trend-research

trend-research is a skill for Claude Code from TikHub/tikhub-plugin. It costs 71 tokens per session (491 once invoked), scanned A, original, MIT.

A research helper for finding popular videos, hashtags, sounds, creators, and ranking lists on TikTok, Douyin, Twitter/X, and other platforms.

In plain words
What is it for?
Use it to make trend reports, compare platform trends, find rising creators, or investigate a popular hashtag or sound.
Why use it?
It saves you from checking several social networks separately when you need to know what is gaining attention. Results can be narrowed by region, topic, and time period.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the tikhub-plugin plugin — 19 skills, 7 MCP servers shipped together

Good fit Use it to make trend reports, compare platform trends, find rising creators, or investigate a popular hashtag or sound.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tikhub/tikhub-plugin/trend-research
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add TikHub/tikhub-plugin --skill trend-research
Clone the repo
git clone --depth 1 https://github.com/TikHub/tikhub-plugin

Made for: Claude Code.

Or install tikhub-plugin, the plugin that ships this one along with the rest of its 19 skills, 7 MCP servers.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for trend-research

README.md
[![agentmods](https://agentmods.dev/badge/skills/tikhub/tikhub-plugin/trend-research.svg)](https://agentmods.dev/skills/tikhub/tikhub-plugin/trend-research)
Your own site
<a href="https://agentmods.dev/skills/tikhub/tikhub-plugin/trend-research"><img src="https://agentmods.dev/badge/skills/tikhub/tikhub-plugin/trend-research.svg" alt="Measured on agentmods" height="20"></a>
Per session 71 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 491 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00071 $0.00491
Opus 5 $0.00036 $0.00246
Sonnet 5 $0.00014 $0.00098
Haiku 4.5 $0.00007 $0.00049

Measured 8d ago against content hash 627fcffb54b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

trend-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/trend-research/SKILL.md · 49 lines

What it actually says

Trend Research

Surface trending content, hashtags, sounds, and rankings, optionally scoped to a region or niche.

Setup gate

[ -z "${TIKHUB_API_KEY:-}" ] && echo "Set TIKHUB_API_KEY first (see tikhub-onboarding)."

Sources by platform

Platform What Endpoint
TikTok Popular trends GET /api/v1/tiktok/ads/get_popular_trends (period, country_code)
TikTok Trending hashtags GET /api/v1/tiktok/ads/get_trends_hashtag_list
TikTok Hot sounds GET /api/v1/tiktok/ads/get_sound_rank_list
Twitter/X Trending topics GET /api/v1/twitter/web/fetch_trending (country)

For niche trends, also run keyword/hashtag search on the relevant platform skill. For other platforms' trend sources, use tikhub-find-endpoint "<goal>" --platform <slug>.

Workflow

  1. Clarify scope: platform(s), region/country, niche/keyword, time window.
  2. Pull the relevant trend boards above (one call each).
  3. Normalize into a single ranked list (rank, name, volume/score, example content, platform).
  4. Deliver a trend report; optionally drill into a hot hashtag via hashtag-research.

Cost awareness

Each board is 1 call. A multi-platform report is a handful of calls — cheap. Drilling into many hashtags/posts multiplies calls; warn before deep dives.

Verification gate

  1. Each board returns a non-empty ranked list.
  2. Region/period filters were actually applied (echo them in the report).

Red flags

  • Presenting Ads-API "trends" as organic virality without noting the source.
  • Mixing regions/time windows in one ranked table without labeling them.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 49 lines · 71 tokens per session scan A 627fcffb54b1

Subscribe to this mod's changes

trend-research is a skill published in the GitHub repository TikHub/tikhub-plugin (6 stars, last pushed 2mo ago), licensed MIT. It adds 71 tokens to every session and 491 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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