SKILLEMALL.ai

AD viral-topic-finder-claw

爆款选题发现虾 — 全网热点实时监控与爆款选题挖掘专家。从微博、抖音、知乎、百度、B站等平台抓取热榜数据,智能过滤匹配账号定位,分析爆款内容规律,生成可执行的选题建议,并存入飞书多维表格选题库。 **当以下情况时使用此 Skill**: (1) 用户要求监控热点、找热搜、发现爆款选题 (2) 需要分析同领域高赞内容的选题规律 (3) 需要管理选题库(存档、分类、查询) (4) 需要追踪竞品账号内容策略 (5) 用户提到"热点监控"、"爆款选题"、"热搜"、"选题推荐"、"内容灵感"、"蹭热点"、"流量密码"、"高赞内容"、"竞品分析"、"选题库" (6) 用户说"帮我找找最近有什么热点"、"看看同行发了什么爆款"、"推荐几个选题"

ClawHub Agent Skills author: Ricky v1.0.0 MIT-0 6 files body ≈ 513 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
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
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: 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 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) that frontmatter does not declare
  • 100Steps. 15 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 513 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

  • +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
  • +5Description quotes 3 example trigger phrases
  • +3Description length 320: enough signal without eating the budget
  • +4Structure: 10 headings
  • +3Step-by-step instructions: 15 items
  • +4Has examples (2 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: 84.

External checks

ClawHub: suspicious
This trend-research skill is mostly coherent, but it asks users to use live platform cookies and can write planning data to Feishu without enough credential and data-sharing safeguards.
LLM: suspicious (high) · VirusTotal: · 29 May 2026