BB china-social-media-ops
Orchestrate social media operations across China's major platforms (Xiaohongshu, Douyin, WeChat Official Account, Bilibili, Zhihu). Teach AI agents how to plan content calendars, adapt content for each platform's algorithm, schedule posts, track engagement, and manage cross-platform content distribution. Covers: content calendar planning with platform-specific timing, cross-platform content adaptation (one piece → 5 formats), engagement tracking dashboard, trending topic monitoring, and community management workflows. Triggers on: 中国社交媒体运营, china social media operations, 小红书运营, xiaohongshu operations, 抖音运营, douyin operations, 微信公众号运营, wechat official account, B站运营, bilibili operations, 知乎运营, zhihu operations, 跨平台内容分发, cross-platform content distribution, 社交媒体日历, social media calendar, 内容适配, content adaptation, 社交媒体工作流, social media workflow, 中国社媒自动化, china social media automation
Orchestrate social media operations across China's major platforms (Xiaohongshu, Douyin, WeChat Official Account, Bilibili, Zhihu).
As a process B 65/100 · Nearly there — weak spots: inputs and preconditions, failures and branches, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 65/100
- 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
- 30Running it twice. 1 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 70When it triggers. States when to use, but not when not to
- 100Tools and files. No external tools needed
- 100Steps. 39 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1280 tokens
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 10 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)
- +3Description length 892: 120–800 characters recommended
- -225 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +4Structure: 27 headings
- +3Step-by-step instructions: 39 items
- +3Output format is stated explicitly
- +4Has examples (11 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 70.