AC hot-topic-content-maker
Turn a trending topic into a post you can publish today. Bring the hot topic, moment, or seasonal peg — or have it read the public trending boards on Douyin, TikTok, and X, or name a topic and have it search what people are actually posting about it on Xiaohongshu and Douyin, and pick the ones worth a look. This trending content workflow finds the angles that genuinely connect the topic to your brand or account, judges which one is worth your name on it, then builds the chosen angle into a finished post: cover wording and a rendered cover image, the caption, the hashtags, a beat-by-beat plan for a short cut, and the narrated vertical clip itself. Use it for trendjacking, newsjacking, trend-riding, trend discovery, seasonal and holiday campaigns, festival and shopping-event content, moment marketing, and getting a same-day social post or short video out of a topic while it is still moving. The finished post fits Douyin, Xiaohongshu, WeChat Channels, TikTok, Reels, and Shorts.
Turn a trending topic into a post you can publish today.
As a process C 60/100 · Has gaps — weak spots: result and completion, running it twice, progress reporting
How to improve
- 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: 19. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 60/100
- 0Result and completion. Does not say what the result is
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 7 mutating operations with no state check
- 50When it triggers. No condition that starts the skill
- 50Failures and branches. 0 branches, has a failure section
- 60Tools and files. Uses tools (bash) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 31 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3837 tokens
- low 12 top-level sections: this looks like several domains in one skill
- low The skill ranks results itself: that belongs to the system behind the tool, not the model
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 989: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- -32 of 3 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +4Structure: 16 headings
- +3Step-by-step instructions: 31 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (13 of 13)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 82.