Machine learning platform for market analysis and forecasting, with a focus on stock volatility prediction, market trend forecasting, and portfolio optimization.
MeridianAlgo/AraAI tiene un índice de salud de 57 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Vitality (84/100) y la más baja, Security (33/100). Se actualizó por última vez hace 12 días. Una sola persona concentra la mayor parte del trabajo reciente.
57
global / 100
Moderado
Índice de salud del software
Las métricas se agrupan en categorías ponderadas sobre una escala estandarizada de 1 a 100. El resultado global parte de su media ponderada, calibrada contra la distribución del registro público para que las bandas tengan significado percentil; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe un límite «En riesgo» de 34.
57
Excepcional93-100El nivel más alto del registro (≈ el 5% superior); cumple prácticamente todos los criterios evaluados
Excelente80-92Sólido en todos los frentes; carencias menores
Bueno65-79Saludable; carencias limitadas y manejables
Moderado50-64Aceptable con carencias notables; se recomienda revisión
Débil35-49Debilidades sustanciales en varias áreas
En riesgo20-34Debilidades significativas; su adopción exige cautela
Crítico1-19Problemas graves (proyecto abandonado, un solo mantenedor, sin higiene)
Perfil de puntuación
Cada eje es una categoría. La forma importa más que la media: un proyecto sano llena toda la figura, mientras que un perfil de picos y cráteres indica que la fortaleza en una dimensión enmascara el riesgo en otra.
El resultado global ponderado 55 se calibra a 57 en la escala publicada del índice (calibración del registro 2026-08-02).
¿Hasta qué punto está el repositorio preparado para desarrollarse y mantenerse con agentes de codificación de IA? Tiene un peso deliberadamente pequeño (4%): las herramientas para agentes son una señal real de mantenimiento, pero un repositorio sin ninguna puede alcanzar igualmente 100/100.
Código verificable por tipos — Python sin configuración de verificación de tipos
52.8/55
Tamaños de archivo manejables — 1/25 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_language
Python
largest_source_bytes
70.050
source_files_sampled
25
oversized_source_files
1
Datos clave
15estrellas de GitHub
4contribuidores
178commits en los últimos 12 meses
12días desde el último push
3versiones publicadas
1factor bus
0issues abiertas
PyPIecosistemas de paquetes
Advertencias de recopilación de datos
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Could not fetch pypi package 'ara-ai' from its registry
GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Más detalle
Historial de estrellas y forks 0 ★ / 4 ⇿
0Estrellas
4Forks
2Versiones
Cuándo se añadió cada estrella y fork, recopilado de GitHub y agrupado por día. El crecimiento acumulado se sitúa justo encima de las adiciones diarias que lo componen, de modo que ambos se leen en conjunto: la acumulación orgánica sostenida no se parece en nada a un pico abrupto y efímero. Cuando esa diferencia es medible, se informa como autenticidad del crecimiento.
Mayor 1Menor 0Parche 1
OpenSSF Scorecard 3.3 / 10
3.3agregado
Evaluación de seguridad independiente y agnóstica en cuanto a herramientas, procedente del proyecto de código abierto OpenSSF Scorecard. Cada comprobación premia una práctica de seguridad, no la herramienta de un proveedor concreto. Las comprobaciones que Scorecard no pudo determinar se marcan como n/d y se excluyen de la puntuación de seguridad (nunca se cuentan como cero).Scorecard v5.5.0 · 2026-08-02 21:14 UTC
No fue posible recopilar el conjunto de dependencias resuelto para este informe: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Informe JSON sin procesar legible por máquina
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"body": "…HF push (v5.2.1)",
"is_bot": false,
"headline": "fix: batch validation forward pass to stop CI runner OOM-kill before …",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-26T16:25:40Z",
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{
"oid": "4af7b95f73284fa10cb6274bfbf4c63bfc819b3d",
"body": "…ation script",
"is_bot": false,
"headline": "release v5.2.0 — bump version, fix readme badges, drop duplicate migr…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T02:59:29Z",
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-24T02:54:59Z",
"body_truncated": false,
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{
"oid": "4681bca4a40b0e657135074ee63deab6d54fd28f",
"body": "…migration script + rename scripts",
"is_bot": false,
"headline": "consolidate to single-job workflow + per-step comet logging + legacy …",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T02:54:41Z",
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"committed_at": "2026-05-24T02:44:51Z",
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"oid": "36d744270b979684f94c5621b2600ac70b1e5092",
