Home/Compare/GSM-IC vs Auto-claude-code-research-in-sleep

Comparison

GSM-IC vs Auto-claude-code-research-in-sleep

Verdict

Pick GSM-IC if gSM-IC is a benchmark dataset that evaluates the distractibility of language models by introducing irrelevant context into grade-school math problems; pick Auto-claude-code-research-in-sleep if auto-claude-code-research-in-sleep provides specialized Markdown-based utilities for automating and enhancing autonomous ML research by connecting various models in an open framework.

Markdown twin · GSM-IC alternatives · Auto-claude-code-research-in-sleep alternatives

GraphCanon updated Sep 20, 2026

GSM-IC logo

GSM-IC

google-research-datasets/GSM-IC

★ 67pushed Feb 13, 2023
vs
Auto-claude-code-research-in-sleep logo

Auto-claude-code-research-in-sleep

wanshuiyin/Auto-claude-code-research-in-sleep

★ 16kpushed Sep 18, 2026

Trust & integrity

SignalGSM-ICAuto-claude-code-research-in-sleep
Maintenance
Archived (1312d since push)
As of Sep 18, 2026 · github_public_v1
Very active (1d since push)
As of Sep 20, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 20, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
No lockfile (source not queried)
As of Aug 23, 2026 · 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

GSM-IC
GSM-IC benchmark evaluates distractibility of language models with grade-school math problems and irrelevant context.
Auto-claude-code-research-in-sleep
Lightweight Markdown-only skills for autonomous ML research

Stars

GSM-IC
67
Auto-claude-code-research-in-sleep
16k

Forks

GSM-IC
2
Auto-claude-code-research-in-sleep
1.4k

Open issues

GSM-IC
1
Auto-claude-code-research-in-sleep
70

Language

GSM-IC
-
Auto-claude-code-research-in-sleep
Python

Adopt for

GSM-IC
GSM-IC is a benchmark dataset that evaluates the distractibility of language models by introducing irrelevant context into grade-school math problems.
Auto-claude-code-research-in-sleep
Auto-claude-code-research-in-sleep provides specialized Markdown-based utilities for automating and enhancing autonomous ML research by connecting various models in an open framework.

Persona

GSM-IC
-
Auto-claude-code-research-in-sleep
-

Runtime

GSM-IC
-
Auto-claude-code-research-in-sleep
-

License

GSM-IC
License information is not provided in the repository.
Auto-claude-code-research-in-sleep
MIT License, allowing for broad usage without restrictions on commercial use.

Last pushed

GSM-IC
Feb 13, 2023
Auto-claude-code-research-in-sleep
Sep 18, 2026

Categories

GSM-IC
Evaluation & Observability
Auto-claude-code-research-in-sleep
AI Agents, Developer Tools, Evaluation & Observability

Trust and health

Maintenance

GSM-IC
Archived (8%)
Auto-claude-code-research-in-sleep
Very active (96%)

Days since push

GSM-IC
1312d
Auto-claude-code-research-in-sleep
1d

Archived on GitHub

GSM-IC
Yes
Auto-claude-code-research-in-sleep
No

Open issues (now)

GSM-IC
1
Auto-claude-code-research-in-sleep
70

Stars delta

GSM-IC
0 (30d)
Auto-claude-code-research-in-sleep
+2.5k (30d)

Open issues delta

GSM-IC
0 (30d)
Auto-claude-code-research-in-sleep
+10 (30d)

Owner type

GSM-IC
Organization
Auto-claude-code-research-in-sleep
User

Full report

Auto-claude-code-research-in-sleep
Trust report

Choose GSM-IC if…

  • Pricing: Pricing details are not available..
  • Requirements: The dataset is derived from GSM8K and includes irrelevant context in problem descriptions to test the distractibility of language models..
  • Tags unique to GSM-IC: arithmetic reasoning, benchmark, distractibility, grade-school math.
  • Use GSM-IC when you need to assess how well a language model can focus on relevant information in arithmetic reasoning tasks, especially when faced with distracting irrelevant context.

When NOT to use GSM-IC

  • Avoid GSM-IC if your evaluation focuses on the model's ability to solve math problems without any form of distraction or if the context is always assumed to be relevant.
  • Do not use GSM-IC if your primary interest is in evaluating the model's performance on pure arithmetic tasks without the added complexity of irrelevant context.

