SKILLEMALL.ai

BD tiktok-video-search

TikTok高赞视频搜索工具。支持关键词获取TikTok实时高赞视频数据,助力创作者发现热门趋势、获取创作灵感。提供3个能力①关键词搜索(可按点赞/相关度排序、发布时间筛选)②博主作品获取,按主页链接或用户名批量获取公开作品列表,支持最新/最热排序 ③视频评论抓取,按视频链接或作品 ID 获取评论内容、评论者与互动数据,输出结构化 JSON(含作者、互动数据、标签、链接)。当用户需要搜TikTok视频、抓博主作品、看TikTok评论、做竞品/对标账号监控、短视频选题调研、评论舆情分析、热点追踪、爆款挖掘时使用。

ClawHub Agent Skills author: why20261 v1.0.0 MIT-0 30 files · 18 scripts body ≈ 2 067 tokens Open the sourceclawhub.ai↗ analyzed 6 d ago

TikTok高赞视频搜索工具。支持关键词获取TikTok实时高赞视频数据,助力创作者发现热门趋势、获取创作灵感。提供3个能力①关键词搜索(可按点赞/相关度排序、发布时间筛选)②博主作品获取,按主页链接或用户名批量获取公开作品列表,支持最新/最热排序 ③视频评论抓取,按视频链接或作品 ID…

As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

ProcedureMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
91/100
safety, quality, tests
Safety 60%
100
Quality 40%
77
Run on models
none yet
Process rating
D
43/100
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: 30. 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 43/100

  • 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
  • 30Running it twice. 1 mutating operations with no state check
  • 60Tools and files. Uses tools (node) that frontmatter does not declare
  • 100Steps. 37 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 2067 tokens

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
  • +2Single-language instructions
  • +3Description length 258: enough signal without eating the budget
  • +4Structure: 20 headings
  • +3Step-by-step instructions: 37 items
  • +4Has examples (2 code blocks)
  • +4Reference files are cited in the instructions (2 of 2)
  • +1License stated

Quality base 70; lint remarks subtract, signals add up to 100. Result: 77.

External checks

ClawHub: clean
This is a coherent read-only TikTok data tool, but it sends query targets and an API token to a third-party service and saves returned public data in local temp logs.
LLM: benign (high) · VirusTotal: · 25 Sept 2026