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腾讯云智能顾问架构风险巡检分析报告生成工具。用于分析用户在腾讯云智能顾问产品下的架构图风险巡检情况，从API拉取数据并生成移动端友好的HTML可视化报告，最终将HTML转换为PNG图片输出。当用户提到智能顾问架构巡检、风险分析、巡检报告、架构图风险、腾讯云巡检等关键词时或对当前报告内容修改时，请务必使用此插件。

LeoYeAI/openclaw-master-skills Claude Code author: LeoYeAI MIT 11 files body ≈ 1 670 tokens Open the sourcegithub.com↗ analyzed 2 d ago

腾讯云智能顾问架构风险巡检分析报告生成工具。用于分析用户在腾讯云智能顾问产品下的架构图风险巡检情况，从API拉取数据并生成移动端友好的HTML可视化报告，最终将HTML转换为PNG图片输出。当用户提到智能顾问架构巡检、风险分析、巡检报告、架构图风险、腾讯云巡检等关键词时或对当前报告内容修改时，请务必使用此插件。

As a process F 35/100 · Will not run — References files that are not bundled: 免密登录URL, scripts/login_url.py

ProcedureSoftware developmentData and analyticsWriting and documentstype 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
83/100
safety, quality, tests
Safety 60%
94
Quality 40%
66
Run on models
none yet
Process rating
F
35/100
Will not run
References files that are not bundled: 免密登录URL, scripts/login_url.py
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
0
the three weakest of ten parameters · all ten
This is a copy of a skill from another catalog; the rating counts the canonical one: tsa-risk (LeoYeAI/openclaw-master-skills)

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Broad scope medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The skill asks for more than the task needs: broad tool access, credential environment variables, binaries. Every extra permission widens the damage from a mistake or a compromise.

For the author

Narrow allowed-tools and the variable list to the minimum; replace binaries with readable sources or scripts.

How to improve

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
  2. The text references files that are not there: add them or drop the references.
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 · 2

✓ No critical or high findings

Medium and low: 2
  • medium Broad scope meta-broad-allowed-tools SKILL.md:1
    Broad tool permissions pre-approved: Bash
    allowed-tools: Bash Read Grep Write
  • low Secrets in code secret-high-entropy-token scripts/generate_report_default.py:714
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    product_top_names = {"Top1…ure", "当前架构图产品TOP15风险", "产品风险TOP", "产品TOP15风险", "当前架构图覆盖产品风险 Top15", "当前架构图覆盖产品风险 TOP15"}
    quoted

Files scanned: 11. 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")
  • warning missing-ref reference to a missing file: 免密登录URL
  • warning missing-ref reference to a missing file: scripts/login_url.py

Process rating: all ten parameters 35/100

Will not run. References files that are not bundled: 免密登录URL, scripts/login_url.py
  • 0Tools and files. 2 referenced file(s) missing: 免密登录URL, scripts/login_url.py
  • 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
  • 100Steps. 44 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1670 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)
  • +3Output format is not stated: the model decides each time
  • +1No license
  • +2Single-language instructions
  • +3Description length 156: enough signal without eating the budget
  • +4Structure: 26 headings
  • +3Step-by-step instructions: 44 items
  • +4Has examples (11 code blocks)
  • +3All 3 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 66.