Acontext

Agent Skills as a Memory Layer

Agent Skills JavaScript Grade D Listed Apache-2.0
17.4/100
Rank #132 of 148
Compare Acontext

Thin or incomplete trust evidence. Review carefully before production use.

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Listing state
Listed
Evidence coverage
Grade D · 1/5 signals
Last push
2026-07-14 · 29d ago
Recent change
New

Is Acontext safe? Acontext scores 17.4/100 (Grade D), ranked #132 of 148 tracked open-source AI agent projects, on evidence coverage D (1 of 5 independent signal types). The public evidence: no package-provenance attestation found; no OSSF Scorecard result yet; 59% of recent commits are signed; last pushed 2026-07-14. Every point is earned from checkable signals — never paid placement. How scoring works →

Ranked neighbours in Agent Skills

Quick Trust Read

What Would Improve It
Add or improve OSSF Scorecard coverage so safety checks are easier to verify.
Recent Changes
2026-08-11
Newly Listed
First tracked at rank #133
Maintainer Checklist
Add Scorecard coverage Expose the repository to OpenSSF Scorecard checks so supply-chain posture is easier to verify.
Publish provenance Add package provenance or release attestations so users can verify where shipped artifacts came from.
54.2
Activity sub-score · out of 100
#132

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 D is separate — it grades how many independent signal types back the score (1 of 5), so a high score on thin evidence stays visible. Full methodology →

Signals refreshed 2026-08-12 05:02 UTC · Repo last pushed 29 days ago

Rank Trend

2026-08-11 2026-08-12

Activity & Reach

Stars
3.7k
Forks
333
Last Push
2026-07-14
29 days ago
Commits (4 wk)
0
Downloads (7d)
HN mentions (30d)
Open Issues
14
Rank Change
▲1
was #133

Analysis

HVTrust Dimensions vs Agent Skills

17.4 / 100 · 50.0% confidence

Acontext Agent Skills average (148 agents)

Safety / Integrity50% OSSF Scorecard · 30% provenance · 20% signed commits
2.9 / 25
in line with avg 2.7
Identity / Provenance60% listing status · 40% build provenance
10.8 / 18
0.5 below avg 11.3
Transparency50% declared license · 50% OSSF Scorecard
8.5 / 17
in line with avg 8.5
Maintenance60% last-push freshness · 40% commit activity
10.1 / 20
5.0 below avg 15.1
AdoptionLog-scaled stars · package downloads
8.6 / 20
0.6 below avg 9.2

Activity Inputs

54.2 / 100
StarsRepository reach
21.4 / 30
FreshnessLast push recency
21.0 / 25
ActivityRecent commits
0.0 / 25
CommunityFork signal
11.7 / 20

Supply Chain Trust

Package Provenance
None
No package attestations found
OSSF Scorecard
Not available
Signed Commits
59%
of last 100 commits verified

Is Acontext safe?

Public trust evidence for Acontext 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 Acontext publish package provenance?
No published build provenance is currently detected for Acontext. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.
Does Acontext have an OpenSSF Scorecard?
No OpenSSF Scorecard data is currently published for Acontext. Maintainers can enable the Scorecard GitHub Action to get a public score; without it, automated supply-chain hygiene is harder for outsiders to verify.
Is Acontext actively maintained?
Maintained. Last push was 29 days ago.
What license does Acontext use?
Acontext ships under Apache-2.0. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are Acontext's commits signed?
59% of the last 100 commits to Acontext 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
medium confidence
Declared
MCP support appears present, but direct server implementation is less certain.
Detailed evidence is not shown in the public view.
External Service Dependencies
high confidence
4 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.
  • database
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

Maintain Acontext?

For maintainers

HVTrust scores Acontext 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
Listed 1
2026-08-11
Newly Listed
First tracked at rank #133

Embed Badge Badge guide for maintainers →

For maintainers
HVTrust 17.4 Grade D
Markdown:
[![HVTrust](https://hvtracker.net/badge/acontext.svg)](https://hvtracker.net/agents/acontext)
HTML:
<a href="https://hvtracker.net/agents/acontext"><img src="https://hvtracker.net/badge/acontext.svg" alt="HVTrust"></a>

Other agents in Agent Skills

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