Is Agent Skills for Context Engineering safe to use?

Agent Skills for Context Engineering has an HVTrust score of 50.7/100 (Grade C), ranked #229 of 351 tracked AI agent projects. This score reflects verifiable supply-chain integrity, transparency, maintenance, and adoption signals.

What is the trust score for Agent Skills for Context Engineering?

Agent Skills for Context Engineering scores 50.7/100 on HVTracker's evidence-weighted HVTrust scale. It has 18.0k GitHub stars and is categorized under Agent Skills.

Agent Skills for Context Engineering

muratcankoylan/Agent-Skills-for-Context-Engineering

A comprehensive collection of Agent Skills for context engineering, multi-agent architectures, and production agent systems. Use when building, optimizing, or debugging agent systems that require effective context management.

Agent Skills Python Listed MIT

Is Agent Skills for Context Engineering safe? Thin or incomplete trust evidence. Review carefully before production use.

OSSF Scorecard 3.6 / 10

Provenance None

Signed commits 69%

Last push 15d ago

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In detail: Agent Skills for Context Engineering scores 50.7/100 (Grade C), ranked #229 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 3.6/10; 69% of recent commits are signed; last pushed 2026-09-11. Every point is earned from checkable signals — never paid placement. How scoring works →

How Agent Skills for Context Engineering compares in Agent Skills

#227 Claude Code Skills 50.8 +0.1
#228 Wondelai Skills 50.8 +0.1
#229 Agent Skills for Context Engineering 50.7 this agent
#230 Claude OSINT 50.6 −0.1
#231 Itr Wala 50.6 −0.1

Bars show each HVTrust score; the tick marks Agent Skills for Context Engineering’s 50.7.

Where the 50.7 comes from

HVTrust dimensions vs the Agent Skills average

50.7 / 100 · 100.0% confidence

Agent Skills for Context Engineering Agent Skills average (351 agents)

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

7.9 / 25

in line with 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

11.6 / 17

0.6 below avg 12.2

Maintenance60% last-push freshness · 40% commit activity

11.0 / 20

3.2 below avg 14.2

AdoptionLog-scaled stars · package downloads

10.2 / 20

1.2 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 21 spots (#208 → #229)

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, OpenAI

Maintainer Checklist

Raise Scorecard signals Current OSSF Scorecard is 3.6/10. 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.

Compare with another agent Get email alerts for Agent Skills for Context Engineering View Agent Skills Report missing data

63.2

Activity sub-score · out of 100

#229

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

18.0k

Forks

1.5k

Last Push

2026-09-11

15 days ago

Commits (4 wk)

Downloads (7d)

—

HN mentions (30d)

—

Open Issues

Rank Change

was #229

Analysis

Activity Inputs

63.2 / 100

StarsRepository reach

25.5 / 30

FreshnessLast push recency

22.9 / 25

ActivityRecent commits

0.0 / 25

CommunityFork signal

14.8 / 20

Supply Chain Trust

Package Provenance

None

No package attestations found

OSSF Scorecard

3.6 / 10

OpenSSF Scorecard · scanned Sep 25, 2026

Signed Commits

69%

of last 100 commits verified

Binary-Artifacts 10

Branch-Protection 3

CI-Tests 8

CII-Best-Practices 0

Code-Review 2

Contributors 0

Dangerous-Workflow 10

Dependency-Update-Tool 0

Fuzzing 0

License 10

Maintained 10

Packaging -1

Pinned-Dependencies 6

SAST 0

Security-Policy 0

Signed-Releases 0

Token-Permissions 0

Vulnerabilities 0

Common questions about Agent Skills for Context Engineering

Public trust evidence for Agent Skills for Context Engineering is thin: several supply-chain signals are missing or weak. This does not mean the project is unsafe — it means an outside observer cannot easily verify the usual integrity checks. Treat with extra scrutiny.

Does Agent Skills for Context Engineering publish package provenance?

No published build provenance is currently detected for Agent Skills for Context Engineering. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.

Does Agent Skills for Context Engineering have an OpenSSF Scorecard?

Agent Skills for Context Engineering has an OpenSSF Scorecard score of 3.6/10. 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 Agent Skills for Context Engineering actively maintained?

Maintained. Last push was 15 days ago.

What license does Agent Skills for Context Engineering use?

Agent Skills for Context Engineering ships under MIT. A declared, OSI-approved license is one of the transparency signals HVTrust scores.

Are Agent Skills for Context Engineering's commits signed?

69% of the last 100 commits to Agent Skills for Context Engineering 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

None detected

No MCP server signal detected.

Detailed evidence is not shown in the public view.

External Service Dependencies

high confidence

2 detected

Public provider/service dependencies detected.

Credential signal: No explicit API-key/config marker detected.

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 Agent Skills for Context Engineering'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, OpenAI

Maintain Agent Skills for Context Engineering?

For maintainers

HVTrust scores Agent Skills for Context Engineering 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 21 spots (#208 → #229)

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, OpenAI

2026-09-23

Grade Changed

Trust grade D → C

2026-09-23

Rank Moved

Rank dropped 54 spots (#153 → #207)

2026-09-23

HVTrust Changed

HVTrust up 11.0pts (39.9 → 50.9)

2026-09-22

Newly Listed

First tracked at rank #153

2026-09-21

Removed From Active Tracking

Removed from active tracking

2026-09-11

Rank Moved

Rank rose 13 spots (#198 → #185)

2026-09-09

Rank Moved

Rank dropped 44 spots (#148 → #192)

2026-09-09

HVTrust Changed

HVTrust down 3.9pts (54.2 → 50.3)

2026-09-09

Activity Score Changed

Activity score down 12pts (74 → 62)

2026-09-07

Rank Moved

Rank dropped 10 spots (#137 → #147)

2026-09-05

Rank Moved

Rank dropped 12 spots (#120 → #132)

2026-09-01

Rank Moved

Rank dropped 12 spots (#91 → #103)

2026-08-31

Scorecard Added

OSSF Scorecard: 3.6/10

2026-08-31

Grade Changed

Trust grade D → C

2026-08-31

Rank Moved

Rank rose 160 spots (#251 → #91)

2026-08-31

HVTrust Changed

HVTrust up 31.8pts (23.3 → 55.1)

2026-08-30

Rank Moved

Rank dropped 28 spots (#223 → #251)

2026-08-29

Rank Moved

Rank dropped 29 spots (#194 → #223)

2026-08-28

Rank Moved

Rank dropped 22 spots (#172 → #194)

2026-08-27

Rank Moved

Rank dropped 17 spots (#155 → #172)

2026-08-26

Rank Moved

Rank dropped 83 spots (#72 → #155)

2026-08-11

Newly Listed

First tracked at rank #60

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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