ci: build plugins-index.json in-repo so worker refresh stays under budget

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.

plugins-index.json

@@ -0,0 +1 @@
+[{"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"}]