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ARIA — Applied Reasoning and Insight Architecture

Agent Memory · Context Engineering · Planning & Reasoning · Human-in-the-Loop Governance

ARIA is the missing infrastructure layer for production AI coding agents: persistent memory that survives context compaction, deliberate context engineering that loads the right knowledge before action, human-governed trust gates that keep AI from acting on noise, and structured session discipline that gives agents the continuity needed for long-horizon reasoning.

The AI captures. The human promotes. Trusted knowledge acts.

New to ARIA? See QUICKSTART.md — 5-minute setup + best practices by session phase.

ARIA is a local-first knowledge and execution-discipline layer for AI coding sessions. It ships as a family of ports — Claude Code (plugin-claude-code/), Claude Cowork (plugin-claude-cowork/), OpenAI Codex (plugin-openai-codex/), Antigravity (plugin-antigravity/), and Cursor (plugin-cursor-template/) — all sharing the same ~/Projects/knowledge/ folder. Insights captured in one tool flow into another. The folder itself is plain markdown — readable by any AI, any human, any editor, with or without ARIA installed.

ARIA manages a complete knowledge lifecycle: it captures insights, decisions, and feedback during sessions; stages them in backlogs for human review; promotes what matters into a searchable, tag-indexed knowledge base; and applies that trusted knowledge back into future tasks, edits, and handoffs. Session hooks prevent knowledge loss during context compaction, surface relevant knowledge when tasks are created, and enforce a visible change decision framework at every file edit.

Why ARIA

Production AI coding agents do not usually fail because the model is incapable. They fail because the working system around the model is incomplete. ARIA addresses four failure modes that repeatedly break agentic work in practice.

Agent Memory

Every session starts from zero. Context compaction erases decisions. Debugging discoveries disappear into transcripts. The next session reopens questions that were already settled.

ARIA gives your agent persistent, structured memory across sessions and across tools. It captures insights during work, stages them for review, and builds a durable knowledge base that survives session boundaries.

Context Engineering

What the model sees determines what it does. Most teams still treat this as an ad hoc prompt-writing problem.

ARIA engineers context deliberately. It surfaces relevant knowledge at task creation time, loads project-specific rules and patterns before edits, and grounds work with artifacts like code maps, cross-repo stitch tables, and repository-aware task specs — so the model always acts on current, accurate context rather than assumptions.

Planning & Reasoning

Long-horizon work fails when the agent loses continuity between decisions, constraints, and active workstreams.

ARIA does not implement planning algorithms. It solves the continuity layer planning depends on: /distill turns tickets into grounded task specs that cite real files, /codemap gives structural codebase awareness, /stitch builds cross-repo bindings, and /handoff preserves full session state so reasoning chains do not break at session boundaries.

Human-in-the-Loop Governance

Auto-memory tools drift. They accumulate noise alongside signal, and the model eventually acts on unreviewed assumptions.

ARIA keeps humans in the loop. The AI captures candidate knowledge, but humans review and promote what becomes trusted. Audit logs and disposition history live in your own repo under git — not a vendor dashboard. Every promotion is explicit and traceable.

The Core Idea

Most memory tools help an assistant remember more. ARIA goes further: it asks what knowledge is worth trusting, how it should be reviewed, and how trusted knowledge should actively shape the next decision, task, and code change.

That is the difference between passive memory and applied operational knowledge.

How It Works

Knowledge moves through a five-phase lifecycle: Capture → Govern → Promote → Apply → Refresh.

Capture

Preserve session knowledge before context evaporates.

• /extract — Scan conversations for uncaptured insights, decisions, feedback, references, and ideas. Deduplicates against existing entries.
• /ask — Research a question, check existing knowledge first, save the answer directly as a knowledge doc.
• /intake — Capture knowledge from outside the conversation. A single URL or text snippet clips whole to intake/clippings/; files/dirs/globs bulk-scan into the backlogs; /intake extract <source> decomposes a source (incl. a Notion/Confluence/Google Doc via a connected ~~docs MCP) into backlog entries; /intake doc <url-or-title> (v2.17.0+) captures one structured 5-section artifact + user reaction; /intake thread <id> (v2.33.0+) pulls a chat/email thread via a connected ~~chat/~~email MCP. (v2.33.0 consolidated three former standalone capture skills — quick-clip, thread-capture, and doc-extract — into these /intake modes.)
• /interview <mode> (v2.31.0+) — Elicit knowledge through dialogue rather than harvesting it. Three modes: project (scope a new build), knowledge (get a topic out of your head into the KB), deep-dive (extract the rationale behind something you already built — requires a basis via --ground). Cadence (one-at-a-time socratic vs research-then-batch battery) is chosen in-session. Stages to intake/projects|interviews/ for manual review.

Govern

Convert raw capture into reviewable candidates.

• All captured knowledge stages in a backlog — nothing enters the trusted layer automatically.
• Human review is the gate between capture and promotion.
• Provenance is preserved so every piece of knowledge is inspectable and auditable.

