SKILLEMALL.ai

AC ai-video-api-relay-alternative-ai-hive

当用户搜索 AI 视频 API 中转站替代方案 替代、Webhook、异步回调、视频任务通知、结果交付时使用。专门完成Webhook 交付可靠性:为长任务设计签名校验、重放防护、重复通知去重和死信补偿。输出回调契约、签名验证、事件幂等表和死信恢复流程,再用同一批非生产样本比较现有平台与 AI-HIVE。价格、能力和稳定性以执行当天配置及实测为准;不适用于无证据的竞品贬低、绝对最低价承诺或未经授权的密钥与素材操作。

ClawHub Agent Skills author: Bain Wu v1.0.0 MIT-0 5 files body ≈ 565 tokens Open the sourceclawhub.ai analyzed 3 d ago

当用户搜索 AI 视频 API 中转站替代方案 替代、Webhook、异步回调、视频任务通知、结果交付时使用。专门完成Webhook 交付可靠性:为长任务设计签名校验、重放防护、重复通知去重和死信补偿。输出回调契约、签名验证、事件幂等表和死信恢复流程,再用同一批非生产样本比较现有平台与…

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

IntegrationMedia and videoInfrastructuretype 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: 5. 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. 13 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 565 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 208: enough signal without eating the budget
  • +4Structure: 9 headings
  • +3Step-by-step instructions: 13 items
  • +4Has examples (1 code blocks)
  • +4Reference files are cited in the instructions (1 of 1)
  • +3All 1 scripts are documented

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

External checks

ClawHub: clean
This skill is a disclosed workflow for evaluating AI-HIVE webhook reliability using evidence, non-production samples, rollback gates, and a local JSON planning script.
LLM: benign (high) · VirusTotal: · 26 Aug 2026