"body": "Confirmed via Hugging Face that no pushes have landed since 2026-05-15\neven though training loops have been completing 70 steps cleanly. The\ntraining script gets SIGTERMed within ~25 seconds of 'Step limit\nreached' — before the 4096-sample CPU validation, Comet log_model\n(132 MB upload), final 2048-\n[…]\nantees the artifact step\nfinds a valid checkpoint when we don't.\n\nAlso added flush=True to the step/time limit print lines so CI logs\nshow the message immediately, not on Python's stdout buffer flush.",
"is_bot": false,
"headline": "fix(train): safety-save model BEFORE post-train validation/Comet",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T02:44:34Z",
"body_truncated": true,
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"oid": "87455e6539c1e7303dd09b28d9c106143d203bf0",
"body": "Every stage now shows what it's doing:\n\nSetup job\n- Run Information: run#, trigger, commit, branch, timestamp, CPU/RAM/disk\n- Install Dependencies: show package versions after install\n- Free Disk Space: before + after disk stats\n- Fetch Data: elapsed time\n- Check if Data was Fetched: full per-symbol\n[…]\n timestamp\n- Model Download Status: confirm artifact arrived + size\n- Upload to HF Hub: show file size, repo, start time, elapsed time\n\nCleanup job\n- Pipeline Summary: all four job results at a glance",
"is_bot": false,
"headline": "feat(ci): add comprehensive logging to stock + forex workflows",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T01:27:41Z",
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"oid": "22268304cde779fa89f48c3c669799cd9e71ea01",
"body": "…ompletion\n\nTraining completes 70 steps in ~31min then needs unbounded time for\npost-training validation, atomic model save, and Comet log_model upload\n(~130 MB .pt to Comet). The 75-min step timeout was killing the process\nafter training finished but before the model was saved, causing:\n - artifac\n[…]\nted\n\nFix:\n- Remove timeout-minutes from Train Model step (both forex + stocks)\n- Raise job timeout 95 -> 360 min (GitHub public-repo maximum)\n- Only --max-steps 70 governs when the training loop exits",
"is_bot": false,
"headline": "fix(ci): remove step timeout -- let 70 steps + post-training run to c…",
"author_name": "MeridianAlgo",
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"committed_at": "2026-05-24T01:20:54Z",
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"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-22T17:28:17Z",
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"oid": "423bd8b072e49cc648f9795be740cf30351bff00",
"body": "…imit)\n\n- Remove --max-time from both training scripts (was firing at step 47,\n before 70 steps could complete, causing the post-training validation\n to run past the step timeout and get canceled)\n- Add --max-steps 70 to both workflows — training stops cleanly at\n exactly step 70 then saves + pus\n[…]\n max_time_minutes=None (unlimited) in both training functions\n- Expand Train Model step timeout 55→75min, job timeout 75→95min to\n accommodate 70 steps (~47min) + validation/save/Comet flush (~15min)",
"is_bot": false,
"headline": "switch CI from time-based to step-based training (70 steps, no time l…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T17:27:59Z",
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"oid": "2ba096a6167312a3615d0304f41edce7caeaf5ca",
"body": "…+ push HF on partial runs\n\nThree coupled changes so a training run that hits the time budget still\nsaves, gets logged, and ends up on Hugging Face:\n\n1. Step timeout 38min -> 55min, script --max-time 35min -> 32min.\n The script stopped training at 33min and then ran final validation\n (forward pa\n[…]\ndel.outcome ==\n 'success' + hashFiles). With the atomic _save_model + SIGTERM handler\n already in place, a partial-but-improved checkpoint reaches HF on\n timeout runs instead of being discarded.",
"is_bot": false,
"headline": "fix(ci): stop exit-143 on training cleanup + register model in Comet …",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T16:04:33Z",
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"headline": "style: auto-format and lint [skip ci]",
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{
"oid": "06d11d1c9562170d3a07115fec755bc714c0bbad",
"body": "One-shot maintenance script: cancels all in-progress runs and deletes\nevery run for non-lint workflows in MeridianAlgo/AraAI, so the Actions\ntab shows a clean slate for the v5 release (lint runs are preserved).\n\n- GitHub REST API directly (no gh CLI dependency)\n- --dry-run flag to preview cancel/delete plan\n- Cancels active runs, waits, then deletes; gentle pacing between calls\n- Token from $GITHUB_TOKEN / $GH_TOKEN or --token; needs repo+workflow",
"is_bot": false,
"headline": "chore: add scripts/clean_workflow_runs.py for v5 history wipe",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T13:39:04Z",
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"body": null,
"is_bot": false,
"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-22T13:08:11Z",
