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Cognitive architecture for AI-augmented software development with structured memory, ensemble validation, and closed-loop correction. FAIR-aligned artifacts, 84% cost reduction via human-in-the-loop, standards adopted by 100+ organizations.

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# Execution Snapshot Schema # Based on REF-058 R-LAM (Reproducible LLM Agent Workflows) # Issue: #115 $schema: "https://json-schema.org/draft/2020-12/schema" $id: "https://aiwg.io/schemas/execution-snapshot/v1" title: "Execution Snapshot Schema" description: | Configuration snapshot system that captures full execution context at runtime for later replay and reproducibility validation. type: object required: - snapshot_id - workflow_id - captured_at - config - inputs - outputs properties: snapshot_id: type: string format: uuid description: "Unique snapshot identifier" workflow_id: type: string description: "Workflow this snapshot captures" version: type: string default: "1.0" description: "Schema version for evolution" captured_at: type: string format: date-time description: "When snapshot was captured" config: type: object required: [model, execution_mode] description: "Complete execution configuration" properties: model: type: object properties: id: type: string description: "Model identifier (e.g., claude-3-opus-20240229)" provider: type: string description: "Model provider" version: type: string description: "Model version if available" required: [id] execution_mode: type: string enum: [strict, seeded, logged, default] temperature: type: number minimum: 0 maximum: 2 seed: type: integer description: "Random seed if set" max_tokens: type: integer top_p: type: number stop_sequences: type: array items: type: string system_prompt_hash: type: string description: "Hash of system prompt for verification" agent: type: object description: "Agent configuration" properties: name: type: string version: type: string tools: type: array items: type: string rules_active: type: array items: type: string inputs: type: object description: "All inputs to the workflow" properties: user_prompt: type: string description: "Original user request" user_prompt_hash: type: string description: "SHA-256 of user prompt" context_files: type: array items: type: object properties: path: type: string hash: type: string size_bytes: type: integer description: "Context files loaded" environment: type: object additionalProperties: type: string description: "Relevant environment state" outputs: type: object description: "All outputs from the workflow" properties: response: type: string description: "Final response" response_hash: type: string description: "SHA-256 of response" artifacts_created: type: array items: type: object properties: path: type: string hash: type: string operation: type: string enum: [created, modified, deleted] tool_calls: type: array items: type: object properties: tool: type: string input_hash: type: string output_hash: type: string timestamp: type: string format: date-time metrics: type: object description: "Execution metrics" properties: duration_ms: type: integer tokens_input: type: integer tokens_output: type: integer tool_calls_count: type: integer iterations: type: integer replay_status: type: object description: "Status of replay attempts" properties: replayed: type: boolean default: false replay_count: type: integer default: 0 last_replay: type: string format: date-time match_status: type: string enum: - exact_match # Outputs identical - semantic_match # Semantically equivalent - partial_match # Some outputs differ - no_match # Outputs differ significantly - not_replayed # Never replayed # Replay configuration replay: matching_strategies: exact: description: "Byte-for-byte identical outputs" use_for: "Deterministic workflows" semantic: description: "Semantically equivalent outputs" use_for: "Natural language outputs" similarity_threshold: 0.95 structural: description: "Same structure, different values" use_for: "Code generation, schemas" comparison_fields: required: [outputs.response_hash] optional: [outputs.artifacts_created, outputs.tool_calls] # Storage storage: location: ".aiwg/provenance/snapshots/" format: json naming: "{workflow_id}-{timestamp}.json" retention: default_days: 90 on_replay_failure: 180 # Examples examples: - snapshot_id: "snap-001-example" workflow_id: "flow-implement-112" version: "1.0" captured_at: "2026-01-25T15:00:00Z" config: model: id: "claude-3-opus-20240229" provider: "anthropic" execution_mode: strict temperature: 0 seed: 42 max_tokens: 4096 agent: name: "Software Implementer" version: "1.0.0" tools: [Read, Write, Edit, Bash, Glob, Grep] inputs: user_prompt: "Implement checkpoint recovery system" user_prompt_hash: "abc123..." context_files: - path: ".aiwg/research/findings/REF-058-r-lam.md" hash: "def456..." size_bytes: 12345 outputs: response: "Created checkpoint schema..." response_hash: "ghi789..." artifacts_created: - path: "agentic/code/addons/ralph/schemas/checkpoint.yaml" hash: "jkl012..." operation: created metrics: duration_ms: 5000 tokens_input: 2000 tokens_output: 3000 tool_calls_count: 5 replay_status: replayed: false replay_count: 0 match_status: not_replayed # References references: research: - "@.aiwg/research/findings/REF-058-r-lam.md" implementation: - "#115" related: - "@agentic/code/frameworks/sdlc-complete/schemas/flows/execution-mode.yaml" - "@agentic/code/addons/ralph/schemas/checkpoint.yaml" - "@agentic/code/frameworks/sdlc-complete/schemas/provenance/prov-record.yaml"