Last updated: 2026-05-12
| Prefix/Pattern | Role |
|---|---|
vla-* |
VLA pipeline (robotics/embodied AI) |
ai-app-* or ai-* |
AI agent / app pipeline |
prep-<pipeline>.py |
Phase 1: collect + filter candidates |
run-<pipeline>-two-phase.py |
Phase 2: LLM agent runner (two-phase) |
post-<pipeline>.py |
Phase 3: deterministic post-processor / TG push |
_*.py |
Private shared module (imported by other scripts) |
gh-*.py |
GitHub Contents API operations |
vla-rss-collect.py → vla-rss-YYYY-MM-DD.json
rate-vla-daily.py → vla-daily-rating-in/out-YYYY-MM-DD.json (Phase 1.5)
run-vla-daily-two-phase.py → vla-daily-hotspots.json + TG push
prep-vla-theory.py → agent → post-vla-theory.py (theory dissection)
prep-vla-social.py → run-vla-social-two-phase.py → post-vla-social.py
prep-vla-sota.py → run-vla-sota-two-phase.py → post-vla-sota.py
prep-vla-release.py → run-vla-release-two-phase.py → post-vla-release.py
prep-vla-weekly.py → run-vla-weekly-two-phase.py → post-vla-weekly.py
vla-daily-rerate-push.py (re-push with ratings after keyword-fallback day)
vla-trend-snapshot.py (weekly trend snapshot for quality review)
backfill-vla-history.py (one-off historical backfill utility)
_vla_expert.py (shared: get_api_key, call_qwen, fetch_handbook_context)
ai-app-rss-collect.py → ai-app-rss-YYYY-MM-DD.json
ai-daily-pick-collect.py → ai-daily-pick-sources-YYYY-MM-DD.json
prep-ai-app-rss-filtered.py → write-ai-app-daily.py (tool news / 日报)
prep-ai-app-social.py → run-ai-app-social-two-phase.py (社交情报)
prep-ai-app-workflow.py → run-ai-app-workflow-two-phase.py (工作流灵感)
prep-ai-deep-dive.py → agent → post-ai-deep-dive.py (深度解析)
prep-ai-weekly.py → run-ai-weekly-two-phase.py → post-ai-weekly.py
post-ai-app-daily.py (deterministic daily stats → ai-app-daily-stats.json)
prep-ai-app-dedup.py (shared dedup helper)
prep-calibration-check.py (daily 11:00 assumption scan)
monthly-calibration-agg.py (monthly aggregation + confidence update)
quality-drift-check.py (7-day rolling baseline + 30-day sustained-decay)
ai-field-state.py (mechanical zero-LLM trigger gate; 6 trigger types →
memory/field-state-YYYY-MM-DD.json)
cross-domain-rule-engine.py (v2: 7 built-in rules R001-R007 + LLM significance →
memory/cross-domain-insight.json)
entity-tracker.py (90-day rolling index of authors/labs/methods/benchmarks)
upstream-signal-monitor.py (track 1-2 upstream domains for early signals)
A 4-script pipeline that watches an OSS-repo registry and infers adoption phases, the Daily Field Index (DFI), and cross-repo convergence.
collect-github-issues.py (daily; tier-1 repos)
↓
memory/gh-issues-YYYY-MM-DD.json
↓
compute-gh-adoption.py (Fri; tier-1 + tier-2 → adoption phases + DFI)
↓
memory/gh-adoption-YYYY-MM-DD.json
↓
update-gh-field-notes.py (push back to PULSAR_FIELD_NOTES_REPO)
prep-community-context.py (bundle community notes + adoption snapshot
into tmp file consumed by weekly reports)
_gh_issues_config.py (shared: registry of monitored repos,
tier flags, method-family tags)
semantic-index-builder.py (DashScope text-embedding-v3, batch=10, incremental)
semantic-search.py (pure-Python cosine top-k)
daily-watchdog.py (16 checks, self-healing, lockfile)
emit-system-health.py (emit system-health.json)
evaluate-shadow-config.py (A/B shadow config evaluator)
gateway-preflight.py (gateway connectivity check)
server-health-check.sh (shell-level health check)
system-moltbot-monitor.sh (moltbot process monitor)
memory-janitor.py (age-out old records from JSON stores)
memory-snapshot.py (daily tar.gz snapshot → snapshots/)
memory-upsert.py (atomic upsert helper)
gh-contents-upload.py (generic GitHub Contents API PUT)
gh-app-index-update.py (update AI app index on GitHub)
gh-paper-index-update.py (update VLA paper index on GitHub)
gh-handbook-changes-collect.py (collect VLA-Handbook git changes)
gh-agent-library-blog-readme-patch.py (patch Agent-Playbook README)
_heartbeat_run.py (heartbeat keepalive for long-running agents)
_paper_index_input_from_hotspots.py (extract paper index input from hotspots)
write-ai-app-daily.py— writes to ai-app-daily.json; named "write" not "post" because it is a pure atomic writer with no agent dependency. Referenced in jobs.json by this name.rate-vla-daily.py— Phase 1.5 between RSS collect and two-phase runner; no prep/run/post framing because it runs inline before the LLM agent step.vla-daily-rerate-push.py— special re-push called by watchdog on keyword-fallback days.