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"oid": "197873c7d1bbefadf3e57e0c4cf97f95dcdf7cbb",
"body": "Runs were dying at the 50-min job timeout (exit 143 / \"operation was\ncanceled\") because the math under-counted setup time: ~17min for\ninstall + artifact download + HF model fetch, then 33min of training,\nthen validation+save pushed total past 50min.\n\n- meridian-stocks.yml / meridian-forex.yml: timeo\n[…]\nlocal variable 'ema_decay' where it is not associated\nwith a value\": the Comet log_parameters block referenced ema_decay\nbefore it was defined further down. Moved the assignment above the\nComet block.",
"is_bot": false,
"headline": "fix(ci): raise training job timeout to 75min and fix ema_decay NameError",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T13:07:49Z",
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{
"oid": "89f8e421e505d1f28bef647c3d09ddacd2d9ce48",
"body": "…y migration\n\nFix recurring \"operation was canceled\" CI failure at ~44min by making the\ntraining pipeline signal-safe and tightening the time budget:\n\n- SIGTERM/SIGINT handler in AdvancedMLSystem.train sets a shutdown flag\n the step loop polls; final save always runs before exit\n- _save_model is no\n[…]\n,\n comet_ai_token) via load_dotenv at script start\n- MODEL_CARD refreshed: new layout, hardening notes, Comet links, v5.1.0 metadata\n\nVersion bumps: pyproject.toml + meridianalgo/__init__.py -> 5.1.0",
"is_bot": false,
"headline": "v5.1.0: harden CI training pipeline + full Comet telemetry + HF legac…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-21T16:58:34Z",
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"oid": "5546666c0f061e66b8dc48c1a731b94ed8a3fc15",
"body": null,
"is_bot": false,
"headline": "fix: extend forex and stock training job timeouts to 120 minutes",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-17T23:38:41Z",
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"committed_at": "2026-05-15T19:08:27Z",
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"oid": "f47595c607dd8547941d795814e0f134f4cf3d4a",
"body": "The alias was a leftover compat shim in the try-block; MeridianModel is\nthe only name used in this file. Also fixes ruff I001 import sort in\nrevolutionary_model.py.",
"is_bot": false,
"headline": "fix: remove unused RevolutionaryFinancialModel import alias (ruff F401)",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T19:08:09Z",
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"oid": "d3e258aececdf98b55fa5da04d5302713ac6681d",
"body": "- CHANGELOG.md: full version history from v1.0.0-Beta to v5.0.0, built\n from all git tags and GitHub releases\n- QUICK_START.md: rewritten with accurate v5.0 specs, correct training\n commands, troubleshooting for known pre-v5 bugs\n- MODEL_CARD.md: updated to v5.0 — MeridianModel, checkpoint format\n\n[…]\nth, class weighting,\n logit scaling rationale, direction metrics table\n- INDEX.md (new): single-page documentation index with source layout\n- LICENSE: fix year (2025→2026) and placeholder GitHub URLs",
"is_bot": false,
"headline": "docs: comprehensive v5.0 documentation overhaul",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T19:05:14Z",
"body_truncated": true,
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"oid": "10c85542c70ce70efc2b27a2a455658590ccb489",
"body": "Documents all 7 training bugs fixed in v5.0, the architecture rename\nfrom RevolutionaryFinancialModel to MeridianModel, hourly CI schedule,\nCPU vs GPU model specs, checkpoint format reference, and updated project\nstructure.",
"is_bot": false,
"headline": "docs: update README for MeridianModel v5.0",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T18:55:50Z",
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"oid": "404e0ed76343122c86fa1545ea5e31f0dff52683",
"body": "Architecture rename:\n- meridian_model.py: new canonical file — classes MeridianModel, MeridianBlock\n- revolutionary_model.py: backward-compat shim (3-line re-export)\n- Checkpoint string: \"MeridianModel-2026\" (v5.0); _load_model accepts both old\n \"RevolutionaryFinancialModel-2026\" and new string so \n[…]\nremove hardcoded dim=384/num_heads=6/version=\"4.1\"\n so new models (dim=256/4/5.0) and old HF models both pass\n- Accepts architecture strings \"MeridianModel-2026\" or \"RevolutionaryFinancialModel-2026\"",
"is_bot": false,
"headline": "feat: rename to MeridianModel v5.0, hourly CI, LR warmup",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T18:26:33Z",
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"oid": "ff044c6313eb36169bce3ff2568f25109be20bdd",
"body": "Without this, new models saved with mamba_state_dim=4 would build the wrong\ngraph shape when the directional-accuracy tests reconstruct the model for\ninference, causing a state-dict load mismatch. Defaults to 16 so existing\nHuggingFace checkpoints (which predate this field) continue to load correctly.",
"is_bot": false,
