beunec-asps 0.1.0

Agentic-System-Prompt-as-a-Skill (ASPS) — A three-layer framework for deterministic skill construction in agentic systems.

beunec-asps

Agentic-System-Prompt-as-a-Skill™ (ASPS™) — A lightweight, zero-dependency Python framework for deterministic skill construction in agentic systems.

An LLM does not "have skills." It has parameters. ASPS™ provides the infrastructure that makes an agentic system skillful.

Install

pip install beunec-asps

Quick Start

from beunec_asps import (
    ASPSBuilder,
    create_heuristic,
    create_pseudonym_protocol,
    NetworkTopologies,
    HEURISTIC_LIBRARIES,
)

# Build a skill in 4 lines
skill = (
    ASPSBuilder(name="Stock Analyst", domain="Equity Research", description="...")
    .distill(HEURISTIC_LIBRARIES["financial_stock_analyst"])
    .reinforce(
        pseudonym_protocol=create_pseudonym_protocol(
            identity="CFA Charterholder",
            persona="A disciplined equity research analyst.",
        ),
        guardrail_presets=["standard", "financial"],
    )
    .network(NetworkTopologies.hub_and_spoke(
        orchestrator_label="Lead Analyst",
        spokes=[{"label": "Market Data API", "node_type": "api", "capabilities": ["quotes"]}],
    ))
    .compile()
)

# Use the compiled system prompt with any LLM
print(skill.compiled_system_prompt)

Pre-Built Templates

from beunec_asps.templates import ASPS_TEMPLATES

# 7 ready-to-use skill templates
skill = ASPS_TEMPLATES["financial_stock_analyst"]()
skill = ASPS_TEMPLATES["full_stack_developer"]()
skill = ASPS_TEMPLATES["scientific_researcher"]()
skill = ASPS_TEMPLATES["content_creator"]()
skill = ASPS_TEMPLATES["private_equity_analyst"]()
skill = ASPS_TEMPLATES["financial_investment_analyst"]()
skill = ASPS_TEMPLATES["academia_professor"]()

The Three Techniques

Layer	Technique	Purpose
1	ASD™ (Agentic Skill Distillation)	Extract expert heuristics → deterministic instruction chains
2	ASR™ (Agentic Skill Reinforcement)	Behavioral checkpoints, pseudonym protocols, ICRL, guardrails
3	ANS™ (Agentic Network System)	Wire skills into governed multi-agent network topologies

Works With Everything

beunec-asps is zero-dependency and produces plain strings. It works alongside — never conflicts with:

• LangChain / LangGraph — use the compiled prompt as your agent's system message
• OpenAI SDK — pass skill.compiled_system_prompt as the system message
• Anthropic SDK — same
• AutoGen / CrewAI — use as the internal prompt for any agent in your graph
• Any LLM — it's just a string

Custom Skills

from beunec_asps import ASPSBuilder, create_heuristic, create_pseudonym_protocol, NetworkTopologies

skill = (
    ASPSBuilder(name="My Expert", domain="My Domain", description="What it does")
    .distill([
        create_heuristic(name="Step 1", instruction="Do this first."),
        create_heuristic(name="Step 2", instruction="Then do this."),
    ])
    .reinforce(
        pseudonym_protocol=create_pseudonym_protocol(
            identity="Domain Expert",
            persona="An experienced professional.",
        ),
        guardrail_presets=["standard"],
    )
    .network(NetworkTopologies.pipeline(stages=[
        {"label": "Agent A", "node_type": "agent", "capabilities": ["analyze"]},
        {"label": "Agent B", "node_type": "agent", "capabilities": ["synthesize"]},
    ]))
    .compile()
)

License

MIT — © 2025 Beunec Technologies, Inc.

ASPS™, ASD™, ASR™, ANS™ are trademarks of Beunec Technologies, Inc.