Glebis Claude Skills
Collection of Claude Code skills for enhanced AI workflows
Is Glebis Claude Skills safe? Thin or incomplete trust evidence. Review carefully before production use.
Compare Glebis Claude Skills
How does it stack up against its Agent Skills neighbours?
Pick any agent to compare →In detail: Glebis Claude Skills scores 42.7/100 (Grade D), ranked #322 of 371 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 2.4/10; 10% of recent commits are signed; last pushed 2026-10-08. Every point is earned from checkable signals — never paid placement. How scoring works →
How Glebis Claude Skills could raise its score
Each line changes one public signal and recomputes with the live scoring function. The gains don't add up exactly, because the score is capped near the top.
- Raise the OSSF Scorecard from 2.4 to 9.0lowest checks: Branch-Protection 0, CII-Best-Practices 0, Code-Review 0 +13.9 → 56.6 C · #143 of 371
- Sign every commit10% signed today +4.5 → 47.2 D · #281 of 371
Chain of custody
Scanners check what the code says. This traces who ships Glebis Claude Skills and whether that has changed: from the source repository, through how changes are reviewed and released, to the code you run. These are the checks for OWASP ASI04 Agentic Supply Chain Vulnerabilities and, for skills, AST02 Supply Chain Compromise.
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Source Partly signed
github.com/glebis/claude-skills, MIT, last pushed 2026-10-08. 10% of the last 100 commits carry a verified signature; the rest can't be tied to a verified identity.
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Review and release Weak
OpenSSF Scorecard rates the repository's practices 2.4/10 (scanned Oct 10, 2026). The checks that decide who can get a change released:
- Code Review0
- Branch Protection0
- Signed Releasesn/a
- Dangerous Workflown/a
- Token Permissionsn/a
- Pinned Dependencies0
All 18 Scorecard checks
Binary-Artifacts 10Branch-Protection 0CI-Tests -1CII-Best-Practices 0Code-Review 0Contributors 0Dangerous-Workflow -1Dependency-Update-Tool 0Fuzzing 0License 10Maintained 10Packaging -1Pinned-Dependencies 0SAST 0Security-Policy 0Signed-Releases -1Token-Permissions -1Vulnerabilities 0 -
Published packages None
No registry package. Glebis Claude Skills is used from its repository, so what you run is whatever you check out: pin a release tag or commit.
Changes to this chain
- 2026-08-30 OSSF Scorecard: 2.4/10
Evidence behind this score
Coverage C: 2 of 5 independent evidence types found.
- GitHub repository data
- Package downloads (missing)
- Supply-chain checks
- Public actions (missing)
- Community mentions (missing)
Verify this score yourself
Every build re-issues Glebis Claude Skills’s score as an Ed25519-signed credential, valid for 7 days. You can check it offline against HVTracker’s published key; if anyone changes a number after signing, verification fails.
What this score doesn’t check
It covers who ships the code, not what the code does. It doesn’t read the skill’s instructions for injected instructions, watch runtime behaviour, or find bugs nobody has disclosed yet. For that, run a content scanner before you install it, such as Cisco Skill Scanner.
How Glebis Claude Skills compares in Agent Skills
- #320 Paperasse 42.7 ±0
- #321 Ip As Logo Skill 42.7 ±0
- #322 Glebis Claude Skills 42.7 this agent
- #323 Three.js Game Skills 42.3 −0.4
- #324 Story To Handdrawn Video 42.3 −0.4
Bars show each HVTrust score; the tick marks Glebis Claude Skills’s 42.7.
Where the 42.7 comes from
HVTrust dimensions vs the Agent Skills average
42.7 / 100 · 100.0% confidenceGlebis Claude Skills Agent Skills average (371 agents)
Quick Trust Read
How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade D 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
Activity & Reach
Analysis
Activity Inputs
54.1 / 100Common questions about Glebis Claude Skills
Does Glebis Claude Skills publish package provenance?
Does Glebis Claude Skills have an OpenSSF Scorecard?
Is Glebis Claude Skills actively maintained?
What license does Glebis Claude Skills use?
Are Glebis Claude Skills's commits signed?
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
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 signal live
- External deps live
- Tool / plugin surface live
- Package provenance drift live
Detected changes to Glebis Claude Skills'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.
Maintain Glebis Claude Skills?
For maintainers
HVTrust scores Glebis Claude Skills 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.
Reputation Timeline
Signal history
Embed Badge Badge guide for maintainers →
For maintainers
[](https://hvtracker.net/agents/glebis-claude-skills)
<a href="https://hvtracker.net/agents/glebis-claude-skills"><img src="https://hvtracker.net/badge/glebis-claude-skills.svg" alt="HVTrust"></a>
Other agents in Agent Skills
GitHub REST API (repo, commits, stars, forks, license) · OpenSSF Scorecard CLI
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.4 · Raw JSON