SKILLEMALL.ai

AD newmedia-operations

全链路新媒体运营技能,覆盖从行业分析→竞品分析→账号养号→爆款内容创作→互动钩子设计的完整运营闭环。结合 opencli(浏览器直操控)、ima知识库、联网搜索、违禁词检测等能力,适用于抖音、视频号、小红书三大平台的品牌账号运营。 触发场景: - 用户说"帮我做新媒体运营方案" - 用户说"分析竞品账号" - 用户说"帮我养号" / "账号冷启动" - 用户说"帮我写爆款内容" / "二次创作" - 用户说"设计互动钩子" / "提升评论互动" - 用户说"做行业分析报告" - 用户说"监控对标账号" - 用户提供了品牌/产品 PPT,要求制定内容运营策略

ClawHub Agent Skills author: swcxy12315 v1.0.2 MIT-0 27 files body ≈ 1 812 tokens Open the sourceclawhub.ai analyzed 3 d ago

As a process D 46/100 · Unfinished process — 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
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
78
Run on models
none yet
Process rating
D
46/100
Unfinished process
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: 27. 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 46/100

  • 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
  • 60Tools and files. Uses tools (web, python) that frontmatter does not declare
  • 100Steps. 17 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1812 tokens
  • 100Running it twice. No mutating operations
  • low 11 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

  • +4Description does not say when NOT to use the skill (false activations)
  • +3Output format is not stated: the model decides each time
  • -34 of 15 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +5Description quotes 7 example trigger phrases
  • +3Description length 282: enough signal without eating the budget
  • +4Structure: 32 headings
  • +3Step-by-step instructions: 17 items
  • +4Has examples (22 code blocks)
  • +4Reference files are cited in the instructions (7 of 7)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 78.

External checks

ClawHub: suspicious
This social-media operations skill is mostly coherent, but it needs Review because it can operate real logged-in accounts, publish content, scrape or store business data, and generate misleading mock analytics without enough guardrails.
LLM: suspicious (high) · VirusTotal: · 29 May 2026