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By mikeprasad
Persistent human-governed knowledge management for Claude Code: capture session insights, decisions, and feedback into structured backlogs; promote approved items to a tag-indexed markdown knowledge base; run pre-mortems on plans and retrospectives on shipped work with evidence sourcing; enforce change-decision hooks on edits and writes.
npx claudepluginhub mikeprasad/aria-knowledge --plugin aria-knowledgeResearch a question, check existing knowledge first, draft a knowledge doc from the answer, and save directly to the appropriate category. Use when user says '/ask', 'ask about', 'research and save', 'I want to learn about', 'what is the pattern for'. Skips backlogs — the user reviews the answer in real-time before saving. (Claude Code variant — bare-slash canonical when both ports loaded; see ADR-094.)
Audit project configuration and documentation for drift, staleness, and broken references. Use when user asks for 'config audit', 'docs audit', 'check setup', 'audit configs', 'review CLAUDE.md files', or at session start when audit cadence is exceeded. (Claude Code variant — bare-slash canonical when both ports loaded; see ADR-094.)
Batch-review personal knowledge for promotion to team-shared project knowledge. Walks insights/decisions/approaches/rules and IDEAS-BACKLOG.md entries, recommends a target _project-knowledge/ destination per item, and lets the user approve all/numbers/modify/skip. Use when user says '/audit-share', '/share-audit', 'share knowledge', 'promote to team', 'sync to shared knowledge', or after enabling the projects_shared_knowledge feature.
View and manage pending backlog items. Use when user says '/backlog', '/backlog insights', '/backlog clear', 'what's pending', 'show backlogs', 'check backlog status'. (Claude Code variant — bare-slash canonical when both ports loaded; see ADR-094.)
NOTE: this skill requires ~~chat or ~~email MCPs, which are typically only connected in Cowork — the Code variant exists for parity but most users will want the Cowork variant. Capture a chat or email thread from a connected MCP to the knowledge intake. Use when user says '/clip-thread', 'clip this thread', 'save this Slack thread', 'capture this email chain', 'archive this conversation'. Pulls thread content from ~~chat (Slack, Teams) or ~~email (Gmail, MS365) MCP, composes a clipping with thread metadata + body, writes to intake/clippings/ for review at next /audit-knowledge. (Claude Code variant — bare-slash canonical when both ports loaded; see ADR-094.)
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
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Make your AI agent code with your project's architecture, rules, and decisions.
AI-powered knowledge base management - Capture conversation learnings, maintain topic-specific KB files, Obsidian-compatible knowledge graph, structured dynamic context loading, and institutional knowledge in CLAUDE.md
Plugin for effective agentic development
Development toolkit for Claude Code — plan, implement, ship, review, and assess features with AI-assisted workflows. Progressive zero-config init: auto-configures with sensible defaults on first skill invocation, no upfront ceremony required. Three-tier ceremony model: swift (lightweight), standard (mid-ceremony spec-plan-execute), and thorough (full pipeline) with severity-aware scope routing. Five entry points: arn-planning (scope router, spec, plan), arn-implementing (execute plans, swift, or standard changes), arn-shipping (commit, push, PR), arn-reviewing-pr (PR feedback), arn-assessing (codebase health). Includes arn-code-sketch for UI preview, arn-code-swift for quick implementations, and arn-code-standard for mid-ceremony changes. Includes arn-code-catch-up for retroactive documentation of out-of-pipeline commits. Pipeline preference persistence for streamlined repeat sessions. Batch pipeline: arn-code-batch-planning (multi-feature planning), arn-code-batch-implement (parallel worktree execution), arn-code-batch-merge (conflict-aware merge), arn-code-batch-simplify (cross-feature quality).
Post-processing utilities for manifest workflows. ADR synthesis from session transcripts.
You work with me (Claude) - I guide your workflow and suggest next actions.
External network access
Connects to servers outside your machine
External network access
Connects to servers outside your machine
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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 knowledge-and-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/), and Cursor (plugin-cursor-template/) — all living in this repo and 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.
Both ports installed? When
plugin-claude-codeandplugin-claude-coworkare loaded in the same session (most common in Claude Desktop), bare slash commands (/handoff,/wrapup,/extract, etc.) deterministically resolve to plugin-claude-code (the Code-side canonical). For the Cowork variant of any skill, use the namespaced form:/aria-cowork:handoff,/aria-cowork:wrapup, etc. Each colliding skill carries a Runtime Gate that surfaces a notification if invoked from the wrong runtime. See ADR 094 for the full design. ARIA manages a complete knowledge lifecycle — capturing insights, decisions, and feedback during sessions, staging them in backlogs for human review, and promoting what matters into a searchable, tag-indexed knowledge base. Session hooks prevent knowledge loss during context compaction, surface relevant knowledge when tasks are created, and enforce a change decision framework at every file edit, requiring visible impact assessment and scope verification before and after changes. Each session builds on the last instead of starting from scratch.
Beyond capture, ARIA provides active tooling: /codemap generates feature-organized maps that trace full-stack flows; /stitch builds cross-repo binding tables for product groups; /distill turns raw ticket text into tiered executable task specs that cite real files. /ask researches questions and saves answers as knowledge docs. /intake bulk-imports from files, URLs, or directories. /audit-config and /audit-knowledge detect drift, staleness, and gaps on configurable cadences. /wrapup (gated or auto) closes out a session cleanly when you're done — no passoff intended; /handoff (combined-go, auto, or brief) generates a passoff package — paste-ready next-session opener for future-you in a new session, or 80–150 word coworker prose brief. An optional project-specific tier (v2.8.0+) organizes architecture decisions and patterns by project, with cross-project promotion when patterns validate across multiple projects. Everything is plain markdown, works as an Obsidian vault, and follows the core philosophy: the AI captures, the human promotes, trusted knowledge acts.
AI coding sessions generate valuable knowledge every day. Architecture decisions. Debugging discoveries. Product constraints. Team conventions. Reviewer feedback. Lessons learned the hard way.
Then the session ends. Context gets compacted. Decisions disappear into transcripts. The next session repeats old questions, misses known constraints, or reopens choices already settled.
Most memory tools solve this by helping the assistant remember more. ARIA goes further: it asks what knowledge is worth trusting, how should it be reviewed, and how should that trusted knowledge actively shape the next decision, task, and code change. That is the difference between passive memory and applied operational knowledge.
Knowledge moves through a five-phase lifecycle: Capture → Govern → Promote → Apply → Refresh.
Preserve session knowledge before context evaporates.