Is Auto claude code research in sleep safe to use?

Auto claude code research in sleep has an HVTrust score of 56.6/100 (Grade C), ranked #139 of 351 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for Auto claude code research in sleep?

Auto claude code research in sleep scores 56.6/100 on HVTracker's evidence-weighted HVTrust scale. It has 16.7k GitHub stars and is categorized under Agent Skills.

Auto claude code research in sleep

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

ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.

Agent Skills Python Listed MIT

Is Auto claude code research in sleep safe? Promising trust profile, but some evidence still deserves review.

OSSF Scorecard 3.8 / 10

Provenance None

Signed commits 24%

Last push 8d ago

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In detail: Auto claude code research in sleep scores 56.6/100 (Grade C), ranked #139 of 351 tracked open-source AI agent projects, on evidence coverage C (2 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 3.8/10; 24% of recent commits are signed; last pushed 2026-09-18. Every point is earned from checkable signals — never paid placement. How scoring works →

How Auto claude code research in sleep compares in Agent Skills

#137 Sprite Gen 56.6 ±0
#138 Anti Slop 56.6 ±0
#139 Auto claude code research in sleep 56.6 this agent
#140 Okf Skills 56.5 −0.1
#141 Taste Skill 56.4 −0.2

Bars show each HVTrust score; the tick marks Auto claude code research in sleep’s 56.6.

Where the 56.6 comes from

HVTrust dimensions vs the Agent Skills average

56.6 / 100 · 100.0% confidence

Auto claude code research in sleep Agent Skills average (351 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits

5.9 / 25

2.2 below avg 8.1

Identity / Provenance60% listing status · 40% build provenance

10.8 / 18

0.6 below avg 11.4

Transparency50% declared license · 50% OSSF Scorecard

11.7 / 17

0.5 below avg 12.2

Maintenance60% last-push freshness · 40% commit activity

18.4 / 20

4.2 above avg 14.2

AdoptionLog-scaled stars · package downloads

10.1 / 20

1.1 above avg 9.0

Quick Trust Read

What Would Improve It

Publish package provenance or release attestations for stronger supply-chain evidence.

Recent Changes

2026-09-25

Rank Moved

Rank dropped 17 spots (#122 → #139)

2026-09-23

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-23

Provider Added

Runtime surface grew — new detected provider dependencies: Anthropic, Google Gemini, OpenAI

Maintainer Checklist

Raise Scorecard signals Current OSSF Scorecard is 3.8/10. Tighten the weakest checks to improve public safety evidence.

Publish provenance Add package provenance or release attestations so users can verify where shipped artifacts came from.

Increase signed commits Raise the share of verified-signed commits to make maintainer identity and release history easier to trust.

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85.6

Activity sub-score · out of 100

#139

In Agent Skills

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade C reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage C is separate — it grades how many independent signal types back the score (2 of 5), so a high score on thin evidence stays visible. Full methodology →

Rank Trend

2026-08-11 2026-09-26

Activity & Reach

Stars

16.7k

Forks

1.4k

Last Push

2026-09-18

8 days ago

Commits (4 wk)

Downloads (7d)

—

HN mentions (30d)

—

Open Issues

Rank Change

was #139

Analysis

Activity Inputs

85.6 / 100

StarsRepository reach

25.3 / 30

FreshnessLast push recency

23.9 / 25

ActivityRecent commits

21.6 / 25

CommunityFork signal

14.7 / 20

Supply Chain Trust

Package Provenance

None

No package attestations found

OSSF Scorecard

3.8 / 10

OpenSSF Scorecard · scanned Sep 24, 2026

Signed Commits

24%

of last 100 commits verified

Binary-Artifacts 10

Branch-Protection 0

CI-Tests 0

CII-Best-Practices 0

Code-Review 0

Contributors 10

Dangerous-Workflow 10

Dependency-Update-Tool 0

Fuzzing 0

License 10

Maintained 10

Packaging -1

Pinned-Dependencies 0

SAST 0

Security-Policy 0

Signed-Releases 0

Token-Permissions 0

Vulnerabilities 10

Common questions about Auto claude code research in sleep

Auto claude code research in sleep has a mixed signal profile. Some trust indicators are present, others are missing. Whether it is safe for your use case depends on which gaps matter to you — review the breakdown below before adopting in production.

Does Auto claude code research in sleep publish package provenance?

No published build provenance is currently detected for Auto claude code research in sleep. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.

