SKILLEMALL.ai

BC plug-bundle-alephnet-node

整合4个互补skill的营销组合包,覆盖Security等领域。组合内各skill协同工作,提供从数据输入到结果输出的端到端处理能力。针对安全审计手动覆盖不足、alephnet-node: 存在门槛高问题 (复杂)等痛点提供解决方案。包含4个经质量审核的skill,整体评分81.5分。以alephnet-node为核心,搭配互补skill形成完整工作流。

ClawHub Hermes author: 天轰穿 v1.0.1 MIT-0 3 files body ≈ 2 143 tokens Open the sourceclawhub.ai analyzed 2 d ago

整合4个互补skill的营销组合包,覆盖Security等领域。组合内各skill协同工作,提供从数据输入到结果输出的端到端处理能力。针对安全审计手动覆盖不足、alephnet-node: 存在门槛高问题…

As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions

IntegrationSecuritytype and topics are labelled automatically from the skill text
JSON
Technical rating
B
85/100
safety, quality, tests
Safety 60%
100
Quality 40%
62
Run on models
none yet
Process rating
C
53/100
Has gaps
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.
  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 · 0

✓ No critical or high findings

Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-long-hermes description is 178 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
  • note frontmatter-key unknown frontmatter key "slug"
  • note frontmatter-key unknown frontmatter key "displayName"
  • note frontmatter-key unknown frontmatter key "summary"
  • note frontmatter-key unknown frontmatter key "edition"
  • note frontmatter-key unknown frontmatter key "type"
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "bundle_slug"
  • note frontmatter-key unknown frontmatter key "members"
  • note frontmatter-key unknown frontmatter key "overall_score"
  • note frontmatter-key unknown frontmatter key "suggested_price"
  • note frontmatter-key unknown frontmatter key "pricing_tier"

Process rating: all ten parameters 53/100

  • 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
  • 100Tools and files. Tools declared in frontmatter
  • 100Steps. 80 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2143 tokens
  • 100Running it twice. No mutating operations
  • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
  • low 17 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
  • -2localhost URLs: will not work for another user
  • +2Single-language instructions
  • +3Description length 178: enough signal without eating the budget
  • +4Structure: 42 headings
  • +3Step-by-step instructions: 80 items
  • +4Has examples (2 code blocks)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 62.

External checks

ClawHub: suspicious
This security bundle is not clearly malicious, but it asks for broad read/write/command/API capabilities while leaving important scope and data-flow details unclear.
LLM: suspicious (medium) · 14 Aug 2026