Promote

Move reviewed knowledge into the trusted layer.

• /audit-knowledge (alias /knowledge-audit) — Review staged backlog entries and promote the ones worth trusting into the indexed knowledge base. Promotion happens inside the audit — there is no standalone /promote command.
• Organize by tag, project tier, and cross-project patterns.
• Optional project-specific tier (v2.8.0+) for architecture decisions and patterns.
• Optional non-blocking SessionStart project picker (v2.26.0+) — for multi-project parent dirs, suggests a project menu generated from projects_list and reads the chosen project's CLAUDE.md/PROGRESS.md.

Apply

Make trusted knowledge shape real work.

• TaskCreated hook — Surfaces relevant knowledge files when tasks are created (tag index matching).
• Rule 22 — Change decision framework enforced at every file edit. Requires visible impact assessment and scope verification before and after changes.
• /context — Load relevant knowledge into the current session for immediate use.
• /rules — Surface working rules that apply to the current task.

Codebase and task mapping turn ambiguous surface area into structured artifacts the agent can ground decisions against.

• /codemap — Feature-organized reference for any repository. Scans repos, detects frameworks, traces full-stack flows (routes → hooks → state → views → models → integrations). Four modes: create (full generation), inventory (quick index), update (incremental via git diff), section (rebuild one section).
• /stitch — Cross-repo binding artifact for product groups (backend + frontends). Tables for group identity, auth path, endpoint stitch, entity stitch, integration stitch, and a drift log.
• /distill — Turns raw ticket text into an executable task spec following a TASK.schema.md contract. Auto-tiers by complexity (micro / standard / full). Optional --group flag loads CODEMAP + STITCH context for cited-path specs.
• /auto — Entry point for an autonomous execution arc. A single invocation drives the full chain (brainstorm → spec → /prospect → plan → /prospect → TDD → /retrospect) under the Rule 35 posture, deciding objectively-validatable forks itself and stopping only on a load-bearing fork or an ungranted approval. Modes: /auto [goal] [continue|stop], /auto execute <plan|spec|linear-id>, /auto config (guided one-knob-at-a-time picker). An explicit override of the standing autonomy config (never writes it); three fan-out stopgaps (Workflow opt-in, budget-fraction pre-flight, cumulative subagent cap) guard usage.
• /prospect — Forward-looking pre-mortem on a plan before execution. Per-step actions: PROCEED / SHRINK / SPLIT / DEFER / KILL. Output saved to logs/prospect/.
• /retrospect — Structured retrospective on a shipped commit range, single commit, PR, release, or session. Enforces per-fix validation, surfaces simpler alternatives, runs failure-mode pattern checks. Output saved to logs/retrospect/.
• /recap [arc|commit|push|pull] — Read-only orientation: a scannable What / Where / Status table of recent work — this session by default, or the last arc / commit / push / pull. Summarizes to situate you; never validates (that's /retrospect) and never writes to disk.
• /roadmap [<name>|refresh] — Per-project feature roadmap: a Feature / Band / Status grid (Shipped / Current / Next / Later × done / in-progress / blocked / buildable) synthesized from CLAUDE.md + PROGRESS.md and persisted to a committed ROADMAP.md with source-stamp staleness-aware refresh (renders the persisted grid, then offers a refresh when stale). "Buildable" is the one inference — a Next-band feature with no blocker found, evidence shown, overridable. Writes only ROADMAP.md, never auto-commits.
• /foundational-review — The foundational review chain, run before an irreversible decision (version freeze, format/spec tag, public flip, major re-scope): verdict + named premises + sections A–F → design spec → cold-executable plan with owner routing → composed /prospect (amendments applied in place) → paste-ready executor kickoff. Requires a named irreversible decision (else redirects to /prospect or /readiness-audit). --extend adds the system-design assessment + roadmap chain.
• /readiness-audit — The recurring sibling: a checklist-against-a-surface audit answering "is it clean/legal/consistent to ship for THIS event?" Controller re-verifies every load-bearing agent claim (correction trail), read-only probes only with a mandatory artifact diff-check, tiered evidence-celled findings, phased remediation. No decision anchor needed.

Hooks make application continuous in the background.

• PreToolUse hook on Glob/Grep — Reminds to read CODEMAP.md before exploring a codebase directly. Fires once per project per session.
• PreCompact hook — Saves transcript snapshot before context compaction.
• PostCompact hook — Prompts to review captured snapshot after compaction.
• auto_capture toggle gates all automatic features.

Refresh

Knowledge bases rot when nothing forces review. ARIA treats freshness as a first-class concern.

• Last updated frontmatter on every knowledge file enables mechanical staleness checks.
• Configurable staleness thresholds — ideas_staleness_threshold_days (default 7) for intake/ideas/ entries; staleness_threshold_months for promoted knowledge files.