SKILLEMALL.ai

BD vibecoding-deployment-auditor

面向国内 VibeCoding 与零基础用户的一键静态网站发布:将 H5 游戏、个人作品集、企业官网和活动页等 HTML/CSS/JavaScript、Vite/React/Vue 静态构建发布为公开 HTTPS 链接;无需 GitHub、服务器、域名或 Sites。One-click static site publishing for frontend websites. 仅适用于纯静态站点,不适用于后端、数据库、SSR、服务端运行时或远端安装依赖。

ClawHub Hermes author: kyris wu v2.3.18 MIT-0 9 files body ≈ 2 029 tokens Open the sourceclawhub.ai analyzed 2 d ago

面向国内 VibeCoding 与零基础用户的一键静态网站发布:将 H5 游戏、个人作品集、企业官网和活动页等 HTML/CSS/JavaScript、Vite/React/Vue 静态构建发布为公开 HTTPS 链接;无需 GitHub、服务器、域名或 Sites。One-click static site…

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

AnalyzerGitHubDockerCloudflareSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
98
Quality 40%
70
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:71
    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:60
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    "cont…ves": false
    quoted

Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 229 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. 25 mutating operations with no state check
  • 50Failures and branches. 0 branches, has a failure section
  • 60Tools and files. Uses tools (bash, git, node) that frontmatter does not declare
  • 60Consistency. The Hermes dialect needs category and tags
  • 100Steps. 72 steps
  • 100Execution cost. Instruction body is 2029 tokens
  • low 13 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
  • +2Single-language instructions
  • +3Description length 229: enough signal without eating the budget
  • +4Structure: 17 headings
  • +3Step-by-step instructions: 72 items
  • +4Has examples (12 code blocks)
  • +3All 1 scripts are documented
  • +1License stated

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

External checks

ClawHub: clean
The skill is a disclosed static-site publishing workflow that uploads a vetted static ZIP to a fixed deployment service only when the user asks to publish.
LLM: benign (high) · VirusTotal: · 18 Jul 2026