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Agent Skill · 研究检索

company-analyzer(公司分析仪)

company-analyzer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

company-analyzer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 59,803。

总安装 376周安装 16GitHub Stars 52下载 132核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:company-analyzer(公司分析仪)
来源仓库:https://github.com/aaaaqwq/claude-code-skills
仓库路径:skills/company-analyzer
安装命令:
npx skills add https://github.com/aaaaqwq/claude-code-skills --skill company-analyzer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/aaaaqwq/claude-code-skills --skill company-analyzer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

company-analyzer 用于对公司进行多维度深度分析,适合在 Codex、Claude、Cursor、Gemini CLI 中获取结构化商业洞察。支持按框架分步执行或全量流水线分析,输出内容包括财务指标、业务模式等关键信息。

通过 GitHub 安装,使用 npx skills add 命令添加指定仓库中的技能。安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/company-analyzer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/aaaaqwq/claude-code-skills --skill company-ana…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

company-analyzer 怎么安装?

在终端执行 npx skills add https://github.com/aaaaqwq/claude-code-skills --skill company-analyzer。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

company-analyzer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

company-analyzer 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

company-analyzer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

company-analyzer 用的人多吗?

公开数据是累计安装 376 次,近一周安装 16 次,下载 132 次,GitHub 52 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

company-analyzer 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
company-analyzer

公司分析仪 · 本页

37652接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

CRITICAL: Execution Method

Full pipeline (all 8 frameworks + synthesis): when user asks to "analyze <TICKER>" or "run full analysis" (no "only" one step):

cd skills/company-analyzer && ./scripts/analyze-pipeline.sh <TICKER> --live

Single step only (e.g. "only 02-metrics" or "only produce 01-phase"): do NOT use --live. Run:

cd skills/company-analyzer && ./scripts/run-single-step.sh <TICKER> <FW_ID>

Example: only 02-metrics for KVYO → ./scripts/run-single-step.sh KVYO 02-metrics. Output appears at assets/outputs/<TICKER>_<FW_ID>.md after the script completes. Do not read that file before running the script.

DO NOT spawn subagents. DO NOT use sessions_spawn. Direct script execution only.

Company Analyzer

Perform comprehensive investment research on public companies using 8 specialized analysis frameworks with response caching and cost controls.

Quick Commands

When user types /analyze <TICKER>, execute:

cd skills/company-analyzer && ./scripts/analyze.sh <TICKER> --live

For dry run (no cost):

cd skills/company-analyzer && ./scripts/analyze.sh <TICKER>

Features

FeatureBenefit
Parallel Execution8 frameworks run simultaneously (~4-6s vs ~20s sequential)
Response CachingRe-analyzing same ticker uses cache = ~50-80% cost savings
Cost TrackingLogs spending for visibility (no enforced limits)
Alpha VantagePrice data (P/E, market cap) when configured in OpenClaw auth profiles
Retry Logic3 retries with exponential backoff on API failures

Frameworks

#NameFocus
1Phase ClassificationStartup/Growth/Maturity/Decline
2Key Metrics ScorecardFinancial health dashboard
3AI Moat ViabilityAI-native competitive advantage
4Strategic MoatCompetitive durability analysis
5Price & SentimentValuation + market sentiment
6Growth DriversNew vs existing customer mix
7Business ModelUnit economics & delivery
8Risk AnalysisKey threats & scenarios

Usage

Full Analysis (via Telegram/command)

User types: /analyze AAPL

You execute: cd skills/company-analyzer &&./scripts/analyze-pipeline.sh AAPL --live

Runs all 8 frameworks in parallel. Cost: ~$0.03 (or $0 if cached).

Data Fetching

Before analysis, fetch company data:

cd skills/company-analyzer && ./scripts/fetch_data.sh AAPL

This pulls:

  • Financial metrics from SEC EDGAR
  • Price data from Alpha Vantage (if API key configured)

Run only one framework (no pipeline, no synthesis)

When the user asks for "only 02-metrics" or "only produce 01-phase", run a single step. Do not use --live here (that flag is only for the full pipeline).

cd skills/company-analyzer && ./scripts/run-single-step.sh <TICKER> <FW_ID>

Examples:

  • Only 02-metrics: ./scripts/run-single-step.sh KVYO 02-metrics
  • Only 01-phase: ./scripts/run-single-step.sh KVYO 01-phase

Valid FW_ID values: 01-phase, 02-metrics, 03-ai-moat, 04-strategic-moat, 05-sentiment, 06-growth, 07-business, 08-risk.

