a5c.ai

Human-in-the-loop integration for LangGraph workflows with approval and intervention points

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SONA self-optimizing neural architecture with ReasoningBank trajectory learning, EWC++ anti-forgetting, and reinforcement learning feedback loops.

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Fresh adversarial code review with binary PASS/FAIL verdicts, evidence citations, and anchoring bias prevention via fresh reviewer spawning.

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Transform research findings into actionable implementation plans with stakes-based rigor, test-first strategy, and granular task decomposition.

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Roadmap parsing, analysis, and mutation operations for ROADMAP.md. Handles phase and milestone lifecycle including add, insert (decimal), remove, complete, and requirements coverage analysis.

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Adversarial plan review by 3 independent reviewers (Feasibility, Completeness, Scope & Alignment) before presenting to user.

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Decompose implementation plans into discrete work units with enumerated DoD items, file scope declarations, dependency mapping, and human checkpoint flags.

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Structured code quality assessment with Conventional Comments format, scaled review depth, and soft-gating verdicts preserving user autonomy.

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Execute work units through the rigorous 4-phase Metaswarm cycle (Implement -> Validate -> Adversarial Review -> Commit) with independent quality gate enforcement.

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STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.

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Template loading, variable filling, and scaffolding for all GSD artifacts. Manages 22+ templates covering every document type in the GSD system, from PROJECT.md to milestone archives.

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Technical debt management including branch cleanup, doc verification, TODO scanning, and dependency auditing

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Break technical specifications into small, implementable stories with dependency ordering

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Bug condition/postcondition formalization as testable Behavior Contracts. Defines invariants that must be preserved across fixes.

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Convention discovery and rule generation from codebase analysis. Scans project structure, builds search indexes, identifies patterns, and generates enforceable rules.

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State capture and restore across context window compactions. Monitors usage thresholds and serializes quality, task, and spec state for seamless continuation.

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Git worktree management for safe, isolated feature development. Creates, manages, and cleans up worktrees with branch naming and dependency setup.

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Structured debugging methodology using hypothesis-driven investigation, log analysis, and bisection to isolate and resolve defects.

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Test-first development practice where test specifications are written before production code, integrated into plan tasks as mandatory first sub-steps.

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Complexity-based task routing with Q-Learning optimization, Agent Booster WASM fast-path, and Mixture-of-Experts model selection.

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Systematic codebase exploration following the Iron Law - understand the problem before exploring code. Four phases with file-finder and web-researcher agents.

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Final completion discipline including summary generation, plan document updates, and confirmation that all success criteria from the original plan are satisfied.

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Disciplined execution of approved plans with step-by-step verification, phase checkpoints, failure investigation, and mandatory code/security reviews.

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Multi-protocol consensus for agent swarms supporting Raft leader election, Byzantine fault tolerance, Gossip state propagation, and CRDT conflict-free merging.

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