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Company Analyzer

  • 16 installs
  • 82 repo stars
  • Updated August 2, 2026
  • aaaaqwq/claude-code-skills

company-analyzer is a Claude Code skill that performs investment research on public companies using 8 specialized analysis frameworks plus a synthesis step.

About

company-analyzer is a Claude Code skill for investment research on public companies using 8 specialized analysis frameworks. A developer or investor runs it on a ticker to classify company phase, score financial metrics, assess AI and strategic moats, gauge sentiment, and analyze growth, business model, and risk. It runs frameworks in parallel with caching and cost tracking, pulling data from SEC EDGAR and Alpha Vantage, then synthesizes an investment view.

  • Investment research on public companies using 8 specialized analysis frameworks plus synthesis
  • Runs frameworks in parallel with response caching and cost tracking, pulling SEC EDGAR and Alpha Vantage data
  • Covers phase classification, metrics scorecard, AI/strategic moats, sentiment, growth, business model, and risk

Company Analyzer by the numbers

  • 16 all-time installs (skills.sh)
  • Ranked #739 of 1,106 Finance & Trading skills by installs in the Skillselion catalog
  • Data as of Aug 3, 2026 (Skillselion catalog sync)
At a glance

company-analyzer capabilities & compatibility

Full analysis ~$0.03 per ticker (or $0 if cached); optional Alpha Vantage key for price data

Capabilities
investment research · company analysis · moat analysis · financial scoring
Use cases
research · data analysis
From the docs

What company-analyzer says it does

Perform comprehensive investment research on public companies using 8 specialized analysis frameworks
SKILL.md
npx skills add https://github.com/aaaaqwq/claude-code-skills --skill company-analyzer

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Listed on Skillselion
Installs16
repo stars82
Last updatedAugust 2, 2026
Repositoryaaaaqwq/claude-code-skills

What it does

Run multi-framework investment research on a public company ticker and synthesize an investment thesis.

Who is it for?

Analyzing a public company ticker for investment: phase, metrics, moats, sentiment, growth, and risk

Skip if: Private-company or non-investment analysis, or single trivial lookups

When should I use this skill?

The user wants to analyze a public company for investment or research competitive positioning

By the numbers

  • 8 analysis frameworks plus a synthesis step
  • parallel run ~4-6s vs ~20s sequential
  • caching yields ~50-80% cost savings

Files

SKILL.mdMarkdownGitHub ↗

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.

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