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CD vibecoding-deployment-auditor

免费 AI 网站一键上线助手（内部标识：vibecoding-deployment-auditor）：适合国内用户与零基础小白，无需 Git、服务器、域名或复杂部署配置；面向 VibeCoding 生成的纯静态网站，适用于官方 Sites/ChatGPT Sites 上线不成功或不适用时，通过私有 ZIP 链路完成上线并验证公开 HTTPS 地址。支持 H5 小游戏、个人作品集、企业官网、活动落地页、数据可视化及浏览器直连公开 HTTPS API 的前端工具；最终产物必须可本地构建为含 index.html、可由 CDN/Nginx 直接提供的静态目录，不适用于需要自建后端、数据库、服务器运行时或远端安装/启动依赖的项目。

ClawHub Hermes author: kyris wu v2.3.21 MIT-0 15 files · 1 script body ≈ 2 789 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

免费 AI 网站一键上线助手（内部标识：vibecoding-deployment-auditor）：适合国内用户与零基础小白，无需 Git、服务器、域名或复杂部署配置；面向 VibeCoding 生成的纯静态网站，适用于官方 Sites/ChatGPT Sites 上线不成功或不适用时，通过私有 ZIP…

As a process D 45/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerGitHubDockerCloudflareInfrastructureSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Hermes Agent
JSON
Technical rating
C
88/100
safety, quality, tests
Safety 60%
98
Quality 40%
74
Run on models
none yet
Process rating
D
45/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Progress reporting w 2
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.
  2. For Hermes the description must be one sentence under 60 characters; move the conditions to a "When to Use" section.
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
  • low Secrets in code secret-high-entropy-token templates/deployment-dossier.v1.json:72
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "cont…ves": false
    quoted
  • low Secrets in code secret-high-entropy-token templates/static-artifact-dossier.v1.json:61
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "cont…ves": false
    quoted

Files scanned: 15. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 315 chars; the Hermes authoring standard requires ≤ 60 (one sentence, ending with a period)
  • warning description-no-when neither description nor a "## When to Use" section says when to use the skill

Process rating: all ten parameters 45/100

  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Progress reporting. Says nothing while it works
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 24 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, web, git, node) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 83 steps
  • 100Execution cost. Instruction body is 2789 tokens
  • low 12 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (4 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

  • +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
  • +2Single-language instructions
  • +3Description length 315: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 83 items
  • +4Has examples (14 code blocks)
  • +4Reference files are cited in the instructions (5 of 5)
  • +3All 1 scripts are documented
  • +1License stated

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

External checks

ClawHub: clean
This is a disclosed static-site deployment helper that uploads only vetted build artifacts to a fixed service, though users should review the third-party service and unpinned install commands.
LLM: benign (high) · VirusTotal: · 15 Sept 2026