← All Skills
Enhanced · live dataTikTok Agent

TikTok Data Skill

The TikTok Data Skill is the source-sliced data guide a Platform Agent owns: it names the concrete `tiktok/...` operations, response shapes, and gotchas for reading public TikTok data through UnifAPI MCP, so any creator or trend research (shortlisting, audience-fit, demand-radar, local-buzz) runs from one deterministic workflow. Read-only — it never posts.

Agent-native

Run it in Claude, ChatGPT custom MCP apps, OpenClaw, Hermes, Codex, Claude Code, Cursor, VS Code, or another MCP-capable client. No dedicated GUI flow and no separate LLM API key.

Backed by live public data

Every step is grounded in live public-data records UnifAPI returns, so the output cites what is actually ranking, posting, or being said — not a generic best-practice list.

Composable & open source

Skills cross-reference each other and live in a public, MIT-style repo. Read the full SKILL.md on GitHub, fork it, or run it as-is inside your agent.

Run prompt

Paste this into Codex or Claude Code

The prompt is intentionally editable. Replace the handles, market, budget, and campaign goal, then let the agent call UnifAPI MCP when it needs live public data.

Using the TikTok Data Skill, research creators for a skincare niche: search users and videos for the topic, resolve the strongest handles to ids, read their follower and video engagement, and surface rising hashtags. Return a cited brief. Read-only.
How the skill works

The full skill, rendered from its SKILL.md

The deterministic read path for public TikTok data through UnifAPI. This is a Data Skill: it does not run a marketing job on its own — it names the concrete tiktok/... operations, response shapes, and gotchas so any creator- or trend-first workflow (shortlisting, audience-fit, demand radar, local buzz) reads from one known recipe instead of rediscovering the surface each time.

Read-only — eyes, not hands. It researches public TikTok data and returns cited records; it never posts, comments, or follows, and UnifAPI never holds TikTok credentials.

Use the unifapi skill for live evidence

Connect once through the shared unifapi skill (OAuth MCP), then call the operations below. TikTok users and videos are keyed by numeric id — resolve a @handle or a video URL to its id first (see Gotchas). Keep any billing metadata so the output can state record cost.

Response contract

Single-entity endpoints return the object in data:

{
  "request_id": "unif_...",
  "data": {},
  "billing": { "records_charged": 1, "balance_remaining": 99 }
}

List endpoints return an array in data plus pagination:

{
  "request_id": "unif_...",
  "data": [],
  "pagination": { "has_more": false, "next_cursor": null },
  "billing": { "records_charged": 1 }
}

When pagination.has_more is true, pass pagination.next_cursor as the next request's cursor (limit sets page size). Always preserve billing.

Core operations

NeedOperation
Resolve handle → idtiktok/users/resolve (?username=...)
Resolve video URL → idtiktok/videos/resolve (?url=...)
Search videos / userstiktok/search/videos · tiktok/search/users (?q=...)
Search hashtags / mixedtiktok/search/hashtags · tiktok/search (?q=...)
Creator profiletiktok/users/{id}
Creator videostiktok/users/{id}/videos
Followers / following / likestiktok/users/{id}/followers · .../following · .../likes
Video + reactiontiktok/videos/{id} · tiktok/videos/{id}/comments
Hashtag feedtiktok/hashtags/{id} · tiktok/hashtags/{id}/videos
Music feedtiktok/music/{id} · tiktok/music/{id}/videos

Need a field not listed here? Use the unifapi skill's get_operation to read the exact schema before calling — but pick the operation from this table, don't discover blind.

Workflow

The deterministic recipes. Pick the one that matches the job; each names exactly what to call.

  1. Discover by topic. Call tiktok/search/videos?q=..., tiktok/search/users?q=..., or tiktok/search/hashtags?q=... for the niche; use tiktok/search?q=... for a mixed result.
  2. Resolve a creator. Call tiktok/users/resolve?username=... to get the numeric id, then tiktok/users/{id} for follower_count, like_count, and video_count.
  3. Read engagement. Call tiktok/users/{id}/videos; each Video carries view_count, like_count, comment_count, and share_count — compute engagement per video. Page via next_cursor.
  4. Read a video and its reaction. Call tiktok/videos/{id} (resolve a URL with tiktok/videos/resolve?url=... first), then tiktok/videos/{id}/comments for sentiment.
  5. Track trends. Call tiktok/hashtags/{id} for video_count/view_count and tiktok/hashtags/{id}/videos (or tiktok/music/{id}/videos) for what's spreading on a tag or sound.
  6. Map a network. Call tiktok/users/{id}/followers, .../following, or .../likes for reach and affinity work.
  7. Cite everything. Every figure ties back to the video or profile it came from; report billing.records_charged (or estimate when billing metadata is absent).

Shape notes

  • Userusername, display_name, follower_count, following_count, like_count, video_count, is_verified, is_private, region.
  • Videovideo_description, view_count, like_count, comment_count, share_count, duration, author, music, hashtags, create_time.
  • Hashtagname, video_count, view_count, is_commerce.
  • Musictitle, author, is_original.

Gotchas

  • TikTok users and videos are keyed by numeric id. Resolve a @handle with tiktok/users/resolve?username=... and a video URL with tiktok/videos/resolve?url=... before any tiktok/users/{id}/... or tiktok/videos/{id}/... call.
  • tiktok/videos/batch is a POST (ids in the body), not a GET — use it to hydrate many video ids at once.
  • A private creator (is_private) limits what you can read — surface it.
  • A low balance can silently truncate list pages: check billing.truncated_due_to_balance — when true the page is partial, so top up before trusting any count.

Output

Return the records the calling workflow needs, each cited to its video or profile, plus a one-line cost note (records_charged). When this skill is used directly, a compact creator summary is the default:

**@handle** — {followers} followers, {videos} videos. Recent videos: avg {views} views / {likes} likes / {comments} comments. Rising tags: {#hashtags}. Evidence: {video URLs}. Records: ~{N}.
  • creator-shortlist, audience-fit-check (Influencer Marketing) — shortlist and vet TikTok creators on top of this read path.
  • social-listening-brief (Social Listening), treatment-demand-radar, menu-demand-radar, restaurant-local-buzz (verticals) — trend and demand work that reads TikTok first.
  • unifapi — the shared data skill: connect MCP and look up exact schemas with get_operation.

Source: tiktok/SKILL.md on GitHub — open a PR there to improve it.

Public-data tools

The live APIs this skill calls

Every operation the skill names is one of these UnifAPI platforms — still visible and callable for product code, debugging, and custom agent flows.

  • The concrete `tiktok/...` operations for each common creator/trend read job
  • Response-contract and shape notes for users, videos, hashtags, music
  • Deterministic recipes: resolve creators, read engagement, discover trends
  • Platform gotchas (resolve username to id first, cursor pagination, billing)