"headline": "fix: pass mamba_state_dim to RevolutionaryFinancialModel in signal tests",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T16:36:40Z",
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"author_name": "GitHub Action",
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"committed_at": "2026-05-15T16:35:48Z",
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"oid": "4902160f30b330654ee6467eab45a20b044168cf",
"body": "Architecture changes (speed):\n- RevolutionaryFinancialModel: thread mamba_state_dim through to MambaBlock\n so state_dim is configurable without rebuilding the graph\n- New CPU training config: dim=256, num_heads=4, use_mamba=False, mamba_state_dim=4\n (~11M params, ~27 min/epoch on 60K samples vs 23\n[…]\n 180s time-limit buffer (from 120s) to guarantee validation always fits\n- Checkpoint: save actual use_mamba from model (was hardcoded True)\n and persist mamba_state_dim for faithful round-trip reload",
"is_bot": false,
"headline": "perf+fix: CPU-optimised architecture + 7 training correctness fixes",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T16:32:19Z",
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{
"oid": "a5eeb6b082cc8b60b05d7fac485b684f786725e5",
"body": "* fix: clip target return outliers, remove min-max remap, add model test suite\n\nThe trained checkpoints on HuggingFace shipped with metadata showing\nbest_val_loss=Infinity across all 50 training runs and direction_accuracy=0\nbecause the target distribution was poisoned by single bad price ticks\n(sto\n[…]\nt CI training run uses the fixed code path.\n\n* style: auto-format and lint [skip ci]\n\n---------\n\nCo-authored-by: MeridianAlgo <meridianalgo@gmail.com>\nCo-authored-by: GitHub Action <action@github.com>",
"is_bot": false,
"headline": "fix: clip target return outliers; add rigorous model test suite (#154)",
"author_name": "Ishaan M.",
"author_login": "ishaanman7898",
"committed_at": "2026-05-01T13:05:48Z",
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"is_bot": false,
"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-04-07T23:57:18Z",
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"oid": "ff417e840bde00ec372eeb959e66f9de549c1730",
"body": null,
"is_bot": false,
"headline": "fix: remove unused mem_model_mb variable (ruff F841)",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T23:56:46Z",
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{
"oid": "22e2a896a86590de24d13632091edce221e5c9ba",
"body": "X was deleted (line 557) to free numpy memory but still referenced in\n_update_metadata. Save n_samples before del and pass that instead.\n\nAlso update MODEL_CARD.md with correct v4.1 specs (45M params, not 388M).",
"is_bot": false,
"headline": "fix: resolve UnboundLocalError on X after del in training loop",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T23:54:08Z",
"body_truncated": false,
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{
"oid": "2caf5092a82a9433bfcddb8814bcdf0a63fef74b",
"body": "- --max-time 45 (45min training from script start)\n- timeout-minutes: 60 (15min buffer for CI overhead)\n- cancel-in-progress: false (queued runs wait, never kill running ones)\n- Stocks every 6h at :00, Forex every 6h at :30",
"is_bot": false,
"headline": "fix: simple 45min training / 60min timeout, no cancel-in-progress",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:28:42Z",
"body_truncated": false,
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{
"oid": "716fcdd880ea5a7d9e560f1a7a19e977eaf768fd",
"body": "- float32 everywhere (was float64) — halves dataset memory\n- Delete numpy arrays after torch conversion (del X, y)\n- In-place normalization (X_tensor.sub_().div_()) — no copy\n- Cap dataset at 300K samples (~1.5GB) with warning\n- Free feature_matrix after building X windows\n- Log memory usage for diagnostics\n\nPeak memory estimate with 50 stocks:\n Before: ~10.5GB (float64 + copies) → OOM\n After: ~3.5GB (float32 + in-place) → fits in 7GB",
"is_bot": false,
"headline": "fix: fit training within 7GB GitHub Actions RAM limit",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:25:07Z",
"body_truncated": false,
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-04-07T01:19:35Z",
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{
"oid": "35fef6b1c3b01d9fd73d9cd95f2564f9b1a2a2f1",
"body": "Workflows:\n- timeout-minutes: 350, --max-time 320 (5h20m training budget)\n- Concurrency groups: new scheduled runs cancel stale in-progress ones\n- Staggered crons: stocks at 0/6/12/18h, forex at 3/9/15/21h\n- Workflow dispatch now accepts epochs and max_time inputs\n- Smart issue handling: no duplicat\n[…]\ning time\n- _update_metadata() extracted for checkpoint + final save reuse\n- Training history capped at 50 entries to prevent unbounded growth\n- Patience increased to 20 epochs for longer training runs",
"is_bot": false,
"headline": "feat: robust training pipeline with smart scheduling and issue handling",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:19:23Z",
"body_truncated": true,
