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在 OpenClaw 中安装
/install botlearn-twitter-intel
功能描述
Monitor Twitter to identify key opinion leaders, track emerging trends, analyze sentiment, detect bots, and deliver verified real-time intelligence reports.
使用说明 (SKILL.md)
Role
You are a Twitter Intelligence Analyst. When activated, you monitor the Twitter/X platform to track key opinion leaders (KOLs), extract trending narratives, analyze engagement signals, detect bot-driven amplification, and synthesize actionable intelligence reports from the platform's real-time discourse.
Capabilities
- Curate and maintain watchlists of KOLs, domain experts, and emerging voices within specified topics or industries
- Filter high-signal tweets from noise using engagement metrics, account credibility scoring, and content relevance analysis
- Extract and classify opinions, stances, and sentiment from tweet threads, quote tweets, and reply chains
- Detect emerging trends, narrative shifts, and coordinated amplification campaigns before they reach mainstream awareness
- Synthesize multi-source Twitter intelligence into structured, time-stamped briefings with confidence ratings and source attribution
- Identify bot networks, astroturfing patterns, and inauthentic engagement to separate organic signal from manufactured consensus
Constraints
- Never treat high engagement (likes, retweets) as a proxy for credibility — always verify the source account's authenticity and authority
- Never report on a trend based on a single tweet or a single account — require corroboration from 3+ independent sources
- Never ignore sarcasm, irony, or satire markers — always assess tweet tone before extracting sentiment or opinion
- Never present bot-amplified content as organic public opinion — always flag suspected inauthentic activity
- Always include temporal context (timestamps, trend velocity) — Twitter intelligence is time-sensitive by nature
- Always respect rate limits and platform terms of service when interfacing with Twitter/X API endpoints
Activation
WHEN the user requests Twitter monitoring, KOL tracking, or trend analysis:
- Identify the target topic, industry, or set of accounts to monitor
- Execute source curation and signal filtering following strategies/main.md
- Apply knowledge/domain.md for API usage, metric interpretation, and KOL identification
- Evaluate findings using knowledge/best-practices.md for credibility and trend validation
- Check against knowledge/anti-patterns.md to avoid engagement blindness, sarcasm misreads, and bot amplification traps
- Output a structured intelligence briefing with confidence levels, source attribution, and temporal context
安全使用建议
This skill's documentation shows how to use Twitter/X APIs (including streaming and full-archive access) and gives a detailed analyst workflow, but it does not declare how it will authenticate to Twitter. Before installing or enabling this skill: (1) ask the publisher how authentication is provided and whether the skill expects you to supply API credentials (Bearer token, API key/secret, or elevated Academic/Pro access); (2) confirm where and how the skill will make network calls and whether it will store or transmit collected tweets outside your environment; (3) if you must provide credentials, prefer using short-lived, least-privilege tokens and ensure the skill uses a secure secret store rather than embedding secrets in plaintext; (4) if your platform provides a vetted Twitter connector, verify the skill is explicitly configured to use that connector. The mismatch between required capabilities and declared credentials is the main red flag — it may be an oversight, but treat it as unresolved until clarified.
功能分析
Type: OpenClaw Skill
Name: botlearn-twitter-intel
Version: 1.0.0
The OpenClaw AgentSkills skill bundle for 'twitter-intel' is benign. All instructions across `skill.md`, `knowledge/*.md`, and `strategies/main.md` are consistently focused on Twitter/X platform intelligence gathering and analysis. The skill explicitly details the use of standard Twitter/X API endpoints and query operators, without any indication of accessing sensitive local files, executing arbitrary shell commands, or making unauthorized network requests to external domains for data exfiltration or command and control. The markdown files are used to guide the AI agent's analytical process and enforce best practices, rather than attempting prompt injection for malicious purposes.
能力评估
Purpose & Capability
The skill's stated purpose is live Twitter/X monitoring (search, filtered stream, full-archive) and bot detection, which normally requires authenticated access (API keys/tokens) and possibly elevated API tiers. The manifest and SKILL.md reference v2 endpoints and rate limits, yet the skill declares no required environment variables or primary credential. That is disproportionate: a Twitter-intel skill should at minimum declare a bearer token or instructions to use a platform-provided connector.
Instruction Scope
SKILL.md provides detailed runtime instructions: building queries, fetching tweets, retrieving threads (conversation_id), running bot heuristics, and synthesizing briefings. Those instructions are scoped to the stated purpose and do not ask the agent to read unrelated system files or exfiltrate secrets. However they assume the agent can execute API calls and paginate/stream results without specifying how authentication or network access are provided.
Install Mechanism
This is an instruction-only skill with no install spec and no code files to execute — low disk/write risk. Files are documentation (knowledge, strategies, tests). No remote downloads or install scripts are present.
Credentials
The skill requires access to Twitter API endpoints in its instructions (Recent Search, Filtered Stream, Full-Archive) but declares zero required env vars or credentials. Typical required variables (e.g., TWITTER_BEARER_TOKEN, TWITTER_API_KEY/SECRET, or a platform connector config) are missing. This gap is a proportionality/integrity issue: the skill either omits declaring needed sensitive credentials or expects implicit platform-level credentials (not documented).
Persistence & Privilege
The skill does not request 'always: true', does not declare system config paths, and does not modify other skills. Autonomous invocation is allowed by default, which is normal; there are no extra persistence/privilege flags in the manifest.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install botlearn-twitter-intel - 安装完成后，直接呼叫该 Skill 的名称或使用
/botlearn-twitter-intel触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Major update: Skill transformed from "BotLearn" social learning to specialized Twitter/X intelligence analysis.
- Skill repurposed: Focus is now Twitter/X monitoring, KOL tracking, trend/narrative detection, and bot activity analysis.
- New role, constraints, and activation logic defined for a Twitter Intelligence Analyst.
- Knowledge and strategy files added for domain expertise, best practices, anti-patterns, and intelligence briefings.
- Old BotLearn collaboration and social learning documents removed.
- Structured, actionable Twitter intelligence output specified, emphasizing source credibility, corroboration, and temporal context.
元数据
常见问题
botlearn-twitter-intel 是什么？
Monitor Twitter to identify key opinion leaders, track emerging trends, analyze sentiment, detect bots, and deliver verified real-time intelligence reports. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 344 次。
如何安装 botlearn-twitter-intel？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install botlearn-twitter-intel」即可一键安装，无需额外配置。
botlearn-twitter-intel 是免费的吗？
是的，botlearn-twitter-intel 完全免费（开源免费），可自由下载、安装和使用。
botlearn-twitter-intel 支持哪些平台？
botlearn-twitter-intel 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 botlearn-twitter-intel？
由 邢怀康（@calvinxhk）开发并维护，当前版本 v1.0.0。
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