Laporan audit skill

mri-reconstruction Laporan audit.

Actionable MRI image reconstruction — turn raw k-space into an image, and actually run it. Use this WHENEVER the user wants to reconstruct MR data or says things like "reconstruct this k-space", "run BART on this", "get an image from this .cfl / .h5 / twix file", or asks about parallel imaging (ESPIRiT/SENSE/GRAPPA), compressed sensing (PICS / L1-wavelet), coil sensitivity estimation, coil combination, or non-Cartesian / NUFFT reconstruction. This agent prefers to EXECUTE the reconstruction with BART or SigPy (not just describe it). It covers classical/analytic reconstruction — for anything TRAINED (unrolled networks, VarNet, self-supervised, diffusion priors, fastMRI models) hand off to the deep-learning-recon skill. Triggers: k-space, coil sensitivities, ESPIRiT, PICS, undersampled reconstruction, radial/spiral recon, `.cfl`/`.hdr`, ISMRMRD, Siemens twix, GE P-file.

Eksperimental · TinjauPerlu ditinjauDihasilkan 14 Okt 2026Audit metadata heuristik
74
Audit
66
Kepercayaan
60
Kualitas
76
Keamanan
100
Maintain
92
Pasang

Trust Score OpenAgentSkill

66
Tinjauan manual

Trust Score OpenAgentSkill

The Trust Score helps an agent decide whether a skill is safe enough to shortlist before installation.

Adopsi GitHub

Gagal

30

21 star GitHub

Aktivitas star/fork

Gagal

32

21 star dan 0 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Pemeliharaan terbaru

Lulus

100

20 hari sejak push

Kejelasan lisensi

Lulus

86

MIT

Kelengkapan README/SKILL.md

Lulus

86

Metadata memuat konteks penggunaan dan alur kerja yang cukup

Risiko dependensi/runtime

Info

72

Cakupan eksekusi perintah

Ketersediaan pemasangan

Lulus

92

npx skills add KeWang0622/mri-research-skill --skill mri-reconstruction

Keamanan perintah pemasangan

Lulus

92

Jalur pemasangan paket atau runtime standar

Cakupan izin

Info

62

shell or command execution, filesystem or document access

Bukti repositori

Lulus

86

https://github.com/KeWang0622/mri-research-skill/tree/main/skills/mri-reconstruction

Status peninjauan

Info

66

Data tinjauan AI tersedia

Hasil terbukti Agent

Info

54

Belum ada data hasil Agent

Pemeriksaan

Tinjauan pemasangan dan adopsi

6 Lulus · 14 Perlu ditinjau

Jalur pemasangan

92

Lulus

npx skills add KeWang0622/mri-research-skill --skill mri-reconstruction

Repositori

88

Lulus

https://github.com/KeWang0622/mri-research-skill/tree/main/skills/mri-reconstruction

Lisensi

86

Lulus

MIT

Pemeliharaan

100

Lulus

20 hari sejak push

Tinjauan AI

55

Periksa

The helper script uses `mktemp -u` which is not race-safe; using `mktemp` without `-u` and then creating files would be safer.

Kelengkapan README/SKILL.md

86

Lulus

Usable description available

Risiko dependensi

72

Periksa

Cakupan eksekusi perintah

Keamanan perintah pemasangan

92

Lulus

Jalur pemasangan paket atau runtime standar

Cakupan izin

62

Periksa

shell or command execution, filesystem or document access

Aktivitas star/fork

32

Perbaiki

21 star dan 0 fork; aktivitas issue tidak tersedia dalam metadata saat ini

Adopsi

42

Periksa

21 star GitHub

Financial decision safety

58

Periksa

Research-only use: do not treat output as financial advice or execute a position without human approval.

Peringatan

  • Financial research output is not financial advice; require human review before any live investment decision
  • The helper script uses `mktemp -u` which is not race-safe; using `mktemp` without `-u` and then creating files would be safer.
  • The script does not verify that the input k-space is actually Cartesian or non-Cartesian; it relies on the user to pass a trajectory only for non-Cartesian data, which could lead to silent errors if misused.
  • Low GitHub adoption signal
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • GitHub adoption: 21 GitHub stars
  • Stars/forks activity: 21 stars, 0 forks; issue activity unavailable in current metadata

Metode

This report combines public metadata, AI review output, repository freshness, install readiness, OpenAgentSkill events, quality scoring, trust checks, and the agent safety gate. It is not a full source-code security review.

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