Choose Auto-claude-code-research-in-sleep if…

  • Pricing: Free to use under MIT license with no explicit pricing model indicated, though users might incur costs based on the AI models and services they choose to integrate..
  • Requirements: Compatibility with diverse language model agents without requiring lock-in or specific frameworks; Utilizes Markdown for skills, aiming at a lightweight automation layer on top of ML research tasks.
  • Tags unique to Auto-claude-code-research-in-sleep: ai research, autonomous-agent, idea-generation, ml-research.
  • Also covers AI Agents, Developer Tools.
  • When you are looking to streamline idea discovery, experiment automation, and cross-model review loops specifically within the context of Python programming for machine learning research

When NOT to use Auto-claude-code-research-in-sleep

  • If you require a solution that is tightly integrated with a specific AI development platform or requires the use of proprietary models
  • When your research workflow demands real-time data analysis and visualization tools that Auto-claude-code-research-in-sleep does not directly support

Explore

Sources

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

GitHub stars on cards: GSM-IC 67 · Auto-claude-code-research-in-sleep 16k (synced Sep 20, 2026).

Common questions

What is the difference between GSM-IC and Auto-claude-code-research-in-sleep?
GSM-IC: GSM-IC benchmark evaluates distractibility of language models with grade-school math problems and irrelevant context.. Auto-claude-code-research-in-sleep: Lightweight Markdown-only skills for autonomous ML research. See the comparison table for live GitHub stats and shared categories.
When should I choose GSM-IC over Auto-claude-code-research-in-sleep?
Choose GSM-IC over Auto-claude-code-research-in-sleep when Pricing: Pricing details are not available.; Requirements: The dataset is derived from GSM8K and includes irrelevant context in problem descriptions to test the distractibility of language models.; Tags unique to GSM-IC: arithmetic reasoning, benchmark, distractibility, grade-school math; Use GSM-IC when you need to assess how well a language model can focus on relevant information in arithmetic reasoning tasks, especially when faced with distracting irrelevant context.
When should I choose Auto-claude-code-research-in-sleep over GSM-IC?
Choose Auto-claude-code-research-in-sleep over GSM-IC when Pricing: Free to use under MIT license with no explicit pricing model indicated, though users might incur costs based on the AI models and services they choose to integrate.; Requirements: Compatibility with diverse language model agents without requiring lock-in or specific frameworks; Utilizes Markdown for skills, aiming at a lightweight automation layer on top of ML research tasks; Tags unique to Auto-claude-code-research-in-sleep: ai research, autonomous-agent, idea-generation, ml-research; Also covers AI Agents, Developer Tools; When you are looking to streamline idea discovery, experiment automation, and cross-model review loops specifically within the context of Python programming for machine learning research.
When should I avoid GSM-IC?
Avoid GSM-IC if your evaluation focuses on the model's ability to solve math problems without any form of distraction or if the context is always assumed to be relevant. Do not use GSM-IC if your primary interest is in evaluating the model's performance on pure arithmetic tasks without the added complexity of irrelevant context.
When should I avoid Auto-claude-code-research-in-sleep?
If you require a solution that is tightly integrated with a specific AI development platform or requires the use of proprietary models When your research workflow demands real-time data analysis and visualization tools that Auto-claude-code-research-in-sleep does not directly support
Is GSM-IC or Auto-claude-code-research-in-sleep more popular on GitHub?
Auto-claude-code-research-in-sleep has more GitHub stars (16,383 vs 67). Stars measure visibility, not whether either tool fits your constraints.
Are GSM-IC and Auto-claude-code-research-in-sleep open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to GSM-IC or Auto-claude-code-research-in-sleep?
GraphCanon lists graph-backed alternatives at GSM-IC alternatives and Auto-claude-code-research-in-sleep alternatives (GSM-IC markdown twin, Auto-claude-code-research-in-sleep 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, GSM-IC or Auto-claude-code-research-in-sleep?
GSM-IC: Archived. Auto-claude-code-research-in-sleep: 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 GSM-IC and Auto-claude-code-research-in-sleep?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: GSM-IC trust report; Auto-claude-code-research-in-sleep trust report.

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