xiaohongshu
xiaohongshu
architectural-forensics
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 arch...
Full skill instructions
Deconstruct agent frameworks to inform derivative system architecture.
Distinguish between software engineering decisions (how it runs) and cognitive architecture decisions (how it thinks) to extract reusable patterns for new systems.
# 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
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 |
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 |
Generate actionable outputs:
┌─────────────────────────────────────────────────────────┐
│ 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 │
└─────────────────────────────────────────────────────────┘
For rapid assessment, run the minimal path:
codebase-mapping → execution-engine-analysis → control-loop-extraction → tool-interface-analysis
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
The protocol is designed to be stateful and resumable.
manifest.json and will skip frameworks marked as completed.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.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 | 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 |
Reader Agents read file clusters (1-5 related files) rather than individual files:
See:
references/orchestrator-agent.md — Top-level coordinationreferences/framework-agent.md — Per-framework analysis coordinationreferences/skill-agent.md — Skill coordination and cluster assignmentreferences/reader-agent.md — File cluster extractionreferences/synthesis-agent.md — Cross-framework synthesis| 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 |
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