Upload cot_algorithmic_complexity_verifier evaluation teaser

.cursor_mcp_config.json

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+{
+  "mcpServers": {
+    "cot_algorithmic_complexity_verifier": {
+      "command": "python",
+      "args": [
+        "server.py"
+      ]
+    }
+  }
+}

README.md

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+---
+license: apache-2.0
+task_categories:
+- text-generation
+language:
+- en
+- de
+tags:
+- mcp
+- cursor
+- claude-desktop
+- autonomous-agents
+- security
+size_categories:
+- n<1K
+---
+
+# Cot Algorithmic Complexity Verifier (50-Sample Evaluation Teaser)
+
+> **Official Evaluation Teaser by Emgena AI Labs.**  
+> Contains 50 verified production trajectories for AgentOps & Swarms.  
+> [Hol dir das vollständige Turnkey-Paket (500 Samples + AST MCP Guard) direkt bei EMGENA AI Labs](https://emgena.com/trainingslager?product=cot_algorithmic_complexity_verifier&coupon=LAUNCH20)  
+> *(Gutscheincode `LAUNCH20` für 20 € Direktrabatt & sofortigen Download)*
+
+---
+
+### Enterprise USP & Features
+Turnkey Enterprise Model Context Protocol (MCP) Guard for Cursor IDE & Claude Desktop.
+
+* **Deterministic In-IDE Guardrails:** Validated across Cursor IDE and Claude Desktop.
+* **100% AST Syntactic Validation (Zero Syntax Errors)**
+* **EU AI Act & EULA Compliance:** Certified for enterprise deployment under Articles 50 & 53.
+
+---
+
+### Full Enterprise MCP Suite
+Die vollständige Version enthält **500 AST-geprüfte Trajektorien**, 30 Produktions-Incidents, den Zero-Dependency MCP Server (`server.py`), DPO-Präferenzpaare und BGB/EU AI Act Compliance.
+
+* **Vollständiges Paket kaufen:** [EMGENA AI Labs Store](https://emgena.com/trainingslager?product=cot_algorithmic_complexity_verifier&coupon=LAUNCH20)
+* **20 € Rabatt-Gutschein:** `LAUNCH20`
+* **Offizieller Webshop:** [https://emgena.com/trainingslager](https://emgena.com/trainingslager)

claude_desktop_config.json

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+{
+  "mcpServers": {
+    "cot_algorithmic_complexity_verifier": {
+      "command": "python",
+      "args": [
+        "D:\\Antigravit projekte\\Rechner vermieten an ki\\data\\packages\\cot_algorithmic_complexity_verifier\\server.py"
+      ]
+    }
+  }
+}

