Competitor Analysis
by bytesagain3
Generate competitor analysis with SWOT and market positioning. Use when comparing features, checking market share, analyzing differentiation strategies.
安装
claude skill add --url github.com/openclaw/skills/tree/main/skills/bytesagain3/rivalwatch文档
Rivalwatch
Rivalwatch v2.0.0 is a utility toolkit for tracking, analyzing, and managing competitive intelligence data. It provides a comprehensive CLI with timestamped logging, multi-format data export, and full activity history tracking for competitor analysis workflows.
Commands
All commands accept optional <input> arguments. When called without arguments, they display the 20 most recent entries from their respective logs. When called with input, they record a new timestamped entry.
| Command | Usage | Description |
|---|---|---|
run | rivalwatch run [input] | Run a competitive analysis task and log the result |
check | rivalwatch check [input] | Check a competitor's status or validate data |
convert | rivalwatch convert [input] | Convert competitive data between formats |
analyze | rivalwatch analyze [input] | Analyze competitive positioning or market data |
generate | rivalwatch generate [input] | Generate competitive intelligence reports |
preview | rivalwatch preview [input] | Preview analysis output before finalizing |
batch | rivalwatch batch [input] | Process multiple competitors in batch mode |
compare | rivalwatch compare [input] | Compare two or more competitors side by side |
export | rivalwatch export [input] | Log an export operation |
config | rivalwatch config [input] | Manage analysis configuration settings |
status | rivalwatch status [input] | Log or view status entries |
report | rivalwatch report [input] | Generate or log competitive reports |
Utility Commands
| Command | Usage | Description |
|---|---|---|
stats | rivalwatch stats | Show summary statistics across all log files |
export <fmt> | rivalwatch export json|csv|txt | Export all data in JSON, CSV, or plain text format |
search <term> | rivalwatch search <term> | Search across all log entries (case-insensitive) |
recent | rivalwatch recent | Show the 20 most recent activity entries |
status | rivalwatch status | Health check — version, data dir, entry count, disk usage |
help | rivalwatch help | Show full command reference |
version | rivalwatch version | Print version string (rivalwatch v2.0.0) |
Data Storage
All data is stored locally in ~/.local/share/rivalwatch/:
history.log— Master activity log with timestamps for every operationrun.log,check.log,analyze.log, etc. — Per-command log files storingtimestamp|inputentriesexport.json,export.csv,export.txt— Generated export files
Each entry is stored in pipe-delimited format: YYYY-MM-DD HH:MM|value. The data directory is created automatically on first use.
Requirements
- Bash 4.0+ (uses
set -euo pipefail,localvariables) - Standard Unix tools:
date,wc,du,tail,grep,sed,basename,cat - No external dependencies, API keys, or network access required
- Works on Linux, macOS, and WSL
When to Use
- Tracking competitor product changes — Use
runandcheckto log competitor updates, feature launches, or pricing changes over time - Comparing market positioning — Use
compareto track how two or more competitors position themselves on features, pricing, or messaging - Generating SWOT-style analysis — Use
analyzefollowed byreportto build structured competitive intelligence documents - Batch monitoring multiple competitors — Use
batchto queue and process data on several competitors in a single pass - Exporting competitive data for presentations — Use
export jsonorexport csvto produce structured data for dashboards or stakeholder reports
Examples
# Log a competitor product update
rivalwatch run "Competitor X launched feature Y at $29/mo"
# Check competitor pricing
rivalwatch check "Competitor Z pricing page updated"
# Analyze market positioning
rivalwatch analyze "SaaS CRM market Q1 2025"
# Compare two competitors
rivalwatch compare "Slack vs Teams - enterprise features"
# Batch process multiple competitor entries
rivalwatch batch "CompA launch" "CompB pivot" "CompC funding"
# Export all competitive intel as JSON
rivalwatch export json
# Search for past entries mentioning a competitor
rivalwatch search "Competitor X"
# View summary statistics
rivalwatch stats
Output
All commands output structured text to stdout. Use standard shell redirection to capture output:
rivalwatch stats > summary.txt
rivalwatch export json # writes to ~/.local/share/rivalwatch/export.json
Powered by BytesAgain | bytesagain.com | hello@bytesagain.com
相关 Skills
迁移架构师
by alirezarezvani
为数据库、API 与基础设施迁移制定分阶段零停机方案,提前校验兼容性与风险,生成回滚策略、验证关卡和时间线,适合复杂系统平滑切换。
✎ 做数据库与存储迁移时,用它统一梳理表结构和数据搬迁流程,架构视角更完整,复杂迁移也更稳。
数据库建模
by alirezarezvani
把需求梳理成关系型数据库表结构,自动生成迁移脚本、TypeScript/Python 类型、种子数据、RLS 策略和索引方案,适合多租户、审计追踪、软删除等后端建模与 Schema 评审场景。
✎ 把数据库结构设计、ER图梳理和SQL建模放到一处,复杂业务也能快速统一数据模式,少走不少返工弯路。
资深数据工程师
by alirezarezvani
聚焦生产级数据工程,覆盖 ETL/ELT、批处理与流式管道、数据建模、Airflow/dbt/Spark 优化和数据质量治理,适合设计数据架构、搭建现代数据栈与排查性能问题。
✎ 复杂数据管道、ETL/ELT 和治理难题交给它,凭 Spark、Airflow、dbt 等现代数据栈经验,能更稳地搭起可扩展的数据基础设施。
相关 MCP 服务
PostgreSQL 数据库
编辑精选by Anthropic
PostgreSQL 是让 Claude 直接查询和管理你的数据库的 MCP 服务器。
✎ 这个服务器解决了开发者需要手动编写 SQL 查询的痛点,特别适合数据分析师或后端开发者快速探索数据库结构。不过,由于是参考实现,生产环境使用前务必评估安全风险,别指望它能处理复杂事务。
SQLite 数据库
编辑精选by Anthropic
SQLite 是让 AI 直接查询本地数据库进行数据分析的 MCP 服务器。
✎ 这个服务器解决了 AI 无法直接访问 SQLite 数据库的问题,适合需要快速分析本地数据集的开发者。不过,作为参考实现,它可能缺乏生产级的安全特性,建议在受控环境中使用。
Firecrawl 智能爬虫
编辑精选by Firecrawl
Firecrawl 是让 AI 直接抓取网页并提取结构化数据的 MCP 服务器。
✎ 它解决了手动写爬虫的麻烦,让 Claude 能直接访问动态网页内容。最适合需要实时数据的研究者或开发者,比如监控竞品价格或抓取新闻。但要注意,它依赖第三方 API,可能涉及隐私和成本问题。