agent_framework_study

Master protocol for deconstructing agent frameworks to inform derivative system architecture. Use when (1) analyzing an agent framework's codebase comprehensively, (2) comparing multiple frameworks to select best practices, (3) designing a new agent system based on prior art, (4) documenting architectural decisions with evidence, or (5) conducting technical due diligence on AI agent implementations. This skill orchestrates sub-skills for data substrate, execution engine, cognitive architecture, and synthesis phases.

Analyze the protocol layer between agent harness and LLM model. Use when (1) understanding message wire formats and API contracts, (2) examining tool call encoding/decoding mechanisms, (3) evaluating streaming protocols and partial response handling, (4) identifying agentic chat primitives (system prompts, scratchpads, interrupts), (5) comparing multi-provider abstraction strategies, or (6) understanding how frameworks translate between native LLM APIs and internal representations.

Document technical debt, anti-patterns, and patterns to avoid from analyzed frameworks. Use when (1) creating a "Do Not Repeat" list from framework analysis, (2) categorizing observed code smells and issues, (3) assessing severity of architectural problems, (4) generating remediation suggestions, or (5) synthesizing lessons learned across multiple frameworks.

Generate a reference architecture specification from analyzed frameworks. Use when (1) designing a new agent framework based on prior art, (2) defining core primitives (Message, State, Tool types), (3) specifying interface protocols, (4) creating execution loop pseudocode, or (5) producing architecture diagrams and implementation roadmaps.

Repository structure and dependency analysis for understanding a codebase's architecture. Use when needing to (1) generate a file tree or structure map, (2) analyze import/dependency graphs, (3) identify entry points and module boundaries, (4) understand the overall layout of an unfamiliar codebase, or (5) prepare for deeper architectural analysis.

Generate structured comparisons and decision matrices across analyzed frameworks. Use when (1) comparing multiple frameworks or approaches side-by-side, (2) making architectural decisions between alternatives, (3) creating best-of-breed selection documentation, (4) synthesizing findings from multiple analysis skills into actionable decisions, or (5) producing recommendation reports for technical stakeholders.

Evaluate extensibility patterns, abstraction layers, and configuration approaches in frameworks. Use when (1) assessing base class/protocol design, (2) understanding dependency injection patterns, (3) evaluating plugin/extension systems, (4) comparing code-first vs config-first approaches, or (5) determining framework flexibility for customization.

Extract and analyze agent reasoning loops, step functions, and termination conditions. Use when needing to (1) understand how an agent framework implements reasoning (ReAct, Plan-and-Solve, Reflection, etc.), (2) locate the core decision-making logic, (3) analyze loop mechanics and termination conditions, (4) document the step-by-step execution flow of an agent, or (5) compare reasoning patterns across frameworks.

Analyze fundamental data primitives, type systems, and state management patterns in a codebase. Use when (1) evaluating typing strategies (Pydantic vs TypedDict vs loose dicts), (2) assessing immutability and mutation patterns, (3) understanding serialization approaches, (4) documenting state shape and lifecycle, or (5) comparing data modeling approaches across frameworks.

Analyze control flow, concurrency models, and event architectures in agent frameworks. Use when (1) understanding async vs sync execution patterns, (2) classifying execution topology (DAG/FSM/Linear), (3) mapping event emission and observability hooks, (4) evaluating scalability characteristics, or (5) comparing execution models across frameworks.

Analyze context management, memory systems, and state continuity in agent frameworks. Use when (1) understanding how prompts are assembled, (2) evaluating eviction policies for context overflow, (3) mapping memory tiers (short-term/long-term), (4) analyzing token budget management, or (5) comparing context strategies across frameworks.

Analyze coordination patterns, handoff mechanisms, and state sharing in multi-agent systems. Use when (1) understanding how agents transfer control, (2) evaluating shared vs isolated state patterns, (3) mapping communication protocols between agents, (4) assessing multi-agent orchestration approaches, or (5) comparing coordination models across frameworks.

Assess error handling, isolation boundaries, and recovery mechanisms in agent frameworks. Use when (1) tracing error propagation paths, (2) evaluating sandboxing for code execution, (3) understanding retry and fallback mechanisms, (4) assessing production readiness, or (5) identifying failure modes and recovery patterns.