Comparison
Agent-Reach vs ai-berkshire
Verdict
Pick Agent-Reach if agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content; pick ai-berkshire if ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's.
Markdown twin · Agent-Reach alternatives · ai-berkshire alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | Agent-Reach | ai-berkshire |
|---|---|---|
| Maintenance | Very active (0d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Agent-Reach
- AI Agent for Automated Web and Social Media Data Extraction
- ai-berkshire
- AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis.
Stars
- Agent-Reach
- 61k
- ai-berkshire
- 14k
Forks
- Agent-Reach
- 4.9k
- ai-berkshire
- 2.0k
Open issues
- Agent-Reach
- 168
- ai-berkshire
- 29
Language
- Agent-Reach
- Python
- ai-berkshire
- Python
Adopt for
- Agent-Reach
- Agent-Reach facilitates hands-off web and social media scraping via command line with no API costs for retrieving varied internet content.
- ai-berkshire
- ai-berkshire implements a unique approach to value investing research through AI agents powered by Claude Code/Codex, inspired by the methodologies of Warren Buffett and Charlie Munger amongst other investors. The tool's
Persona
- Agent-Reach
- -
- ai-berkshire
- -
Runtime
- Agent-Reach
- -
- ai-berkshire
- -
License
- Agent-Reach
- MIT
- ai-berkshire
- MIT
Last pushed
- Agent-Reach
- Jul 25, 2026
- ai-berkshire
- Jul 25, 2026
Categories
- Agent-Reach
- AI Agents, Data & Retrieval
- ai-berkshire
- AI Agents, Evaluation & Observability
Trust and health
Open issues (now)
- Agent-Reach
- 168
- ai-berkshire
- 29
Full report
- Agent-Reach
- Trust report
- ai-berkshire
- Trust report
Choose Agent-Reach if…
- Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation.
- Also covers Data & Retrieval.
- When needing to bypass costly API fees for extensive social media platform data extraction
When NOT to use Agent-Reach
- If strict compliance with website scraping policies is critical due to its use of scraping techniques
- When direct interaction through APIs for precision and reliability is preferred over scraping
Choose ai-berkshire if…
- Tags unique to ai-berkshire: ai, financial-analysis, investment-research, portfolio-management.
- Also covers Evaluation & Observability.
- You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies.
When NOT to use ai-berkshire
- If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise.
- When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Panniantong/Agent-Reach) · observed Jul 26, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 26, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 25, 2026
- License file (MIT) · observed Jul 26, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (xbtlin/ai-berkshire) · observed Jul 26, 2026
- GitHub forks (xbtlin/ai-berkshire) · observed Jul 26, 2026
- Last push (xbtlin/ai-berkshire) · observed Jul 25, 2026
- License file (MIT) · observed Jul 26, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Agent-Reach 61k · ai-berkshire 14k (synced Jul 26, 2026).
Common questions
- What is the difference between Agent-Reach and ai-berkshire?
- Agent-Reach: AI Agent for Automated Web and Social Media Data Extraction. ai-berkshire: AI-era Berkshire: a value investing research framework utilizing Claude Code / Codex with methodologies from Warren Buffett, Charlie Munger among others and multi-Agent adversarial analysis.. See the comparison table for live GitHub stats and shared categories.
- When should I choose Agent-Reach over ai-berkshire?
- Choose Agent-Reach over ai-berkshire when Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers Data & Retrieval; When needing to bypass costly API fees for extensive social media platform data extraction.
- When should I choose ai-berkshire over Agent-Reach?
- Choose ai-berkshire over Agent-Reach when Tags unique to ai-berkshire: ai, financial-analysis, investment-research, portfolio-management; Also covers Evaluation & Observability; You need to leverage multi-Agent adversarial analysis for deep fundamental stock market assessment aligned with renowned investor philosophies.
- When should I avoid Agent-Reach?
- If strict compliance with website scraping policies is critical due to its use of scraping techniques When direct interaction through APIs for precision and reliability is preferred over scraping
- When should I avoid ai-berkshire?
- If your investment research requires real-time trading data or dynamic algorithmic trading strategies which are not the tool's expertise. When you prefer a more manual or traditional approach to value investing that does not integrate AI-driven adversarial agent methodologies.
- Is Agent-Reach or ai-berkshire more popular on GitHub?
- Agent-Reach has more GitHub stars (60,828 vs 14,138). Stars measure visibility, not whether either tool fits your constraints.
- Are Agent-Reach and ai-berkshire open source?
- Yes - both are open-source projects on GitHub (Agent-Reach: MIT, ai-berkshire: MIT).
- Where can I find alternatives to Agent-Reach or ai-berkshire?
- GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and ai-berkshire alternatives (Agent-Reach markdown twin, ai-berkshire markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Agent-Reach or ai-berkshire?
- Agent-Reach: Very active. ai-berkshire: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for Agent-Reach and ai-berkshire?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; ai-berkshire trust report.