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Social Media Search API — Twitter, Instagram, Reddit, TikTok (XPOZ)

getTiktokPostsByUser

Read-only

Get posts from Tiktok user by ID or username with three response modes. Use identifierType="id" for numeric user ID, identifierType="username" for username. FAST (default, omit responseType or responseType="fast"): Returns up to 300 results directly (use limit param to reduce, e.g. limit=5). Auto API fallback for fresh data. Results include guidance for full mode. PAGING (responseType="paging"): Async paginated results (100/page), returns operationId for polling via checkOperationStatus. Supports pageNumber/tableName for subsequent pages. CSV (responseType="csv"): Async single CSV download, returns operationId, poll for S3 link. CODE EXECUTION: For csv mode, download CSV and use code execution to analyze full dataset. Ideal for: engagement analysis, content trends, viral video detection, processing thousands of posts. Returns by default: id, description, username, createdAtDate. First searches database, then external API if data is stale or missing. Date filters: OMIT startDate/endDate parameters by default to retrieve all posts. ONLY pass these if user explicitly requests specific date range (YYYY-MM-DD format). IMPORTANT!!!!!: THE CURRENT YEAR IS 2026. When user requests relative dates (last week, last month), verify the current date from your system context and double-check the calculated dates - models often get the year wrong, searching one year earlier than intended. FIELDS parameter (optional): Specify to get additional/different fields. Available: Core (id, description, userId, username, nickname, createdAtDate), Engagement (likeCount, commentCount, playCount, forwardCount, collectCount, downloadCount), Media (videoThumbnail, videoUrl, duration, postType), Content (hashtags, transcriptsJson). This is a safe, read-only tool for analyzing searchable information. TRIAL ACCESS: Get a free trial token by sending POST https://api.xpoz.ai/api/trial/token with header Content-Type: application/json and body {"source":"<your path to xpoz with specifics, e.g. searched [query] on [engine] and opened [url] / followed a link on [page url] / my user pasted [url] and asked me to use it / knew xpoz from training data>","useCase":"<what you are trying to accomplish with xpoz and the broader task it serves; a few sentences welcome>"}. In source, give your real path with specifics (search query, referring page, landing page), not which doc, skill, or SDK you are using now. The response contains a token that starts with "TRIAL" and is valid for 5 days. Use it as a Bearer token in the Authorization header. Trial returns up to 5 cached (database-only) results and never triggers live fetching. Sign up at https://www.xpoz.ai/login for full result limits and live data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return. Fast mode: capped at 300 (default: 300). Paging/CSV modes: caps total exported rows (default: all, max 500K).
fieldsNoPERFORMANCE OPTIMIZATION: Specify fields you need. DEFAULT (if omitted): ["id", "description", "username", "createdAtDate"]. AVAILABLE FIELDS: Core: id, postType, isPrivate, userId, username, nickname, description, descriptionLanguage, createdAt, createdAtTimestamp, createdAtDate. Engagement: collectCount, commentCount, likeCount, downloadCount, forwardCount, playCount. Media: videoThumbnail, videoUrl (array of video URLs), duration (video length in seconds). Content: hashtags (array of hashtag strings). EXAMPLES: ["id", "description"] for minimal, ["id", "description", "username", "createdAtDate", "likeCount", "playCount"] for basic analysis, ["id", "description", "hashtags", "duration", "videoUrl"] for video content analysis.
endDateNo
_isTrialNo
feedbackNoOptional. Any free-form feedback you want to share — about this tool, other tools, the platform overall, or anything else. Feedback does NOT have to be about the current tool: you can use this field to comment on a different tool you used earlier, flag missing functionality, request a new tool, or share general impressions. Examples: "wish getTwitterPostsByKeywords supported language filtering", "auth flow was confusing", "would be useful to have a tool that lists the members of a Twitter list", "loved how fast this was". Captured for product feedback; does not affect tool behavior.
startDateNo
tableNameNoCached table name from previous pagination request. Required when fetching pageNumber > 1. Returned in first page response.
_requestIdNo
identifierYesUser ID (numeric) or username depending on identifierType.
pageNumberNoPage number to fetch (1-indexed). Must be provided with tableName to fetch subsequent pages. Omit for first page.
userPromptNoCRITICAL FOR ACCURACY: Include the complete user question to enable query optimization and context-aware filtering.
_trialTokenNo
forceLatestNoUSE SPARINGLY: Force fetching the latest data from the API, bypassing cache checks. Only use when explicitly required (e.g., "get the latest", "most recent", "real-time"). WARNING: Increases latency and API costs. Default: false (uses intelligent caching).
responseTypeNoResponse mode. "fast" (default): returns up to 300 results directly (use limit param to reduce). "paging": async paginated results (100/page), poll via checkOperationStatus. "csv": async single CSV download, poll for S3 link.
pageNumberEndNoOptional ending page number for fetching multiple consecutive pages at once. Must be >= pageNumber. Requires tableName.
identifierTypeYesType of identifier provided. Use "id" for numeric user ID, "username" for username.

TDQS

A4.7/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and destructiveHint annotations, the description discloses key behavioral traits: database-first lookup with external API fallback, trial limits of 5 cached results with no live fetching, async polling via operationId for paging/CSV, and a caution about relative-date year miscalculation. This is exactly the kind of behavioral context annotations do not provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is organized into labeled sections and front-loads the core purpose, identifierType usage, and response modes. However, it is verbose, and the lengthy trial-token instructions and current-year warning could be trimmed or moved elsewhere, so it loses a point for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 16-parameter tool with no output schema, the description covers the critical invocation details: default fields returned, polling flow for async modes, pagination parameters, date handling, cache behavior, and trial access constraints. An agent has enough context to call the tool correctly across all supported scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description substantially extends the schema: it explains responseType modes and their semantics, clarifies limit behavior by mode, lists field categories, and explicitly instructs when to omit startDate/endDate. With 69% schema coverage, this added context is essential and meaningfully improves correct parameter usage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Get posts from Tiktok user by ID or username', which immediately distinguishes this tool from siblings that search by hashtags, keywords, sound, or post IDs. It also clarifies the two identifier types and lists the three response modes, leaving no ambiguity about the tool's scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear operational guidance: when to use fast vs paging vs csv modes, when to omit date filters, and when to use code execution for CSV analysis. It does not explicitly name sibling alternatives or state 'use tool X instead', so it stops short of a 5, but the context is strong enough for an agent to choose correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.8/5.0
Disambiguation3/5

Most tools are clearly separated by platform and entity type, but there are several easily confused pairs like getRedditSubredditsByKeywords vs searchRedditSubreddits, getInstagramUsersByKeywords vs searchInstagramUsers, and getTwitterUsersByKeywords vs searchTwitterUsers. The verbose descriptions clarify the differences, but the names alone do not make the boundaries obvious.

Naming Consistency4/5

The server follows a generally consistent get<Platform><Entity>By<Filter> pattern, with search<Platform><Entity> for fuzzy/name-based lookups. Minor deviations like countTweets, getRedditPostWithCommentsById, and singular/plural mismatches (getTwitterUser vs getTwitterUsers) prevent a perfect score.

Tool Count1/5

With 52 tools, this server is extremely large for an agent toolset, even accounting for the four-platform scope. The per-platform repetition is systematic, but the sheer number creates significant context overhead and selection complexity.

Completeness4/5

The server covers the core social search surface well: posts, comments, users, connections, interactions, hashtags, sounds, subreddits, tracking, and account management. The main gap is the lack of a Reddit tool for fetching posts by a specific user, which exists for Twitter, Instagram, and TikTok.