SKILLEMALL.ai

BF douyin-data-method

抖音数据查询方法。核心能力:通过MaxHub API系统化查询抖音全域数据(视频、用户、搜索、热榜、星图、指数、直播)。覆盖从意图解析、端点匹配、参数构造、API调用、降级切换到数据格式化输出的全流程。7大查询域、每种查询的参数清单与1个完整实战范本。触发词:抖音数据、抖音查询、抖音分析、douyin API、抖音热榜、抖音搜索、达人分析、星图数据。

ClawHub Agent Skills author: 波动几何 v1.0.0 MIT-0 2 files body ≈ 3 240 tokens Open the sourceclawhub.ai analyzed 32 h ago

抖音数据查询方法。核心能力:通过MaxHub API系统化查询抖音全域数据(视频、用户、搜索、热榜、星图、指数、直播)。覆盖从意图解析、端点匹配、参数构造、API调用、降级切换到数据格式化输出的全流程。7大查询域、每种查询的参数清单与1个完整实战范本。触发词:抖音数据、抖音查询、抖音分析、douyin…

As a process F 38/100 · Will not run — References files that are not bundled: url

IntegrationWriting and documentsMarketingtype and topics are labelled automatically from the skill text
JSON
Technical rating
B
86/100
safety, quality, tests
Safety 60%
100
Quality 40%
64
Run on models
none yet
Process rating
F
38/100
Will not run
References files that are not bundled: url
Tools and files w 18
0
Result and completion w 14
0
Inputs and preconditions w 11
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.
  2. The text references files that are not there: add them or drop the references.
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: 2. 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")
  • warning missing-ref reference to a missing file: url

Process rating: all ten parameters 38/100

Will not run. References files that are not bundled: url
  • 0Tools and files. 1 referenced file(s) missing: url
  • 0Result and completion. Does not say what the result is
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 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
  • 50Failures and branches. 0 branches, has a failure section
  • 100Steps. 89 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3240 tokens
  • low 13 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

  • +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
  • -227 emoji in the instructions: noise for the model
  • +1No license
  • +2Single-language instructions
  • +3Description length 176: enough signal without eating the budget
  • +4Structure: 47 headings
  • +3Step-by-step instructions: 89 items
  • +4Has examples (4 code blocks)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 64.

External checks

ClawHub: clean
This is a documentation-only Douyin data-query skill that uses a third-party API key, with no executable installer, persistence, or hidden file behavior found.
LLM: benign (high) · VirusTotal: · 6 Jun 2026