SKILLEMALL.ai

BC content-pregenerator

内容预生成器,凌晨低谷期(01:00-05:00)为所有租户预生成当天内容,复用content-orchestrator的15条管道执行'生成+质检'(跳过发布),结果缓存到PG content_pre_cache表,发布时直接取已生成内容实现秒级发布。DRR三阶段公平调度确保多租户Jain≥0.8。分层降级:PL-VIDEO→PL-IMAGE→TEXT→E0兜底。触发:预生成/内容预生成/凌晨生成/批量生成内容/pregenerate 不触发:实时发布/内容生成/单条生成/客服回复/数据分析

ClawHub Agent Skills author: 天轰穿 v1.0.0 MIT-0 3 files body ≈ 871 tokens Open the sourceclawhub.ai analyzed 2 d ago

内容预生成器,凌晨低谷期(01:00-05:00)为所有租户预生成当天内容,复用content-orchestrator的15条管道执行'生成+质检'(跳过发布),结果缓存到PG…

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

ProcedureMedia and videotype and topics are labelled automatically from the skill text
JSON
Technical rating
B
89/100
safety, quality, tests
Safety 60%
100
Quality 40%
73
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: 3. 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")
  • note frontmatter-key unknown frontmatter key "tools"
  • note frontmatter-key unknown frontmatter key "dependencies"

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. Tools declared in frontmatter
  • 100Steps. 33 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 871 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 249: enough signal without eating the budget
  • +4Structure: 12 headings
  • +3Step-by-step instructions: 33 items
  • +4Has examples (5 code blocks)
  • +3All 1 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.

External checks

ClawHub: suspicious
The skill mostly does what a content pre-generator would need, but it can broadly change publishing readiness across tenant and system queues in a way the user-facing description does not clearly disclose.
LLM: suspicious (high) · 15 Aug 2026