Giskard

🐢 Open-Source Evaluation & Testing library for LLM Agents

Observability & Evaluation Python Grade B Listed Apache-2.0
Compare → Suggest correction
Listing state
Listed
HVTrust
70.0/100 · Grade B
Evidence coverage
Grade A · 4/5 signals
Last push
2026-07-10 · 1d ago
Recent change
No recent signal change

Is Giskard safe? Giskard scores 70.0/100 (Grade B), ranked #83 of 328 tracked open-source AI agent projects, on evidence coverage A (4 of 5 independent signal types). The public evidence: no package-provenance attestation found; OSSF Scorecard rates its supply-chain practices 7.0/10; 84% of recent commits are signed; last pushed 2026-07-10. Every point is earned from checkable signals — never paid placement. How scoring works →

Quick Trust Read

Verdict
Promising trust profile, but some evidence still deserves review.
70.0/100 · Grade B
Strongest Signal
Maintenance
18.5/20
Weakest Signal
Safety / Integrity
13.0/25
What Would Improve It
Publish package provenance or release attestations for stronger supply-chain evidence.
Maintainer Checklist
Publish provenance Add package provenance or release attestations so users can verify where shipped artifacts came from.
80.3
Activity Score · out of 100
70.0
HVTrust Score · out of 100
#83
Global Rank · of 328
#8

How to read this: HVTrust (0–100) weighs supply-chain signals (provenance, OSSF Scorecard, signed commits, open license) alongside real-world adoption. Grade B reflects the trust score band: A ≥ 80, B ≥ 65, C ≥ 50, D < 50. Evidence coverage A is separate — it grades how many independent signal types back the score (4 of 5), so a high score on thin evidence stays visible. Full methodology →

Signals refreshed 2026-07-11 04:00 UTC · Repo last pushed yesterday

Rank Trend

2026-07-05 2026-07-11

Activity & Reach

Stars
5.5k
Forks
485
Last Push
2026-07-10
yesterday
Commits (4 wk)
42
Downloads (7d)
6,541
pypi
HN mentions (30d)
1
Open Issues
28
Rank Change
▲1
was #84

Analysis

HVTrust Dimensions

70.0 / 100 · 100.0% confidence
Safety / IntegrityOSSF, provenance, signatures
13.0 / 25
Identity / ProvenanceListing and build link
10.8 / 18
TransparencyLicense and public checks
14.4 / 17
MaintenanceFreshness and commits
18.5 / 20
AdoptionStars and downloads
14.1 / 20

Activity Inputs

80.3 / 100
StarsRepository reach
22.4 / 30
FreshnessLast push recency
24.9 / 25
ActivityRecent commits
20.4 / 25
CommunityFork signal
12.5 / 20

Supply Chain Trust

Package Provenance
None
No package attestations found
OSSF Scorecard
7.0 / 10
OpenSSF Scorecard · scanned Jul 10, 2026
Signed Commits
84%
of last 100 commits verified
Binary-Artifacts 10
Branch-Protection 8
CI-Tests 10
CII-Best-Practices 0
Code-Review 8
Contributors 10
Dangerous-Workflow 0
Dependency-Update-Tool 10
Fuzzing 0
License 10
Maintained 10
Packaging -1
Pinned-Dependencies 10
SAST 10
Security-Policy 10
Signed-Releases 0
Token-Permissions 10
Vulnerabilities 8

Is Giskard safe?

Giskard 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 Giskard publish package provenance?
No published build provenance is currently detected for Giskard. This is common for open-source projects but means consumers cannot independently verify that the package on the registry matches the GitHub source.
Does Giskard have an OpenSSF Scorecard?
Giskard has an OpenSSF Scorecard score of 7.0/10. 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 Giskard actively maintained?
Actively maintained. The repository was pushed to within the last 1 day(s).
What license does Giskard use?
Giskard ships under Apache-2.0. A declared, OSI-approved license is one of the transparency signals HVTrust scores.
Are Giskard's commits signed?
84% of the last 100 commits to Giskard 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.

Ranked neighbours in Observability & Evaluation

AI agent 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
medium confidence
1 tags
Broad capability areas detected.
  • code
Detailed evidence is not shown in the public view.
Package Provenance Drift
low confidence
Unknown
Package source metadata is missing or inconclusive
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 Giskard'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.

2026-06-05
Provider Added
Runtime surface grew — new detected provider dependencies: Anthropic, OpenAI

Maintain Giskard?

HVTrust scores Giskard 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

Score 2Rank 2HVTrust 2Listed 1Grade 1Scorecard 1Surface 1
2026-06-05
Provider Added
Runtime surface grew — new detected provider dependencies: Anthropic, OpenAI
2026-05-29
HVTrust Changed
HVTrust up 10.4pts (59.6 → 70.0)
2026-05-27
Scorecard Added
OSSF Scorecard: 6.8/10
2026-05-27
Grade Changed
Trust grade C → B
2026-05-27
Rank Moved
Rank rose 94 spots (#110 → #16)
2026-05-27
HVTrust Changed
HVTrust up 30.5pts (32.9 → 63.4)
2026-05-27
Activity Score Changed
Activity score up 21pts (60 → 81)
2026-05-26
Rank Moved
Rank dropped 94 spots (#16 → #110)
2026-05-26
Activity Score Changed
Activity score down 22pts (81 → 60)
2026-05-25
Newly Listed
First tracked at rank #16

Embed Badge Badge guide for maintainers →

HVTrust 70.0 Grade B
Markdown:
[![HVTrust](https://hvtracker.net/badge/giskard.svg)](https://hvtracker.net/agents/giskard)
HTML:
<a href="https://hvtracker.net/agents/giskard"><img src="https://hvtracker.net/badge/giskard.svg" alt="HVTrust"></a>

Other agents in Observability & Evaluation

Data sources
GitHub REST API (repo, commits, stars, forks, license) · PyPI / pypistats (downloads, provenance) · OpenSSF Scorecard CLI · Algolia HN Search API
Each agent's signals refresh once daily across 6 staggered batches. Methodology v4.2 · Raw JSON