.0 MIT-0 3 files body ≈ 585 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

动环综合网管（温湿度监控平台）交互式登录工具。自动识别图片验证码(RSA-OAEP-SHA256加密密码)并触发短信下发，用户仅需手动输入手机短信验证码即可完成登录，保存Cookie供脚本/定时任务复用。触发场景：登录动环系统、获取动环Cookie、动环网管2FA登录、刷新动环Session、动环登录验证码、dh…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureSoftware 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
89/100
safety, quality, tests
Safety 60%
99
Quality 40%
74
Run on models
none yet
Process rating
D
43/100
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 Secrets in code secret-password-literal SKILL.md:69
    Hard-coded password / key literal (may be an example)
    password='XZ$ua98E#dYO',

Files scanned: 3. 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 "agent_created"

Process rating: all ten parameters 43/100

  • 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
  • 30Running it twice. 3 mutating operations with no state check
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 585 tokens

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
  • +1No license
  • +2Single-language instructions
  • +3Description length 173: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (5 code blocks)
  • +3All 1 scripts are documented

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

External checks

ClawHub: suspicious
This is a disclosed login helper, but it handles passwords and reusable session cookies in ways that could expose them, so users should review it carefully before installing.
LLM: suspicious (high) · 17 Jul 2026