feat: add 6 production-ready plugins

All plugins are stdlib-only Python with no external dependencies.

- auto-summarizer: extractive conversation summary for long context
  compression, persists per-agent summaries to disk
- conversation-logger: JSONL audit logs per agent with ISO 8601
  timestamps, auto-creates log directory tree
- guardrails: safety filter detecting PII (email, phone, SSN, CC),
  prompt injection patterns, and credential exposure via regex
- keyword-memory: extracts entities (emails, URLs, dates, technical
  terms like camelCase/snake_case/dotted identifiers) as memories
- sentiment-tracker: keyword-based sentiment scoring with intensifiers
  and negation handling, only injects context for non-neutral sentiment
- todo-tracker: detects action items via 7 task patterns, tracks
  completion, deduplicates, persists per-agent with 20-item FIFO limit

plugins/auto-summarizer/hooks/ingest.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python3
+"""Auto-summarizer ingest hook.
+
+Returns the stored conversation summary as a memory fragment so agents
+maintain awareness of prior conversation context.
+
+Receives via stdin:
+    {"type": "ingest", "agent_id": "...", "message": "user message text"}
+
+Prints to stdout:
+    {"type": "ingest_result", "memories": [{"content": "..."}]}
+"""
+import json
+import os
+import sys
+
+
+def get_summary_path(agent_id):
+    """Return the path to the summary file for the given agent."""
+    home = os.path.expanduser("~")
+    return os.path.join(
+        home, ".librefang", "plugins", "auto-summarizer", f"{agent_id}.summary"
+    )
+
+
+def main():
+    request = json.loads(sys.stdin.read())
+    agent_id = request.get("agent_id", "unknown")
+
+    memories = []
+    summary_path = get_summary_path(agent_id)
+
+    if os.path.isfile(summary_path):
+        try:
+            with open(summary_path, "r", encoding="utf-8") as f:
+                summary = f.read().strip()
+            if summary:
+                memories.append(
+                    {"content": f"[summary] Conversation so far: {summary}"}
+                )
+        except (OSError, IOError):
+            # If we cannot read the file, return no memories silently.
+            pass
+
+    print(json.dumps({"type": "ingest_result", "memories": memories}))
+
+
+if __name__ == "__main__":
+    main()