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Hot take: Storing full prompt/responses for every inference is a lazy audit design.

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(@local_llm_runner)
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  [#731]

Okay, so I've been setting up a bunch of local agents using Ollama and Docker Compose, and I'm finally digging into the security side with OpenClaw. I keep seeing this pattern in example audit logs: a giant JSON blob with the *entire* prompt and the *entire* model response stored for every single inference call. It feels… lazy? And honestly, a bit dangerous.

If we're logging everything forever, we're gonna be storing a ton of PII and sensitive data by accident. Plus, it makes the actual important forensic data—like *which* tool was called, with *what* parameters, and *why* the agent decided to do it—a nightmare to sift through. The signal is buried in all that text.

I think we should be logging structured events, not just dumping conversation history. For incident response, I need to know:
- The agent's decision: e.g., `"action": "tool_call", "tool_name": "send_email"`
- The critical parameters *sanitized*: `"to": "user@domain.com"` (not the full email body which might contain PII).
- The *reason* from the LLM, but maybe only the classification or intent: `"reasoning_extract": "user requested summary report"`.
- Credential or key access events: which key was used (just a key ID, not the secret!), for what scope.
- And crucially, a deterministic hash of the full prompt/response so we can reproduce if we *absolutely* have to, but we don't store the actual text by default.

Something like this structure feels safer and more queryable:

```json
{
"event_id": "xyz123",
"timestamp": "2024-...",
"agent_id": "report_generator",
"event_type": "tool_call",
"tool_call": {
"name": "query_database",
"parameters_sanitized": {
"query_type": "select",
"table": "sales_data",
"row_limit": 100
},
"credential_used_id": "key_db_ro_001"
},
"context": {
"session_id": "session_abc",
"user_input_hash": "sha256:...",
"llm_response_hash": "sha256:..."
},
"risk_level": "low"
}
```

This way, my audit log isn't a data liability, and I can actually run queries to find "all tool calls that used credential X" or "all database accesses in the last hour." Am I on the right track? How are you all designing your logs to be both useful and responsible?

- ella


- ella


   
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(@indie_dev_42)
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You're absolutely right. That pattern comes from the early demo days where logging everything was easier than thinking about what actually matters. I've been bitten by the PII storage problem myself - a dev agent once dumped a whole customer support transcript into a log table because the example code did it.

The structured events approach is the way to go, but the tricky part is agreeing on a schema. Your list is a great start. For my own agents, I've been logging something like this for tool calls:

```json
{
"event": "tool_invocation",
"tool": "send_email",
"params_safe": {"to": "redacted", "subject_length": 24},
"decision_summary": "User requested account summary"
}
```

The key is making the `params_safe` extraction part of the tool definition itself, so you can't forget to sanitize. What do you think about pushing OpenClaw to adopt a standard event schema?


~Sophie


   
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