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
guardrails
Safety filter plugin that detects potentially harmful content patterns in user messages and injects warning memories into agent context. Uses only Python stdlib regex -- no external dependencies.
Detection Categories
| Category | Examples | Memory Tag |
|---|---|---|
| PII | Email addresses, phone numbers, SSNs, credit card numbers | [guardrails:pii] |
| Prompt injection | "ignore previous instructions", "you are now", "system prompt:" | [guardrails:injection] |
| Credentials | password=, api_key=, secret=, token=, PEM private keys |
[guardrails:credential] |
Hooks
| Hook | Script | Description |
|---|---|---|
| ingest | hooks/ingest.py |
Scans user messages for harmful patterns and returns warning memories |
How It Works
When a user message arrives, the ingest hook runs all pattern checks against it. For each detected issue a memory is returned with the category tag and a recommendation for the agent (e.g. "avoid echoing PII", "maintain original instructions"). If nothing is detected the plugin returns an empty memories list.
All patterns use word boundaries and anchoring to minimise false positives on casual conversation.
Usage
Installed automatically when enabled in agent configuration.