secemp9

Formal Framework: The Rubric Design Space

Source Material

This document formalizes the rubric design space observed across secemp9's three repositories:

• references/main/rubrics/README.md -- Philosophy: (roleplaying == jailbreak == context following) == rubrics
• references/main/gist-ae3976ad/rubric_draft.md -- Playbook: 5 properties, 4 pitfalls, useful weirdness, policy mirrors
• references/main/gist-ff87ac23/red_team_rubric.py -- ComplianceJudge implementation
• references/main/rubrics/books2rubrics/on_writing_well_v1.xml -- ZinsserJudge v1 (232 lines)

secemp9

#!/usr/bin/env bash
# Full dev environment setup for general_wisdom monorepo & agentic_auxilary
# Ubuntu/Debian

set -euo pipefail

# Rust toolchain 1.93.0
rustup install 1.93.0 && rustup default 1.93.0

# Cargo tools

secemp9

#!/usr/bin/env bash
#
# setup_proxy.sh - CLIProxyAPI Setup and Management Script
#
# This script provides comprehensive setup and management capabilities for CLIProxyAPI,
# a proxy server that provides OpenAI/Gemini/Claude compatible API interfaces.
#
# Features:
#   - Automatic Go 1.26+ installation check
#   - CLIProxyAPI build and setup

secemp9

#!/usr/bin/env python3
"""
43-Parameter MLP for Multiplication — PyTorch Port

Original solution by Stefan Mesken (Code Golf, 2019)
Ported from TensorFlow to PyTorch with identical weights.

A standard neural network architecture with weights that would emerge
from actual training — not hand-crafted mathematical tricks.

secemp9

#!/usr/bin/env python3
"""
3-Parameter MLP for Addition

A minimal neural network with weights that would emerge from actual training.
Empirically verified: all random initializations converge to these exact weights.

Architecture: Input(2) → Dense(1, linear)
Parameters:  3 (weights [1, 1], bias 0)
Max error:   0.0 (exact)

secemp9

#!/usr/bin/env python3
"""
Deep AST-based static analysis of the dockercraft package.

Designed to catch artifacts from parallel agent edits:
- Duplicate/conflicting definitions across files
- Broken import chains after renames
- Orphaned references to moved/deleted symbols
- Inconsistent class hierarchies
- self.attr usage for attrs never set in __init__

secemp9

#!/usr/bin/env python3
"""
General-purpose AST-based Python module splitter.

Analyzes any monolithic .py file, builds a full dependency graph with structural
fingerprints, auto-discovers natural clusters, and produces split module files.

Capabilities:
  - AST parsing with full symbol table (ast + inspect-style signatures)
  - Structural hashing (hashlib) to fingerprint each symbol for drift detection

secemp9

<LLM_JUDGE_SPEC version="1.0" name="AntiLLMY" schema="1">
  <mission>Score a passage for LLM-y speak (“slop”), using only the given text. Return a compact diagnosis plus concrete fixes.</mission>

  <!-- ===== Regex library (mechanically checkable signs) ===== -->
  <regex_library flags="i">
    <!-- Tone / puffery / editorializing -->
    <pattern id="puffery_words">\b(stunning|breathtaking|must[- ]?(see|visit)|rich (?:cultural )?heritage|enduring(?:\s+legacy)?|nestled|in the heart of|watershed moment|stands as|serves as|is a testament|plays a (?:vital|significant) role|continues to captivate|solidifies)\b</pattern>
    <pattern id="editorialize">\b(it'?s (?:important|worth) (?:to note|noting)|no discussion would be complete|this (?:article|section) (?:wouldn'?t|would not) exist without)\b</pattern>
    <pattern id="weasel">\b(some (?:critics|observers|commentators) (?:argue|say|believe)|many (?:believe|say)|industry (?:reports|analysts) (?:suggest|say))\b</pattern>
    <pattern id="superficial_ing">\b(?:ens

secemp9

import requests
import json
import time
import copy
from enum import Enum
from typing import Dict, List, Any, Optional, Union, Iterator
from dataclasses import dataclass, field

class ModelErrorType(Enum):
    MAX_LENGTH = "1024"

secemp9

import requests
import json
import os
import subprocess
import time
from typing import Dict, List, Any, Optional
import uuid
import shutil

class ToolCallingTester: