Home/Compare/AutoAudit vs Agent-Reach

Comparison

AutoAudit vs Agent-Reach

Verdict

Pick AutoAudit when autoAudit is primarily HTML; Agent-Reach is Python; pick Agent-Reach when agent-Reach is primarily Python; AutoAudit is HTML.

Markdown twin · AutoAudit alternatives · Agent-Reach alternatives

GraphCanon updated 1d

AutoAudit logo

AutoAudit

ddzipp/AutoAudit

355pushed Feb 28, 2025
vs
Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026

Trust & integrity

SignalAutoAuditAgent-Reach
Maintenance
Dormant (498d since push)
As of 1d · github_public_v1
Very active (0d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Personal account
As of 1d · github_public_v1
Not a fork · Personal account
As of 1d · github_public_v1
Security (OSV)
No lockfile
As of 1d · none
No MCP manifest
As of 1d · mcp_manifest

Tagline

AutoAudit
AutoAudit—— the LLM for Cyber Security 网络安全大语言模型
Agent-Reach
Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.

Stars

AutoAudit
355
Agent-Reach
55k

Forks

AutoAudit
38
Agent-Reach
4.5k

Open issues

AutoAudit
4
Agent-Reach
144

Language

AutoAudit
HTML
Agent-Reach
Python

Adopt for

AutoAudit
-
Agent-Reach
-

Persona

AutoAudit
-
Agent-Reach
-

Runtime

AutoAudit
-
Agent-Reach
-

License

AutoAudit
MIT
Agent-Reach
MIT

Last pushed

AutoAudit
Feb 28, 2025
Agent-Reach
Jul 10, 2026

Categories

AutoAudit
LLM Frameworks, Model Training
Agent-Reach
AI Agents, Developer Tools, LLM Frameworks

Trust and health

Maintenance

AutoAudit
Dormant (18%)
Agent-Reach
Very active (96%)

Days since push

AutoAudit
498d
Agent-Reach
0d

Open issues (now)

AutoAudit
4
Agent-Reach
144

Security scan

AutoAudit
No lockfile
Agent-Reach
No MCP manifest

Full report

AutoAudit
Trust report
Agent-Reach
Trust report

Choose AutoAudit if…

  • AutoAudit is primarily HTML; Agent-Reach is Python.
  • Tags unique to AutoAudit: cyber-security, fine-tuning, gpt, html.
  • Also covers Model Training.

When NOT to use AutoAudit

  • Last GitHub push was 499 days ago (dormant maintenance, Feb 28, 2025). Validate activity before betting a new project on AutoAudit.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.

Choose Agent-Reach if…

  • Agent-Reach is primarily Python; AutoAudit is HTML.
  • Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation.
  • Also covers AI Agents, Developer Tools.

When NOT to use Agent-Reach

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: AutoAudit 355 · Agent-Reach 55k (synced Jul 11, 2026).

Common questions

What is the difference between AutoAudit and Agent-Reach?
AutoAudit: AutoAudit—— the LLM for Cyber Security 网络安全大语言模型. Agent-Reach: Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.. See the comparison table for live GitHub stats and shared categories.
When should I choose AutoAudit over Agent-Reach?
Choose AutoAudit over Agent-Reach when AutoAudit is primarily HTML; Agent-Reach is Python; Tags unique to AutoAudit: cyber-security, fine-tuning, gpt, html; Also covers Model Training.
When should I choose Agent-Reach over AutoAudit?
Choose Agent-Reach over AutoAudit when Agent-Reach is primarily Python; AutoAudit is HTML; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents, Developer Tools.
When should I avoid AutoAudit?
Last GitHub push was 499 days ago (dormant maintenance, Feb 28, 2025). Validate activity before betting a new project on AutoAudit. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
When should I avoid Agent-Reach?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is AutoAudit or Agent-Reach more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 355). Stars measure visibility, not whether either tool fits your constraints.
Are AutoAudit and Agent-Reach open source?
Yes - both are open-source projects on GitHub (AutoAudit: MIT, Agent-Reach: MIT).
Where can I find alternatives to AutoAudit or Agent-Reach?
GraphCanon lists graph-backed alternatives at AutoAudit alternatives and Agent-Reach alternatives (AutoAudit markdown twin, Agent-Reach 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, AutoAudit or Agent-Reach?
AutoAudit: Dormant. Agent-Reach: 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 AutoAudit and Agent-Reach?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AutoAudit trust report; Agent-Reach trust report.