Home/Compare/do-not-answer vs Agent-Reach

Comparison

do-not-answer vs Agent-Reach

Verdict

Pick do-not-answer when do-not-answer is primarily Jupyter Notebook; Agent-Reach is Python; pick Agent-Reach when agent-Reach is primarily Python; do-not-answer is Jupyter Notebook.

Markdown twin · do-not-answer alternatives · Agent-Reach alternatives

GraphCanon updated today

do-not-answer logo

do-not-answer

Libr-AI/do-not-answer

334pushed Jun 7, 2024
vs
Agent-Reach logo

Agent-Reach

Panniantong/Agent-Reach

55kpushed Jul 10, 2026

Trust & integrity

Signaldo-not-answerAgent-Reach
Maintenance
Dormant (764d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No MCP manifest
As of today · mcp_manifest

Tagline

do-not-answer
Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs
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

do-not-answer
334
Agent-Reach
55k

Forks

do-not-answer
29
Agent-Reach
4.5k

Open issues

do-not-answer
0
Agent-Reach
144

Language

do-not-answer
Jupyter Notebook
Agent-Reach
Python

Adopt for

do-not-answer
-
Agent-Reach
-

Persona

do-not-answer
-
Agent-Reach
-

Runtime

do-not-answer
-
Agent-Reach
-

License

do-not-answer
Apache-2.0
Agent-Reach
MIT

Last pushed

do-not-answer
Jun 7, 2024
Agent-Reach
Jul 10, 2026

Categories

do-not-answer
Evaluation & Observability, LLM Frameworks
Agent-Reach
AI Agents, Developer Tools, LLM Frameworks

Trust and health

Maintenance

do-not-answer
Dormant (18%)
Agent-Reach
Very active (96%)

Days since push

do-not-answer
764d
Agent-Reach
0d

Open issues (now)

do-not-answer
0
Agent-Reach
144

Owner type

do-not-answer
Organization
Agent-Reach
User

Security scan

do-not-answer
No lockfile
Agent-Reach
No MCP manifest

Full report

do-not-answer
Trust report
Agent-Reach
Trust report

Choose do-not-answer if…

  • do-not-answer is primarily Jupyter Notebook; Agent-Reach is Python.
  • License: do-not-answer is Apache-2.0, Agent-Reach is MIT.
  • Tags unique to do-not-answer: jupyter notebook.
  • Also covers Evaluation & Observability.

When NOT to use do-not-answer

  • Last GitHub push was 764 days ago (dormant maintenance, Jun 7, 2024). Validate activity before betting a new project on do-not-answer.
  • Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose Agent-Reach if…

  • Agent-Reach is primarily Python; do-not-answer is Jupyter Notebook.
  • License: Agent-Reach is MIT, do-not-answer is Apache-2.0.
  • 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: do-not-answer 334 · Agent-Reach 55k (synced Jul 11, 2026).

Common questions

What is the difference between do-not-answer and Agent-Reach?
do-not-answer: Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs. 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 do-not-answer over Agent-Reach?
Choose do-not-answer over Agent-Reach when do-not-answer is primarily Jupyter Notebook; Agent-Reach is Python; License: do-not-answer is Apache-2.0, Agent-Reach is MIT; Tags unique to do-not-answer: jupyter notebook; Also covers Evaluation & Observability.
When should I choose Agent-Reach over do-not-answer?
Choose Agent-Reach over do-not-answer when Agent-Reach is primarily Python; do-not-answer is Jupyter Notebook; License: Agent-Reach is MIT, do-not-answer is Apache-2.0; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents, Developer Tools.
When should I avoid do-not-answer?
Last GitHub push was 764 days ago (dormant maintenance, Jun 7, 2024). Validate activity before betting a new project on do-not-answer. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
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 do-not-answer or Agent-Reach more popular on GitHub?
Agent-Reach has more GitHub stars (54,715 vs 334). Stars measure visibility, not whether either tool fits your constraints.
Are do-not-answer and Agent-Reach open source?
Yes - both are open-source projects on GitHub (do-not-answer: Apache-2.0, Agent-Reach: MIT).
Where can I find alternatives to do-not-answer or Agent-Reach?
GraphCanon lists graph-backed alternatives at do-not-answer alternatives and Agent-Reach alternatives (do-not-answer 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, do-not-answer or Agent-Reach?
do-not-answer: 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 do-not-answer and Agent-Reach?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: do-not-answer trust report; Agent-Reach trust report.