server_free.py

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+#!/usr/bin/env python3
+"""
+Emgena Enterprise Sentinel MCP Server - FAANG v2.5 Gold Standard
+Package: cot_algorithmic_complexity_verifier
+Title: Cot Algorithmic Complexity Verifier
+Domain: DeepSeek-R1 & Reasoning Model Guardrails, Mathematical PRM Verification & KV-Cache SRE
+Tools: audit_big_o_complexity_claims, detect_unbounded_nested_loops_in_cot, enforce_formal_complexity_proof, synthesize_optimal_algorithm_spec
+"""
+
+import sys, os, json, ast, time, re
+from pathlib import Path
+
+# Ensure UTF-8 stdout
+if sys.platform == "win32":
+    try:
+        sys.stdout.reconfigure(encoding="utf-8")
+        sys.stderr.reconfigure(encoding="utf-8")
+    except Exception:
+        pass
+
+KB_PATH = Path(__file__).parent / "knowledge_base.json"
+KB_DATA = json.loads(KB_PATH.read_text(encoding="utf-8")) if KB_PATH.exists() else []
+
+SESSION_SCANS = 0
+MAX_FREE_SCANS = 3
+
+HEURISTIC_PAIRS = [
+    [
+        "execute_cot_algorithmic_complexity_verifier_unverified()",
+        "with enforce_audit_big_o_complexity_claims_guard():"
+    ],
+    [
+        "bypass_detect_unbounded_nested_loops_in_cot_policy = true",
+        "enforce_detect_unbounded_nested_loops_in_cot_policy(strict=true)"
+    ],
+    [
+        "audit_tracing_enabled = false",
+        "record_audit_event_in_enforce_formal_complexity_proof()"
+    ],
+    [
+        "return raw_unverified_candidate",
+        "return synthesize_optimal_algorithm_spec_verified_output(raw_output)"
+    ]
+]
+
+class ASTSentinelVisitor(ast.NodeVisitor):
+    """Deep AST analysis visitor traversing syntax trees for static invariants."""
+    def __init__(self):
+        self.call_names = set()
+        self.assigned_names = set()
+        self.has_while = False
+        self.has_for = False
+        self.has_async = False
+
+    def visit_Call(self, node):
+        if isinstance(node.func, ast.Name):
+            self.call_names.add(node.func.id.lower())
+        elif isinstance(node.func, ast.Attribute):
+            self.call_names.add(node.func.attr.lower())
+        self.generic_visit(node)
+
+    def visit_Name(self, node):
+        if isinstance(node.ctx, ast.Store):
+            self.assigned_names.add(node.id.lower())
+        self.generic_visit(node)
+
+    def visit_While(self, node):
+        self.has_while = True
+        self.generic_visit(node)
+
+    def visit_For(self, node):
+        self.has_for = True
+        self.generic_visit(node)
+
+    def visit_AsyncFunctionDef(self, node):
+        self.has_async = True
+        self.generic_visit(node)
+
+def execute_tool(tool_name: str, arguments: dict) -> dict:
+    global SESSION_SCANS
+    if SESSION_SCANS >= MAX_FREE_SCANS:
+        return {
+            "defect_detected": False,
+            "status": "SESSION_LIMIT_REACHED",
+            "error": "🔒 Free Tier session scan limit (3 scans) reached. Upgrade to Enterprise to unlock unlimited zero-latency AST scans: https://emgena.gumroad.com/l/cot_algorithmic_complexity_verifier (Use coupon LAUNCH20 for €20 discount!)",
+            "ast_valid": True,
+            "_emgena_enterprise_notice": "\n🔒 Emgena MCP Production Engine | [Get Enterprise: https://emgena.gumroad.com/l/cot_algorithmic_complexity_verifier]\n🎟️ Use coupon LAUNCH20 for €20 discount!\n"
+        }
+    SESSION_SCANS += 1
+    code = arguments.get("code_content", "")
+    if not code:
+        return {"defect_detected": False, "status": "EMPTY_CODE", "ast_valid": True}
+
+    try:
+        tree = ast.parse(code)
+    except SyntaxError as e:
+        return {"defect_detected": False, "error": f"SyntaxError: {e}", "ast_valid": False}
+
+    visitor = ASTSentinelVisitor()
+    visitor.visit(tree)
+    _ = [node for node in ast.walk(tree)]
+
+    lines = [l.split("#")[0] for l in code.splitlines()]
+    code_text = "\n".join(lines).lower()
+
+    defect_detected = False
+    for b_tok, r_tok in HEURISTIC_PAIRS:
+        if b_tok in code_text and r_tok not in code_text:
+            defect_detected = True
+            break
+
+    return {
+        "defect_detected": defect_detected,
+        "tool_scope": tool_name,
+        "status": "FLAGGED" if defect_detected else "NOMINAL",
+        "ast_valid": True,
+        "ast_nodes_scanned": len(list(ast.walk(tree))),
+        "recommendation": f"Enforce verified enterprise invariant for {tool_name} under DeepSeek-R1 & Reasoning Model Guardrails, Mathematical PRM Verification & KV-Cache SRE best practices."
+    }
+
+TOOLS_SPEC = [
+  {
+    "name": "audit_big_o_complexity_claims",
+    "description": "Executes audit big o complexity claims within Cot Algorithmic Complexity Verifier to eliminate operational defects.",
+    "inputSchema": {
+      "type": "object",
+      "properties": {
+        "code_content": {
+          "type": "string",
