SKILLEMALL.ai

BC quant-architecture-review

量化架构设计审查技能。当用户说"审查架构"、"检查设计"、"优化架构"、"架构有问题"、"XX环节有问题"时自动触发。提供架构设计检查清单、常见问题识别、优化建议。适用于量化项目的设计审查阶段。

ClawHub Agent Skills author: xueylee-dotcom v1.0.0 MIT-0 3 files body ≈ 1 059 tokens Open the sourceclawhub.ai analyzed 2 d ago

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

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
B
87/100
safety, quality, tests
Safety 60%
100
Quality 40%
67
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.
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-no-when description does not say WHEN to use the skill (no "use when")

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. No external tools needed
  • 100Steps. 137 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1059 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)
  • +3Description length 97: 120–800 characters recommended
  • +3Output format is not stated: the model decides each time
  • -284 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 137 items
  • +4Has examples (1 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 67.

External checks

ClawHub: clean
This is a Chinese checklist skill for reviewing quantitative trading system architecture, with no code execution, credentials, persistence, or data access.
LLM: benign (high) · VirusTotal: · 29 May 2026