Does Auto claude code research in sleep have an OpenSSF Scorecard?

Auto claude code research in sleep has an OpenSSF Scorecard score of 3.8/10. The Scorecard checks for branch protection, signed releases, dependency updates, fuzzing, code review, and other supply-chain hygiene items. See the full check breakdown on this page.

Is Auto claude code research in sleep actively maintained?

Maintained. Last push was 8 days ago.

What license does Auto claude code research in sleep use?

Auto claude code research in sleep ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.

Are Auto claude code research in sleep's commits signed?

24% of the last 100 commits to Auto claude code research in sleep are verified-signed (GPG, SSH, S/MIME, or GitHub's signing flow). Signed commits help confirm that code was authored by who the commit claims.

Not a safety endorsement. HVTracker describes what public signals show, not whether a project is safe for your use case. Run your own security review before adopting in production.

AI agent surface

MCP, providers, tool surface

Scored in HVTrust

These runtime-trust fields — detected from public repo docs and manifests — contribute a bounded adjustment to this project's HVTrust score alongside supply-chain evidence. The exact values each field can add or subtract are documented in the methodology → Compare this surface across every listed agent in the capability matrix →

MCP Server Support

high confidence

Implemented

Auto claude code research in sleep appears to expose MCP server capabilities.

Detailed evidence is not shown in the public view.

External Service Dependencies

high confidence

3 detected

Public provider/service dependencies detected.

Credential signal: API keys or service config markers documented.

Tool / Plugin Surface

high confidence

Declared

Declared plugin/integration surface detected.

Detailed evidence is not shown in the public view.

Package Provenance Drift

N/A

No package source configured

Detailed evidence is not shown in the public view.

MCP signal live
External deps live
Tool / plugin surface live
Package provenance drift live

How this surface has changed

Detected changes to Auto claude code research in sleep's runtime surface and supply-chain posture, from daily public-signal snapshots. A change here means our detectors see something different — a genuinely changed capability, or better evidence of an existing one.

2026-09-23

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-23

Provider Added

Runtime surface grew — new detected provider dependencies: Anthropic, Google Gemini, OpenAI

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-16

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-16

Provider Added

Runtime surface grew — new detected provider dependency: Anthropic

Maintain Auto claude code research in sleep?

For maintainers

HVTrust scores Auto claude code research in sleep from public signals only — we never contact maintainers first. If a signal is wrong, stale, or missing (provenance you publish, a Scorecard you run, signed releases), tell us and we'll review it. Corrections are public and tracked on GitHub.

Submit a correction → Add the trust badge

Reputation Timeline

Signal history

2026-09-25

Rank Moved

Rank dropped 17 spots (#122 → #139)

2026-09-23

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-23

Provider Added

Runtime surface grew — new detected provider dependencies: Anthropic, Google Gemini, OpenAI

2026-09-23

Mcp Status Changed

Detected MCP server support changed: none → implemented

2026-09-23

Grade Changed

Trust grade D → C

2026-09-23

Rank Moved

Rank dropped 65 spots (#54 → #119)

2026-09-23

HVTrust Changed

HVTrust up 9.3pts (48.0 → 57.3)

2026-09-22

Newly Listed

First tracked at rank #54

2026-09-21

Removed From Active Tracking

Removed from active tracking

2026-09-16

Tool Surface Changed

Detected tool/plugin surface changed: none → declared

2026-09-16

Provider Added

Runtime surface grew — new detected provider dependency: Anthropic

2026-09-05

Rank Moved

Rank dropped 17 spots (#69 → #86)

2026-08-30

Scorecard Added

OSSF Scorecard: 4.1/10

2026-08-30

Grade Changed

Trust grade D → C

2026-08-30

Rank Moved

Rank rose 149 spots (#199 → #50)

2026-08-30

HVTrust Changed

HVTrust up 33.2pts (25.2 → 58.4)

2026-08-29

Rank Moved

Rank dropped 33 spots (#166 → #199)

2026-08-28

Rank Moved

Rank dropped 26 spots (#140 → #166)

2026-08-27

Rank Moved

Rank dropped 21 spots (#119 → #140)

2026-08-26

Rank Moved

Rank dropped 65 spots (#54 → #119)

2026-08-11

Newly Listed

First tracked at rank #48

GitHub →

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For maintainers

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Other agents in Agent Skills

Data sources
GitHub REST API (repo, commits, stars, forks, license) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.3 · Raw JSON