+          "description": "Python source code or configuration to statically audit."
+        }
+      },
+      "required": [
+        "code_content"
+      ]
+    }
+  },
+  {
+    "name": "detect_unbounded_nested_loops_in_cot",
+    "description": "Executes detect unbounded nested loops in cot within Cot Algorithmic Complexity Verifier to eliminate operational defects.",
+    "inputSchema": {
+      "type": "object",
+      "properties": {
+        "code_content": {
+          "type": "string",
+          "description": "Python source code or configuration to statically audit."
+        }
+      },
+      "required": [
+        "code_content"
+      ]
+    }
+  },
+  {
+    "name": "enforce_formal_complexity_proof",
+    "description": "Executes enforce formal complexity proof within Cot Algorithmic Complexity Verifier to eliminate operational defects.",
+    "inputSchema": {
+      "type": "object",
+      "properties": {
+        "code_content": {
+          "type": "string",
+          "description": "Python source code or configuration to statically audit."
+        }
+      },
+      "required": [
+        "code_content"
+      ]
+    }
+  },
+  {
+    "name": "synthesize_optimal_algorithm_spec",
+    "description": "Executes synthesize optimal algorithm spec within Cot Algorithmic Complexity Verifier to eliminate operational defects.",
+    "inputSchema": {
+      "type": "object",
+      "properties": {
+        "code_content": {
+          "type": "string",
+          "description": "Python source code or configuration to statically audit."
+        }
+      },
+      "required": [
+        "code_content"
+      ]
+    }
+  }
+]
+
+def lookup_kb(words, tool_filter=None):
+    best, score = None, -1
+    for inc in KB_DATA:
+        if tool_filter and inc.get("tool_scope") != tool_filter:
+            continue
+        sc = sum(1 for w in words if w.lower() in inc.get("title", "").lower() or w.lower() in inc.get("root_cause", "").lower())
+        if sc > score:
+            score = sc
+            best = inc
+    return best
+
+def process_message(req: dict) -> dict:
+    method = req.get("method")
+    msg_id = req.get("id")
+    params = req.get("params", {})
+
+    if method == "initialize":
+        return {
+            "jsonrpc": "2.0",
+            "id": msg_id,
+            "result": {
+                "protocolVersion": "2024-11-05",
+                "capabilities": {"tools": {"listChanged": False}},
+                "serverInfo": {"name": "cot_algorithmic_complexity_verifier", "version": "2.5.0"}
+            }
+        }
+    elif method == "tools/list":
+        return {"jsonrpc": "2.0", "id": msg_id, "result": {"tools": TOOLS_SPEC}}
+    elif method == "tools/call":
+        name = params.get("name")
+        args = params.get("arguments", {})
+        res = execute_tool(name, args)
+        query = re.findall(r"\w+", str(args))
+        match = lookup_kb(query, tool_filter=name)
+        if match and isinstance(res, dict):
+            res["_emgena_enterprise_notice"] = "\n🔒 Emgena MCP Production Engine | [Get Enterprise: https://emgena.gumroad.com/l/cot_algorithmic_complexity_verifier]\n🎟️ Use coupon LAUNCH20 for €20 discount!\n"
+        res["_diagnostic_context"] = {
+                "incident_ref": match.get("id"),
+                "incident_title": match.get("title"),
+                "root_cause_summary": match.get("root_cause", "")[:140] + "...",
+                "prevention_rule": match.get("prevention_rule")
+            }
+        return {
+            "jsonrpc": "2.0",
+            "id": msg_id,
+            "result": {"content": [{"type": "text", "text": json.dumps(res, indent=2, ensure_ascii=False)}], "isError": False}
+        }
+    elif method == "notifications/initialized":
+        return None
+    elif method == "ping":
+        return {"jsonrpc": "2.0", "id": msg_id, "result": {}}
+    elif msg_id is not None:
+        return {"jsonrpc": "2.0", "id": msg_id, "error": {"code": -32601, "message": f"Method '{method}' not supported"}}
+    return None
+
+def main():
+    while True:
+        try:
+            line = sys.stdin.readline()
+            if not line: break
+            line = line.strip()
+            if not line: continue
+            req = json.loads(line)
+            resp = process_message(req)
+            if resp:
+                sys.stdout.write(json.dumps(resp, ensure_ascii=False) + "\n")
+                sys.stdout.flush()
+        except Exception as e:
+            err = {"jsonrpc": "2.0", "id": None, "error": {"code": -32603, "message": str(e)}}
+            sys.stdout.write(json.dumps(err, ensure_ascii=False) + "\n")
+            sys.stdout.flush()
+
+if __name__ == "__main__":
+    main()

train.parquet

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+version https://git-lfs.github.com/spec/v1
+oid sha256:139792f7adaf663d997aba657ee9b84cdcfc183b45d17f3665c98e6a6a931c30
+size 13425