SKILLEMALL.ai

BC mingxi-analyzer

明析分析框架体系(明析-analyzer)。当用户需要进行结构化深度分析、系统诊断、矛盾分析、博弈推演、内容质量评估、知识管理或交叉验证时使用。触发词:分析、诊断、推演、复盘、评估、框架分析、系统诊断、矛盾分析、五层推演、OCGS、政策解读、灵感评估、交叉验证。适用于政策分析、市场研究、战略规划、内容评估、组织诊断、复杂问题拆解等场景。此技能将方法论转化为可操作的分析流程,确保每次输出都有信度标注、失效条件和回查计划。

ClawHub Agent Skills author: 122201 v1.0.0 MIT-0 15 files body ≈ 556 tokens Open the sourceclawhub.ai analyzed 34 h ago

明析分析框架体系(明析-analyzer)。当用户需要进行结构化深度分析、系统诊断、矛盾分析、博弈推演、内容质量评估、知识管理或交叉验证时使用。触发词:分析、诊断、推演、复盘、评估、框架分析、系统诊断、矛盾分析、五层推演、OCGS、政策解读、灵感评估、交叉验证。适用于政策分析、市场研究、战略规划、内容评估、组织诊断、…

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

AnalyzerSoftware developmenttype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
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: 15. 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. 4 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 556 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
  • -31 of 2 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 211: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 4 items
  • +4Has examples (4 code blocks)
  • +4Reference files are cited in the instructions (11 of 11)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: clean
This is a Chinese structured-analysis skill with local helper scripts and disclosed local tracking, with no evidence of exfiltration, credential access, destructive actions, or hidden installation behavior.
LLM: benign (high) · VirusTotal: · 9 Jul 2026