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
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# sentiment-tracker hooks
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Python hook scripts for the sentiment-tracker plugin. Each script reads a JSON request from stdin and writes a JSON response to stdout.
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## Scripts
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| Script | Hook | Description |
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|--------|------|-------------|
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| `ingest.py` | ingest | Receives `{"message": "..."}`, analyzes sentiment, returns emotional context as a memory fragment |
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## Protocol
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- **Input**: JSON object on stdin (fields vary by hook type)
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- **Output**: JSON object on stdout (`ingest_result` with memories, empty for neutral sentiment)
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