SKILLEMALL.ai

AC content-rewriter-claw

流量重组洗稿虾 — 基于爆款逻辑的深度内容改写专家。保留爆款基因,规避重复风险,快速产出高质量原创内容。 **当以下情况时使用此 Skill**: (1) 需要将爆款内容改写为符合自己账号风格的原创版本 (2) 需要跨平台内容迁移(长文→短视频脚本、视频→图文) (3) 需要基于同一核心观点生成多个不同角度的内容版本 (4) 需要将可能触及平台红线的内容改写为合规版本 (5) 用户提到"改写"、"洗稿"、"内容改编"、"换个角度"、"重新演绎"、"借鉴爆款"、"规避重复"、"原创改写"、"内容衍生"、"合规化"

ClawHub Agent Skills author: Ricky v1.0.0 MIT-0 6 files body ≈ 383 tokens Open the sourceclawhub.ai analyzed 4 d ago

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

ProcedureInfrastructuretype and topics are labelled automatically from the skill text
JSON
Technical rating
A
92/100
safety, quality, tests
Safety 60%
100
Quality 40%
79
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: 6. 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. 35 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 383 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
  • +1No license
  • +2Single-language instructions
  • +3Description length 259: enough signal without eating the budget
  • +4Structure: 11 headings
  • +3Step-by-step instructions: 35 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.

External checks

ClawHub: clean
This is a disclosed text-rewriting skill with copyright-adjacent use risks, but it does not show hidden access, persistence, credential use, networking, or destructive behavior.
LLM: benign (high) · VirusTotal: · 29 May 2026