End-to-end: select template → fill slots → lint → verify → correction loop. Needs ANTHROPIC_API_KEY | DEEPSEEK_API_KEY | OPENAI_API_KEY. Without key → falls back to chiasmus_formalize. Returns: solver result + template used + correction history. NOTE: \
AI agents invoke chiasmus_solve to trigger actions in Chiasmus. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool executes an end-to-end automated pipeline: it selects templates, fills them, lints, runs formal verification via Z3/SWI-Prolog, and iterates through a correction loop. It actively invokes external solvers and AI APIs (Anthropic/DeepSeek/OpenAI), making it an Execute-category tool.
From the tool's definition 'End-to-end: select template → fill slots → lint → verify → correction loop' and 'solver result + template used + correction history' — runs a full pipeline through Z3/SWI-Prolog formal verification including automated correction loops
Documented attack patterns abuse exactly the kind of access chiasmus_solve gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Chiasmus, and nothing reaches the server without passing your rules. This is the rule we recommend for chiasmus_solve:
{
"version": "1",
"default": "deny",
"tools": {
"chiasmus_solve": {
"limits": [
{
"counter": "chiasmus_solve_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}chiasmus_solve stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
End-to-end: select template → fill slots → lint → verify → correction loop. Needs ANTHROPIC_API_KEY | DEEPSEEK_API_KEY | OPENAI_API_KEY. Without key → falls back to chiasmus_formalize. Returns: solver result + template used + correction history. NOTE: \. It is categorised as a Execute tool in the Chiasmus MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Chiasmus MCP server in PolicyLayer and add a rule for chiasmus_solve: 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 Chiasmus. Nothing to install.
chiasmus_solve 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 chiasmus_solve 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 chiasmus_solve. 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.
chiasmus_solve is provided by the Chiasmus MCP server (yogthos/chiasmus). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 11 Chiasmus tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
11 Chiasmus tools catalogued and risk-classified — across an index of 42,500+ MCP servers.