A read-only TikTok research skill that converts public videos, creator profiles, and comments into structured data for audience insight, trend analysis, and product discovery.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tiktok-user-insight
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install tiktok-user-insight using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is TikTok User Insight and Product Opportunity Analysis?
TikTok User Insight and Product Opportunity Analysis is an Openclaw Skills command skill for collecting and analyzing publicly available TikTok data. It supports keyword search, creator work retrieval, and video comment extraction, returning consistent JSON that can be used for market research, content analysis, influencer discovery, competitor monitoring, social listening, and viral-topic research.
The skill is designed to turn raw TikTok signals into actionable business insight. Teams can identify audience needs, uncover emotional motivations, compare creator activity, detect content patterns, evaluate public sentiment, and translate findings into product or marketing opportunities. It is read-only, does not require TikTok account login, and does not perform publishing, liking, commenting, following, or messaging actions.
TikTok User Insight and Product Opportunity Analysis Use Cases
- Research high-performing TikTok topics, keywords, hashtags, and viral content for editorial or product ideation.
- Discover public creator, influencer, KOL, and competitor content sorted by recency or popularity.
- Analyze video comments to identify recurring opinions, pain points, questions, sentiment, and audience motivations.
- Monitor competitor accounts, publishing cadence, engagement signals, and breakout-content ratios.
- Build influencer shortlists using creator names, average interactions, posting frequency, and content relevance.
- Support cross-border marketing, short-video strategy, social listening, and market-entry research.
- Produce structured datasets for ranking, clustering, comparison, reporting, dashboards, or downstream AI analysis.
- Use Openclaw Skills when the request concerns public TikTok data; route requests for other platforms, private data, or content writing to another appropriate capability.
How TikTok User Insight and Product Opportunity Analysis Works
- Interpret the request and identify whether the user needs keyword search, creator posts, or comments for a specific video.
- Route the request to
search-cli.js,post-cli.js, orcomment-cli.jsbased on the user intent and supplied keyword, profile URL, video URL, or content ID. - Infer supported options such as sorting, time range, and result limit. Search sorting distinguishes relevance or likes, while creator-post sorting distinguishes newest or hottest content.
- Validate the request and execute the Node.js command from the skill root with the
GUAIKEI_API_TOKENenvironment variable. - Read machine-readable JSON exclusively from stdout. Progress messages, banners, errors, and the saved-log location are written to stderr.
- Return a consistent response envelope containing status, error code, message, timestamp, request parameters, runtime metadata, results, and warnings.
- Treat
successas usable data,emptyas a valid request with no matches, anderroras a failed request requiring error-specific handling. - Preserve and report every parameter adjustment in
warnings; do not present fallback values as if the original parameters were used. - Transform the returned records into the user’s requested output, such as a top-content ranking, creator shortlist, comment-theme analysis, sentiment summary, or market-research report.
- Stop immediately for
AUTH_REQUIRED, never invent missing data, and never broaden search conditions without user approval.
TikTok User Insight and Product Opportunity Analysis Setup
Requirements
- Node.js 16.14.0 or newer, compatible with Windows, macOS, and Linux.
- The
nodeexecutable available on the system path. - A valid
GUAIKEI_API_TOKEN, obtained through the Guaikei service atwww.guaikei.com. - Commands executed from the skill root directory.
Configure the token
export GUAIKEI_API_TOKEN="your_token_here"
On Windows PowerShell:
$env:GUAIKEI_API_TOKEN="your_token_here"
Run the primary commands
# Search public TikTok content by keyword
node scripts/tiktok/search-cli.js --keyword "AI" --sort 1 --limit 20
node scripts/tiktok/search-cli.js --keyword "AI model" --time 7 --limit 20
# Retrieve a creator's public posts
node scripts/tiktok/post-cli.js --url "https://www.tiktok.com/@username" --limit 30
node scripts/tiktok/post-cli.js --url "https://www.tiktok.com/@username" --sort 1 --limit 30
# Retrieve comments for a public video
node scripts/tiktok/comment-cli.js --url "https://www.tiktok.com/@username/video/1234567890123456789" --limit 40
Operational notes
Use --sort 0 for default or relevance-oriented search and --sort 1 for the hottest search results. For creator posts, --sort 0 means newest and --sort 1 means hottest. Supported time windows include 1, 7, 30, 90, and 180 days; the default limit is 10 and a single request should generally remain at or below 1000 results. If authentication fails with exit code 3 or AUTH_REQUIRED, configure the token instead of retrying with different parameters.
TikTok User Insight and Product Opportunity Analysis Data Schema & Taxonomy
Command interfaces
| Capability | Entry script | Required input | Primary output |
|---|---|---|---|
| Keyword search | scripts/tiktok/search-cli.js |
--keyword |
Public content, author, engagement counts, tags, and playback URL |
| Creator posts | scripts/tiktok/post-cli.js |
--url or creator identifier |
Public creator posts sorted by newest or hottest |
| Video comments | scripts/tiktok/comment-cli.js |
Video URL or content ID | Comment text, commenter, likes, replies, and interaction data |
JSON schema assets
- Search request:
assets/search_cli_req.schema.json - Search response:
assets/search_cli_resp.schema.json - Post request:
assets/post_cli_req.schema.json - Post response:
assets/post_cli_resp.schema.json - Comment request:
assets/comment_cli_req.schema.json - Comment response:
assets/comment_cli_resp.schema.json - All schemas use JSON Schema draft-07 conventions.
Common response envelope
| Field | Meaning |
|---|---|
status |
success, empty, or error |
error_code |
Machine-readable result such as OK, NO_MATCH, or AUTH_REQUIRED |
message |
Human-readable execution detail |
timestamp |
Request timestamp |
request |
Normalized command, keyword, URL, sort, time, and limit values |
metadata |
Skill version, skill name, Node runtime, and execution time |
results |
Returned records; an array for success and null for empty or error responses |
warnings |
Parameter corrections, fallbacks, or other execution notices |
Persistence and transport
- Structured JSON is emitted on stdout for reliable machine parsing.
- Diagnostic output and the generated log-file location are emitted on stderr.
- Execution logs are saved under the system temporary directory at
tiktok-guaikei/logs/<date>/. - The service receives the API token, query keyword or target URL/ID, skill name, and Node version; the skill does not collect local files or private TikTok fields.
- Public data is limited to visible creator names, public posts, public comments, and related engagement metadata.
TikTok User Insight and Product Opportunity Analysis Advanced Features
- Intent-aware routing separates keyword discovery, creator-post retrieval, and video-comment analysis, including rules for ambiguous video URLs.
- Supports relevance, popularity, newest, hottest, and time-window filtering through
--sortand--time. - Provides bounded result collection with
--limit, explicit defaults, and warning propagation when invalid values are normalized. - Uses a stable success, empty, and error contract suitable for AI agents, ETL pipelines, reports, and analytics workflows.
- Includes structured metadata for skill version, runtime version, execution time, request parameters, and timestamps.
- Handles network and timeout retries internally while preserving actionable error codes such as
NO_MATCH,NETWORK_ERROR, andTIMEOUT_ERROR. - Enforces strict authentication behavior:
AUTH_REQUIREDstops execution and prevents blind retries or parameter changes. - Uses only Node.js built-in modules, with no npm dependencies, remote script loading,
eval, orchild_processexecution. - Applies a read-only, least-privilege model that avoids account login, private information, and TikTok write operations.
- Enables downstream analysis such as top-content ranking, comment clustering, sentiment estimation, creator screening, publishing-frequency analysis, and product-opportunity synthesis through Openclaw Skills workflows.
SKILL.md
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