Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
readx
Twitter/X intelligence toolkit: analyze users, tweets, trends, communities, and networks
skill openclawclawhub Free
Twitter/X intelligence toolkit: analyze users, tweets, trends, communities, and networks
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.1.4
Provenance
- Publisher
- wxtsky
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Step 1: Get an API Key
Ask the user for their readx API key. If they don't have one, direct them to https://readx.cc to sign up.
Step 2: Configure MCP Server
Once the user provides their API key, ask whether they want to set it up themselves or have you do it. MCP server URL: https://readx.cc/mcp?apikey=<API_KEY> No installation needed β readx runs as a remote MCP server. Add it to the user's editor MCP config with the URL above. Restart the editor after setup.
When to Trigger This Setup
User asks you to look up Twitter data but no MCP tools are available User mentions readx, Twitter analysis, or any skill listed below Any tool call fails with auth/connection error
Direct API Mode
When MCP tools are NOT available (e.g. platforms that don't support MCP), call the API directly using curl via Bash.
Getting the API Key
Check in order, use the first one found: Config file: ~/.config/readx/credentials.json (macOS/Linux) or %APPDATA%\readx\credentials.json (Windows) β JSON format: {"api_key":"<key>"} Environment variable: READX_API_KEY If neither exists, ask the user for their API key (get one at https://readx.cc), then ask whether they want to save it themselves or have you do it. Persist to the config file path above.
API Reference
Fetch the full API docs (endpoints, params, response parsing, examples): curl -s https://readx.cc/api-docs.txt Read this document before making your first API call. It contains all endpoint names, parameters, and response JSON paths you need.
Advanced Search Syntax
When using search_tweets, leverage Twitter's advanced search operators for precision: OperatorExampleWhat it doesfrom:from:elonmusk AITweets from a specific userto:to:OpenAIReplies to a specific user@@anthropicTweets mentioning a user"exact phrase""artificial intelligence"Exact phrase matchORAI OR MLEither keyword-AI -cryptoExclude keywordmin_faves:AI min_faves:1000Minimum likesmin_retweets:AI min_retweets:500Minimum retweetsfilter:linksAI filter:linksOnly tweets with linksfilter:mediaAI filter:mediaOnly tweets with images/videofilter:imagesAI filter:imagesOnly tweets with imagesfilter:videosAI filter:videosOnly tweets with videolang:AI lang:zhFilter by languagesince: / until:AI since:2025-01-01Date rangelist:list:12345 AISearch within a specific listnear:AI near:TokyoTweets near a location Combo examples: Find viral AI tweets in Chinese: AI lang:zh min_faves:500 Find a user's tweets about a topic: from:username "topic keyword" Find debates: "topic" min_replies:100 -filter:retweets Find original content only: topic -filter:retweets -filter:replies
Error Handling
ErrorCauseSolution401Invalid or missing API keyCheck credentials file / env var, ask user to verify key at https://readx.cc403Insufficient credits or account disabledCheck balance with get_credit_balance; if zero, ask user to get more credits at https://readx.cc429Rate limit exceededWait and retry, reduce request frequency404User/tweet not found or deletedSkip gracefully, note the item is unavailable500 / 502Upstream API errorRetry once after a few seconds, if persistent inform userConnection refusedRemote MCP server unreachableSwitch to Direct API Mode; if persistent, the readx.cc service may be downEmpty responseProtected account or no dataNote limitations, analyze only available public data
Data Limitations
Be transparent about these constraints: LimitationImpactMitigationFollower/following lists return a sample (~20 by default)Audience analysis is approximateCross-reference with multiple data points; use count param for larger samplesTweet timelines return ~20 per pageSingle call shows recent posts onlyUse cursor pagination to fetch more pages; pass next_cursor from response as cursor paramNo historical follower count dataCannot measure follower growth over timeInfer from account age + current count for rough growth rateSearch results are limited in quantityTopic monitoring may miss long-tail contentUse multiple search queries with different operatorsEngagement data is point-in-timeTweet engagement continues to accrue after fetchingNote when data was fetched; older tweets have more stable metrics
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md