Report outcome of using recalled memories. Feeds into the adaptive learning loop to improve future retrieval. Valid outcomes: success, failure, partial. Args: memory_ids: Comma-separated list of fact/memory IDs. outcome: One of 'success', 'failure', 'partial'. context: Optional freetext context a...
AI agents use report_outcome to create or update resources in Qualixar/superlocalmemory — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Qualixar/superlocalmemory environment.
This tool writes feedback/outcome data back to the system to update retrieval weights or scoring. It modifies internal state (adaptive learning loop) but in a reversible/incremental way — no data is deleted and no external operations are triggered. Closest to Write. Severity is low because misuse would at worst degrade retrieval quality over time, not cause data loss or financial harm.
From the tool's definition 'Report outcome of using recalled memories. Feeds into the adaptive learning loop to improve future retrieval.'
Documented attack patterns abuse exactly the kind of access report_outcome gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Qualixar/superlocalmemory, and nothing reaches the server without passing your rules. This is the rule we recommend for report_outcome:
{
"version": "1",
"default": "deny",
"tools": {
"report_outcome": {
"limits": [
{
"counter": "report_outcome_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}report_outcome stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Report outcome of using recalled memories. Feeds into the adaptive learning loop to improve future retrieval. Valid outcomes: success, failure, partial. Args: memory_ids: Comma-separated list of fact/memory IDs. outcome: One of 'success', 'failure', 'partial'. context: Optional freetext context about the outcome. It is categorised as a Write tool in the Qualixar/superlocalmemory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Qualixar/superlocalmemory MCP server in PolicyLayer and add a rule for report_outcome: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Qualixar/superlocalmemory. Nothing to install.
report_outcome is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the report_outcome rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for report_outcome. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
report_outcome is provided by the Qualixar/superlocalmemory MCP server (qualixar/superlocalmemory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 59 Qualixar/superlocalmemory tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
59 Qualixar/superlocalmemory tools catalogued and risk-classified — across an index of 42,500+ MCP servers.