Output is written to assets/outputs/<TICKER>_<FW_ID>.md (e.g. KVYO_02-metrics.md). Wait for the script to finish before reading that file. Use ticker KVYO for Klaviyo (not KYVO).

Architecture

Scripts

  • analyze-parallel.sh - Main orchestrator (parallel execution)
  • run-framework.sh - Single framework runner with caching; validates output for required end-markers (does not cache truncated responses; re-run step to get a fresh response)
  • fetch_data.sh - Data acquisition (SEC + Alpha Vantage)
  • lib/cache.sh - Response caching utilities
  • lib/cost-tracker.sh - Budget management
  • lib/api-client.sh - LLM API client (OpenClaw-configured model and auth); retry logic for transient errors

Truncation handling

  • After each framework response, the script checks for a required end-marker (e.g. 01-phase: Avoid:, 02-metrics: SUMMARY:). If missing, the output is still saved but not cached, and the step exits with code 1.
  • Diagnostics: On truncation, the trace logs finishReason, output token count, and limit; stderr explains the cause:

- MAX_TOKENS → Response hit the token limit; increase that framework’s limit or shorten the prompt. - STOP → Model stopped early; the prompt may need a stronger “must complete through [end-marker]” instruction (see 01-phase for an example).

  • Re-run that step (or the full pipeline) to get a fresh response.

Caching

  • Location: skills/company-analyzer/.cache/llm-responses/ (skill dir); falls back to ~/.openclaw/cache/company-analyzer/llm-responses/ if skill dir is read-only
  • TTL: 7 days
  • Key: TICKER_FWID_PROMPT_HASH
  • Cached responses show: 💰 framework: $0.0000 (cached)

Cost Tracking (No enforced limits)

  • Costs are logged for visibility
  • No spending limit enforced
  • Run as many analyses as needed

Configuration

Alpha Vantage (fallback for FCF, revenue_q_yoy)

When Yahoo/SEC leave fcf or revenue_q_yoy as N/A, fetch_data.sh uses Alpha Vantage if configured. Add the Alpha Vantage profile to OpenClaw auth profiles (e.g. alpha-vantage:default with your key).

{
  "profiles": {
    "alpha-vantage:default": {
      "key": "YOUR_API_KEY"
    }
  }
}

Uses: INCOME_STATEMENT (quarterly revenue for YoY), CASH_FLOW (FCF). Free tier: 25 API calls/day; script uses up to 2 calls per ticker with 2s delay between.

LLM / API

Model and API key are read from OpenClaw config (primary model and {provider}:default auth profile). No hardcoded provider or keys. Add your model's pricing to scripts/lib/prices.json for cost tracking.

Output

All analyses saved to assets/outputs/:

  • TICKER_01-phase.md through TICKER_08-risk.md

*(Synthesis phase removed for cost efficiency)*

Performance

ModeTimeCost
Sequential (old)~20s$0.04
Parallel (8 frameworks, unlimited)~4s~$0.045
Configured LLM~5–20sDepends on model and pricing
Cached~1s$0.00

Cost tracking:

  • No reasoning overhead - all tokens go to content
  • Built-in rate limiting from OpenClaw config. Cost per analysis depends on your LLM; add rates to scripts/lib/prices.json.

Troubleshooting

"Alpha Vantage rate limit":

  • Free tier = 25 calls/day
  • Price data falls back to N/A, analysis continues with SEC data only

"API key has run out of credits" / "insufficient balance" / rate limit:

  • Caused by billing or rate limits on your configured LLM provider. The pipeline uses a 45s cooldown between steps to reduce spikes.
  • Fix: Top up or switch the API key in OpenClaw auth profiles for your provider. Avoid running many analyses back-to-back; space runs by at least a few minutes.

"Analysis failed (code 1)" / Heartbeat alert after 01-phase or 02-metrics:

  • Often HTTP 503 (Service Unavailable) or billing/quota (402, 403). The pipeline continues after a failed step and still builds a partial report.
  • Fix: For 503, re-run later. For billing, top up or switch key (see above). Run from the skill directory: cd skills/company-analyzer &&./scripts/analyze-pipeline.sh <TICKER> --live.

Framework failures:

  • Failed steps are listed at the end; partial outputs remain in assets/outputs/. Check assets/traces/<TICKER>_<date>.trace for which step failed and why.

平台分布

Codex

35.91%
按下载量换算47

Claude

29.07%
按下载量换算38

Cursor

19.1%
按下载量换算25

Gemini CLI

8.41%
按下载量换算11

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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