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.
npx skills add TikHub/tikhub-plugin --skill hashtag-researchgit clone --depth 1 https://github.com/TikHub/tikhub-pluginWrote 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.
[](https://agentmods.dev/skills/tikhub/tikhub-plugin/hashtag-research)<a href="https://agentmods.dev/skills/tikhub/tikhub-plugin/hashtag-research"><img src="https://agentmods.dev/badge/skills/tikhub/tikhub-plugin/hashtag-research/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tikhub/tikhub-plugin/hashtag-research"><img src="https://agentmods.dev/badge/skills/tikhub/tikhub-plugin/hashtag-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00049 | $0.00463 |
| Opus 5 | $0.00024 | $0.00231 |
| Sonnet 5 | $0.00010 | $0.00093 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
hashtag-research scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Hashtag Research
Assess a hashtag/keyword and surface its top content and related tags.
Setup gate
[ -z "${TIKHUB_API_KEY:-}" ] && echo "Set TIKHUB_API_KEY first (see tikhub-onboarding)."
Workflow
- Pick platform(s) and the hashtag/keyword.
- Pull signals + content:
- TikTok:
ads/get_trends_hashtag_detail(hashtag_id) andads/get_trends_hashtag_list; pull videos under a hashtag withapp/v3/fetch_hashtag_video_list(ch_id). - Douyin:
search/fetch_general_search_v2(POST) for hashtag/keyword content. - Instagram:
v2/search_hashtags+v2/fetch_hashtag_posts. - Xiaohongshu:
app_v2/search_notes(keyword). - Discover exact paths:
tikhub-find-endpoint "hashtag" --platform <slug>.
- TikTok:
- Summarize: estimated popularity/volume, top posts (engagement), recent momentum, and a list of related/co-occurring hashtags pulled from the top posts.
- Recommend a tag set for the user's niche.
Cost awareness
Detail/list calls are 1 each; pulling top-posts pages multiplies calls. Cap and warn for deep pulls.
Verification gate
- Hashtag resolved (or clearly report "no data / low volume").
- Top posts are actually tagged with the hashtag.
- Related tags derived from real co-occurrence, not guessed.
Red flags
- Inventing volume numbers — only report what the API returns; otherwise say "not available".
- Recommending banned/irrelevant tags.
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.
- 8d ago First seen · 44 lines · 49 tokens per session scan A 1037075797aa
hashtag-research is a skill published in the GitHub repository TikHub/tikhub-plugin (6 stars, last pushed 2mo ago), licensed MIT. It adds 49 tokens to every session and 463 once invoked, about $0.0002 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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