Evan Hu
f9821d5867
Walking ~40+ plugin TOMLs via the GitHub Contents API from the worker exceeded the Workers Free 50-subrequest-per-invocation limit, leaving the daemon's signed plugins index either empty or partial after every forced refresh. Move the walk into the repo: scripts/build-plugins-index.mjs reads each plugins/<name>/plugin.toml directly from the checked-out tree and emits a sorted flat array (name, version?, description?, needs?) at plugins-index.json. The CI workflow regenerates and commits this file on every push under plugins/, then pokes the worker's /api/registry/refresh — which now fetches the single committed plugins-index.json (1 subrequest), validates the JSON shape, and re-signs it with Ed25519. Refresh cost is now constant in registry size, not linear. The dashboard's dict-shaped /api/registry payload is unchanged — that still rebuilds via the daily 02:00 UTC cron.
1 line
1.6 KiB
JSON
1 line
1.6 KiB
JSON
[{"name":"auto-summarizer","version":"0.1.0","description":"Maintains a running conversation summary to help agents handle long conversations without losing context"},{"name":"context-decay","version":"0.1.0","description":"Time-based memory decay with relevance scoring for natural context forgetting"},{"name":"conversation-logger","version":"0.1.0","description":"Logs all conversations to JSONL files for auditing, analytics, and debugging"},{"name":"episodic-memory","version":"0.1.0","description":"Episode-based memory segmentation and recall for cross-conversation context continuity"},{"name":"guardrails","version":"0.1.0","description":"Safety filter that detects potentially harmful content patterns and injects warnings into agent context"},{"name":"keyword-memory","version":"0.1.0","description":"Extracts keywords and named entities from user messages and returns them as contextual memories"},{"name":"mempalace-indexer","version":"0.3.0","description":"Auto-index conversations into MemPalace and recall relevant memories. No API keys, no cloud."},{"name":"sentiment-tracker","version":"0.1.0","description":"Analyzes user message sentiment and injects emotional context so agents can respond with appropriate tone"},{"name":"todo-tracker","version":"0.1.0","description":"Detects action items and tasks mentioned in conversations, persists them, and recalls them as context"},{"name":"topic-memory","version":"0.1.0","description":"Topic-aware memory recall with keyword clustering for cross-conversation context"},{"name":"user-profile","version":"0.1.0","description":"Persistent user profiling from conversation patterns for personalized agent responses"}] |