SKILLEMALL.ai

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信息技术行业经验萃取Skill - 专注于软件开发、系统架构、DevOps、数据工程等信息技术领域的最佳实践和方法论。涵盖敏捷开发、架构设计、技术领导力等核心能力提升。当用户从事IT开发、要求学习技术行业经验、提炼技术方法论时使用。核心能力:开发方法论、架构模式、技术领导力、效能优化。

ClawHub Agent Skills author: smxtx v1.0.0 MIT-0 3 files body ≈ 3 232 tokens Open the sourceclawhub.ai analyzed 13 h ago

信息技术行业经验萃取Skill - 专注于软件开发、系统架构、DevOps、数据工程等信息技术领域的最佳实践和方法论。涵盖敏捷开发、架构设计、技术领导力等核心能力提升。当用户从事IT开发、要求学习技术行业经验、提炼技术方法论时使用。核心能力:开发方法论、架构模式、技术领导力、效能优化。

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

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")
  • note frontmatter-key unknown frontmatter key "auto_update"
  • note frontmatter-key unknown frontmatter key "update_keywords"
  • note frontmatter-key unknown frontmatter key "update_sources"

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. 22 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3232 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
  • -223 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 143: enough signal without eating the budget
  • +4Structure: 35 headings
  • +3Step-by-step instructions: 22 items
  • +4Has examples (10 code blocks)

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

External checks

ClawHub: clean
This is a Chinese-language informational skill for IT best practices, with no executable code or suspicious data access behavior found.
LLM: benign (high) · VirusTotal: · 16 Jun 2026