Comparison
Agent-Reach vs DS-1000
Verdict
Pick Agent-Reach when license: Agent-Reach is MIT, DS-1000 is CC-BY-SA-4.0; pick DS-1000 when license: DS-1000 is CC-BY-SA-4.0, Agent-Reach is MIT.
Markdown twin · Agent-Reach alternatives · DS-1000 alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | Agent-Reach | DS-1000 |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1d · github_public_v1 | Dormant (619d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal account As of 1d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No MCP manifest As of 1d · mcp_manifest | No lockfile As of today · none |
Tagline
- 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.
- DS-1000
- [ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".
Stars
- Agent-Reach
- 55k
- DS-1000
- 273
Forks
- Agent-Reach
- 4.5k
- DS-1000
- 31
Open issues
- Agent-Reach
- 144
- DS-1000
- 2
Language
- Agent-Reach
- Python
- DS-1000
- Python
Adopt for
- Agent-Reach
- -
- DS-1000
- -
Persona
- Agent-Reach
- -
- DS-1000
- -
Runtime
- Agent-Reach
- -
- DS-1000
- -
License
- Agent-Reach
- MIT
- DS-1000
- CC-BY-SA-4.0
Last pushed
- Agent-Reach
- Jul 10, 2026
- DS-1000
- Oct 30, 2024
Categories
- Agent-Reach
- AI Agents, Developer Tools, LLM Frameworks
- DS-1000
- Evaluation & Observability, LLM Frameworks, Model Training
Trust and health
Maintenance
- Agent-Reach
- Very active (96%)
- DS-1000
- Dormant (18%)
Days since push
- Agent-Reach
- 0d
- DS-1000
- 619d
Open issues (now)
- Agent-Reach
- 144
- DS-1000
- 2
Owner type
- Agent-Reach
- User
- DS-1000
- Organization
Security scan
- Agent-Reach
- No MCP manifest
- DS-1000
- No lockfile
Full report
- Agent-Reach
- Trust report
- DS-1000
- Trust report
Choose Agent-Reach if…
- License: Agent-Reach is MIT, DS-1000 is CC-BY-SA-4.0.
- 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.
Choose DS-1000 if…
- License: DS-1000 is CC-BY-SA-4.0, Agent-Reach is MIT.
- Tags unique to DS-1000: benchmark, code-generation, data-science, large-language-models.
- Also covers Evaluation & Observability, Model Training.
When NOT to use DS-1000
- Last GitHub push was 619 days ago (dormant maintenance, Oct 30, 2024). Validate activity before betting a new project on DS-1000.
- 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.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
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 11, 2026
- GitHub forks (Panniantong/Agent-Reach) · observed Jul 11, 2026
- Last push (Panniantong/Agent-Reach) · observed Jul 10, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (xlang-ai/DS-1000) · observed Jul 11, 2026
- GitHub forks (xlang-ai/DS-1000) · observed Jul 11, 2026
- Last push (xlang-ai/DS-1000) · observed Oct 30, 2024
- License file (CC-BY-SA-4.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Agent-Reach 55k · DS-1000 273 (synced Jul 11, 2026).
Common questions
- What is the difference between Agent-Reach and DS-1000?
- 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.. DS-1000: [ICML 2023] Data and code release for the paper "DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation".. See the comparison table for live GitHub stats and shared categories.
- When should I choose Agent-Reach over DS-1000?
- Choose Agent-Reach over DS-1000 when License: Agent-Reach is MIT, DS-1000 is CC-BY-SA-4.0; Tags unique to Agent-Reach: agent-infrastructure, ai-agent, ai-search, automation; Also covers AI Agents, Developer Tools.
- When should I choose DS-1000 over Agent-Reach?
- Choose DS-1000 over Agent-Reach when License: DS-1000 is CC-BY-SA-4.0, Agent-Reach is MIT; Tags unique to DS-1000: benchmark, code-generation, data-science, large-language-models; Also covers Evaluation & Observability, Model Training.
- 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.
- When should I avoid DS-1000?
- Last GitHub push was 619 days ago (dormant maintenance, Oct 30, 2024). Validate activity before betting a new project on DS-1000. 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. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is Agent-Reach or DS-1000 more popular on GitHub?
- Agent-Reach has more GitHub stars (54,715 vs 273). Stars measure visibility, not whether either tool fits your constraints.
- Are Agent-Reach and DS-1000 open source?
- Yes - both are open-source projects on GitHub (Agent-Reach: MIT, DS-1000: CC-BY-SA-4.0).
- Where can I find alternatives to Agent-Reach or DS-1000?
- GraphCanon lists graph-backed alternatives at Agent-Reach alternatives and DS-1000 alternatives (Agent-Reach markdown twin, DS-1000 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 DS-1000?
- Agent-Reach: Very active. DS-1000: Dormant. 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 DS-1000?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agent-Reach trust report; DS-1000 trust report.