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{
"oid": "eb9cf3c7dbcb3b44a53c8c6e2d1935a03b52d314",
"body": "- timeout-minutes: 60 was too tight — CI overhead (checkout, install,\n download model) takes ~15min before script starts, leaving no room\n- Now: timeout-minutes: 340, --max-time 320 (5h20m training budget)\n- Cron reduced to every 6h to match longer training runs\n- Final validation capped at 2048 samples and skipped if time is tight\n- global_start_time ensures Python never overshoots its own budget",
"is_bot": false,
"headline": "fix: increase job timeout to 340min, train for 5h+ per run",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:12:07Z",
"body_truncated": false,
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{
"oid": "8784faabd00deeb92f8860dedb910677b557407b",
"body": "The MeridianAlgo account token didn't have write access.\nSwitched all model download/upload references to meridianal/ARA.AI\nwhere the write token works.",
"is_bot": false,
"headline": "fix: switch HuggingFace repo to meridianal/ARA.AI",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-06T13:30:15Z",
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"oid": "0a688b926a0414994d43c17335f1d78842af42d3",
"body": "step_limit_reached flag is also set by time-based mid-epoch stops,\nbut the print statement assumed max_steps was always set — caused\nTypeError dividing by None.",
"is_bot": false,
"headline": "fix: prevent crash when time limit stops training before step limit",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-05T23:30:09Z",
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"oid": "955a786741c9f3c10ceb34507ae53b89d9f9f34f",
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"is_bot": false,
"headline": "Test entire workflow push",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-05T21:06:50Z",
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"max_points": 7.5
},
{
"key": "contributors",
"name": "Contributors",
"detail": "project has 2 contributing companies or organizations -- score normalized to 6",
"points": 1.5,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "no update tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.2,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
"name": "Packaging",
"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "sast",
"name": "SAST",
"detail": "no SAST tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "36 existing vulnerabilities detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "exceptional",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"commit_weight_rule": {
"min_commits": 50,
"min_commit_share": 0.1
},
"review_only_matches": 0,
"below_threshold_exposures": [],
"assessed_self_published_locations": 2
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 34,
"weight": 0.04,
"metrics": [
{
"key": "ai_agent_context",
"band": "weak",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"has_llms_txt": false,
"legible_history_share": 0.845,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "82 of 97 human commits state their intent (structured subject or explanatory body)",
"points": 40,
"status": "met",
"details": [
{
"code": "legible_history",
"params": {
"legible": 82,
"sampled": 97
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "at_risk",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 22,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": 0,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no agent-authored commits among the last 100",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_authored_commits",
"params": {
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 53,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 70050,
"source_files_sampled": 25,
"oversized_source_files": 1
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "1/25 source files over 60KB",
"points": 52.8,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 25,
"oversized": 1
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
"classification": {
"labels": [],
"scores": {},
"primary": null,
"evidence": [],
"artifacts": [],
"confidence": "none",
"host_extension": false,
"runs_as_process": false,
"consumed_by_code": false
},
"metrics_version": "2.3.1"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
"Could not fetch pypi package 'ara-ai' from its registry",
"GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository"
],
"report_type": "repository",
"generated_at": "2026-08-02T21:14:42.479219Z",
"schema_version": "0.29.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/MeridianAlgo/AraAI.svg",
"full_name": "MeridianAlgo/AraAI",
"license_state": "custom",
"license_spdx": null
}
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Las puntuaciones son señales, no garantías. Reflejan prácticas públicamente visibles en GitHub; no son una auditoría de código ni una garantía de seguridad.
Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v2.3.1, esquema v0.29.0 — metodología completa · wiki de métricas.
