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Tiger3807861189/J-Space-Cognition-Suite

J-Space Cognition Suite — a model-agnostic inference-time control suite for deep reasoning, long-horizon work, verification, and recovery. Based on Anthropic's J-space global workspace research.

  • View repository ↗
  • Python
  • ★ 2,958
  • commit b2023124a1fa
  • scored 2026-11-14
  • scoring prov-4+qual-2+sec-2

AI provenance

0%

possible

Confidence
65%
Coverage
100%

Estimated share of AI-generated code. Explicit attribution is a lower bound.

Code quality

67/100

adequate

Confidence
90%
Coverage
100%

Complexity, duplication, lint density, tests, CI, docs and review process.

Security

75/100

adequate

Confidence
85%
Coverage
100%

Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.

Scores

Pillar Score Signal Confidence Coverage
AI provenance (estimated AI-generated share) 0 possible 65% 100%
Code quality 67 adequate 90% 100%
Security 75 adequate 85% 100%

AI provenance

Weak signals consistent with AI-assisted development.

  • Explicitly attributed share (lower bound): 0.0%

  • Unattributed share in AI-consistent velocity bursts: 42.5%

  • Estimated AI-generated share: 0.0%

  • Stylometry index: 0.22 per 1,000 lines (narrated steps 0, placeholders 0, assistant phrasing 0, emoji 1). Reported as a signal, not scored.

Month Lines added Attributed to AI
2026-08 2,600 0%
2026-09 2,338 0%

Evidence

  • 2,100 lines of first-party code in ~4.0h (525 lines/hour, 1 commit session) (b2023124a1fa)

AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.

Code quality

Code quality is adequate: test-to-source ratio 0.84, CI runs tests; 43% of function code in complex or long functions; 1% duplicated lines. Weakest area: complexity.

Area Score
Complexity (lizard) 27
Duplication 95
Code smells (Opengrep) 52
Tests and CI 90
Documentation 80
Type safety 40
Process (Scorecard review/maintenance) n/a
  • Functions: 81; mean complexity 9.5, 90th percentile 14; 6 complex and 3 long functions
  • Duplicated lines: 0.8% of 1,799 compared
  • Tests: 1,917 test lines for 2,278 source lines (ratio 0.84); CI test commands: unittest; 25% of recent source commits also change tests
  • Docs missing or thin: changelog

Most complex functions:

Security

Security posture is adequate: 1 high-severity SAST findings; 2 high-severity workflow issues. Weakest area: posture.

Area Score
Secrets (gitleaks, tree + history) 100
Static analysis (Opengrep) 89
Vulnerable dependencies (OSV) n/a
CI workflows (zizmor) 63
Posture (policy, updates, signing, lockfiles) 0
OpenSSF Scorecard n/a
  • Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits

Top findings

Severity Finding Location
high opengrep/python.lang.security.audit.dangerous-subprocess-use-audit: Detected subprocess function 'run' without a static string. If this data can be controlled by a malicious actor, it may be an instance of command injection. Audit the use of this call to ensure it is not controllable by an external resource. You may consider using 'shlex.escape()'. [confidence low] j-space/scripts/host_bridge.py:27
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/verify.yml:18
high zizmor/unpinned-uses: unpinned action reference [confidence high] .github/workflows/verify.yml:19
medium zizmor/artipacked: credential persistence through GitHub Actions artifacts [confidence low] .github/workflows/verify.yml:18
medium zizmor/excessive-permissions: overly broad permissions [confidence medium] .github/workflows/verify.yml:10

Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.

Repository profile

  • Source lines: 2,278; test lines: 1,917
Language Lines
Python 4,195

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