Fetch the full /solve/ task ranking for a specific job-to-be-done (e.g., 'extract text from PDFs', 'parse Brazilian NFS-e invoices'). Returns the ranked candidates with install commands, an evaluated scorecard (word accuracy, layout, latency, cost, install friction), alternatives considered and d...
Part of the Auxiliar server.
Free to start. No card required.
AI agents invoke solve_task to trigger processes or run actions in Auxiliar. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.
solve_task can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.
Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.
{
"version": "1",
"default": "deny",
"tools": {
"solve_task": {
"limits": [
{
"counter": "solve_task_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}See the full Auxiliar policy for all 13 tools.
These attack patterns abuse exactly the kind of access solve_task gives an agent. Each links to the full case and the policy that stops it:
Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Fetch the full /solve/ task ranking for a specific job-to-be-done (e.g., 'extract text from PDFs', 'parse Brazilian NFS-e invoices'). Returns the ranked candidates with install commands, an evaluated scorecard (word accuracy, layout, latency, cost, install friction), alternatives considered and dropped, FAQs, and methodological caveats. Use this when an agent needs to pick an installable tool (skill/MCP/API/local binary) for a task rather than a cloud service. Data comes from a reproducible eval run on a real-world corpus — not training data.. It is categorised as a Execute tool in the Auxiliar MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Auxiliar MCP server in PolicyLayer and add a rule for solve_task: 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 Auxiliar. Nothing to install.
solve_task is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the solve_task 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 solve_task. 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.
solve_task is provided by the Auxiliar MCP server (auxiliar-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 13 Auxiliar tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.