Agent Skills: Architectural Forensics Protocol

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.

UncategorizedID: aiskillstore/marketplace/architectural-forensics

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pnpm dlx add-skill https://github.com/aiskillstore/marketplace/tree/HEAD/skills/dowwie/architectural-forensics

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skills/dowwie/architectural-forensics/SKILL.md

Skill Metadata

Name
architectural-forensics
Description
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.

Architectural Forensics Protocol

Deconstruct agent frameworks to inform derivative system architecture.

Mission

Distinguish between software engineering decisions (how it runs) and cognitive architecture decisions (how it thinks) to extract reusable patterns for new systems.

Quick Start

# 1. Map the codebase (uses codebase-mapping skill's script)
python .claude/skills/codebase-mapping/scripts/map_codebase.py /path/to/framework --output codebase-map.json

# 2. Run analysis via the command
/analyze-frameworks

Protocol Phases

Phase 1: Engineering Chassis

Analyze the software substrate. See references/phase1-engineering.md for detailed guidance.

| Analysis | Focus Files | Output | |----------|-------------|--------| | Data Substrate | types.py, schema.py, state.py | Typing strategy, mutation patterns | | Execution Engine | runner.py, executor.py, agent.py | Async model, control flow topology | | Component Model | base_*.py, interfaces.py | Abstraction depth, DI patterns | | Resilience | executor.py, try/except blocks | Error propagation, sandboxing |

Phase 2: Cognitive Architecture

Extract agent "business logic". See references/phase2-cognitive.md for detailed guidance.

| Analysis | Focus Files | Output | |----------|-------------|--------| | Control Loop | agent.py, loop.py | Reasoning pattern, step function | | Memory | memory.py, context.py | Context assembly, eviction policies | | Tool Interface | tool.py, functions.py | Schema generation, error feedback | | Harness-Model Protocol | llm.py, adapters/, stream.py | Wire format, tool call encoding, agentic primitives | | Multi-Agent | orchestrator.py, router.py | Coordination model, state sharing |

Phase 3: Synthesis

Generate actionable outputs:

  1. Best-of-Breed Matrix → Framework comparison table
  2. Anti-Pattern Catalog → "Do Not Repeat" list
  3. Reference Architecture → New framework specification

Execution Workflow

┌─────────────────────────────────────────────────────────┐
│                    For Each Framework                    │
├─────────────────────────────────────────────────────────┤
│  1. codebase-mapping                                    │
│       ↓                                                 │
│  2. Phase 1 Analysis (parallel)                         │
│     ├── data-substrate-analysis                         │
│     ├── execution-engine-analysis                       │
│     ├── component-model-analysis                        │
│     └── resilience-analysis                             │
│       ↓                                                 │
│  3. Phase 2 Analysis (parallel)                         │
│     ├── control-loop-extraction                         │
│     ├── memory-orchestration                            │
│     ├── tool-interface-analysis                         │
│     ├── harness-model-protocol                          │
│     └── multi-agent-analysis (if applicable)            │
└─────────────────────────────────────────────────────────┘
        ↓
┌─────────────────────────────────────────────────────────┐
│                      Synthesis                           │
├─────────────────────────────────────────────────────────┤
│  4. comparative-matrix                                   │
│  5. antipattern-catalog                                  │
│  6. architecture-synthesis                               │
└─────────────────────────────────────────────────────────┘

Quick Analysis (Single Framework)

For rapid assessment, run the minimal path:

codebase-mapping → execution-engine-analysis → control-loop-extraction → tool-interface-analysis

Output Directory Structure

forensics-output/                    # Working/intermediate files
├── .state/
│   ├── manifest.json
│   └── {framework}.state.json
└── frameworks/
    └── {framework}/
        ├── codebase-map.json
        ├── phase1/*.md
        └── phase2/*.md

reports/                             # Final deliverables
├── frameworks/
│   └── {framework}.md               # Framework summary
└── synthesis/
    ├── comparison-matrix.md
    ├── antipatterns.md
    ├── reference-architecture.md
    └── executive-summary.md

State Management & Resumption

The protocol is designed to be stateful and resumable.

  • Idempotency: The Orchestrator tracks progress in manifest.json and will skip frameworks marked as completed.
  • Clean Slate Resumption: If a run is interrupted, frameworks marked as in_progress are considered "stale". Use python scripts/state_manager.py reset-running to move them back to pending and delete their partial output directories, ensuring a clean restart for those items.

Agent Orchestration

This skill uses a 4-tier hierarchy of specialized agents for context efficiency:

Orchestrator
    │
    └── Framework Agents (parallel, one per framework)
            │
            └── Skill Agents (parallel, one per skill) [COORDINATORS]
                    │
                    └── Reader Agents (parallel, one per file cluster) [EXTRACTORS]
                            │
                            └── Synthesis Agent (cross-framework synthesis)

Agent Roles

| Agent | Context Budget | Reads | Produces | |-------|---------------|-------|----------| | Orchestrator | ~10K | State files | Coordination decisions | | Framework Agent | ~50K | Skill outputs | Framework summary report | | Skill Agent | ~25K | Cluster extracts | Skill analysis report | | Reader Agent | ~20K | 1-5 source files | JSON extract (~2K) | | Synthesis Agent | ~40K | All framework reports | Comparison matrix, architecture spec |

Key Innovation: Cluster-Based Reading

Reader Agents read file clusters (1-5 related files) rather than individual files:

  • Clusters are grouped by relationship: hierarchy, module cohort, type+usage, interface+impl
  • Cross-file patterns (inheritance, imports, shared state) are captured in the extract
  • This enables understanding architectural patterns that span multiple files

See:

  • references/orchestrator-agent.md — Top-level coordination
  • references/framework-agent.md — Per-framework analysis coordination
  • references/skill-agent.md — Skill coordination and cluster assignment
  • references/reader-agent.md — File cluster extraction
  • references/synthesis-agent.md — Cross-framework synthesis

Sub-Skill Reference

| Skill | Purpose | Key Outputs | |-------|---------|-------------| | codebase-mapping | Repository structure | File tree, dependencies, entry points | | data-substrate-analysis | Type system | Typing strategy, serialization | | execution-engine-analysis | Control flow | Async model, event architecture | | component-model-analysis | Extensibility | Abstraction patterns, DI | | resilience-analysis | Error handling | Error propagation, sandboxing | | control-loop-extraction | Reasoning loop | Pattern classification, step function | | memory-orchestration | Context management | Assembly, eviction, tiers | | tool-interface-analysis | Tool system | Schema gen, error feedback | | harness-model-protocol | LLM interface layer | Wire format, encoding, agentic primitives | | multi-agent-analysis | Coordination | Handoffs, state sharing | | comparative-matrix | Comparison | Decision tables | | antipattern-catalog | Tech debt | Do-not-repeat list | | architecture-synthesis | New design | Reference spec |