AI-powered codebase understanding — analyze, visualize, and explain any project
Plugin understand-anything from marketplace moaa in ahmadhammoud56/MOAA. Commands read from the repo's manifest — 5 days ago.
This plugin runs code on your machine — its hooks fire automatically on events like tool use. The exact commands are listed below; read them before installing.
understand-chatUse when you need to ask questions about a codebase or understand code using a knowledge graph
understand-dashboardLaunch the interactive web dashboard to visualize a codebase's knowledge graph
understand-diffUse when you need to analyze git diffs or pull requests to understand what changed, affected components, and risks
understand-domainExtract business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
understand-explainUse when you need a deep-dive explanation of a specific file, function, or module in the codebase
understand-figmaAnalyze a Figma file via the Figma REST API and generate an interactive design knowledge graph (pages, screens, components, component sets, instances, design tokens) with a kind:"design" dashboard.
understand-knowledgeAnalyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.
understand-onboardUse when you need to generate an onboarding guide for new team members joining a project
understandAnalyze a codebase to produce an interactive knowledge graph for understanding architecture, components, and relationships
architecture-analyzerAnalyzes a codebase's file structure, summaries, and import relationships to identify logical architectural layers and assign every file to exactly one layer.
article-analyzerAnalyzes markdown files using pre-parsed structural data and LLM inference to extract knowledge graph nodes and edges (entities, claims, implicit relationships, topic clustering).
assemble-reviewerReviews the output of merge-batch-graphs.py for semantic issues the script cannot catch. Recovers dropped nodes/edges and fills cross-batch gaps.
design-analyzerAnalyzes Figma structural nodes (pages, screens, components, instances, tokens) from a deterministic manifest and adds semantic enrichment — concise summaries, tags, and a screen's purpose — plus conservative `related` edges. Does NOT invent structural nodes or edges.
domain-analyzerAnalyzes codebases to extract business domain knowledge — domains, business flows, and process steps. Produces a domain-graph.json that maps how business logic flows through the code.
file-analyzerAnalyzes batches of source files to produce knowledge graph nodes and edges. Extracts file structure, functions, classes, and relationships using a two-phase approach: structural extraction script followed by LLM semantic analysis.
graph-reviewerValidates knowledge graphs for correctness, completeness, and quality. Runs systematic checks and renders approval or rejection decisions.
knowledge-graph-guideUse this agent when users need help understanding, querying, or working with an Understand-Anything knowledge graph. Guides users through graph structure, node/edge relationships, layer architecture, tours, and dashboard usage.
project-scannerScans a codebase directory to produce a structured inventory of all project files, detected languages, frameworks, import maps, and estimated complexity.
tour-builderDesigns guided learning tours through codebases, creating 5-15 pedagogical steps that teach project architecture and key concepts in logical order.
node "${CLAUDE_PLUGIN_ROOT}/hooks/post-tool-use-auto-update.mjs"
UA_DIR=.understand-anything; [ -d "$UA_DIR" ] || UA_DIR=.ua; [ -f $UA_DIR/config.json ] && grep -q '"autoUpdate".*true' $UA_DIR/config.json && [ -f $UA_DIR/meta.json ] && [ -f $UA_DIR/knowledge-graph.
Harness-native ECC operator layer - 68 agents, 286 skills, 94 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
200 skills · 94 commands · 68 agents · 1 MCP server · hooks
Expose the plugin-safe Claude Code subset of Agentic Awesome Skills through a single marketplace entry.
200 skills
Specialist Council: 60 role agents with per-role model/effort and arena-forged members; assembles teams and delivers one verified result.
2 skills · 60 agents · hooks
Matt Pocock's agent skills for real engineering (grilling, spec/ticket flows, TDD, code review, domain modelling and more).
37 skills
Token usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations
24 skills · 1 command · 1 agent · hooks
Talk like caveman. Cut 65% output tokens vs unprompted baseline (measured). Keep all technical accuracy.
20 skills · 1 command · 3 agents · hooks
A four-tier memory ladder for Claude Code where promotion is earned by recurrence, not asserted by confidence. L0 raw transcripts are never injected; L1 candidate atoms are gitignored and recalled on lexical relevance per prompt; L2 project context loads each session start; L3 stable persona is always loaded. L1 to L2 needs three distinct sessions spanning two distinct calendar days (a stated claim needs two; a verified claim is the only single-observation path); L2 to L3 needs two projects and thirty days. Two gates refuse rather than guess: a claim altered by the redaction pass never promotes on evidence alone, and a contradicted claim freezes until a human resolves it. Three hooks run the loop unattended and every one fails open. Nothing reaches a committed CLAUDE.md without an explicit human adopt. Ships 5 stdlib scripts, 3 hooks, a cs-memory-curator agent, /cs-memory, a JSON schema, and a 69-check validator. Concept from TencentCloud/TencentDB-Agent-Memory (MIT); no upstream code included.
1 skill · 1 command · 1 agent · hooks
Audit a project's npm, PyPI, and Go dependencies for supply-chain risk: version-matched advisories for direct dependencies and the full lockfile tree, abandoned upstreams, npm publisher concentration, and install scripts
1 skill
Ships pull requests to open-source projects you don't maintain — CONTRIBUTING compliance, PR-size/scope checks, minimal-diff implementation, AI-disclosure PR descriptions, and rebase or bot-review replies. Use for 提 PR / 上游 PR / 贡献代码, "open a PR", "fix this upstream", "rebase against main", "respond to the bot review". Not for reviewing PRs as maintainer (use github-review-pr) or general GitHub CRUD (use github-ops).
1 skill
Assess compliance with the EU General-Purpose AI (GPAI) Code of Practice under the AI Act (Regulation (EU) 2024/1689), Articles 51-56. Covers GPAI model identification (Art. 3(63)), systemic risk model designation (Art. 3(65), Art. 51, 10^25 FLOP training compute threshold), upstream provider obligations under Art. 53 (transparency, technical documentation, copyright policy, training data summary), additional systemic risk obligations under Art. 55 (model evaluation, adversarial testing, AI Office incident notification, cybersecurity), systemic-risk notification and Commission designation under Art. 52, downstream Art. 25 quasi-provider duties, and Art. 53(2) open-source exemption. Built for in-house counsel and AI governance teams reviewing LLM or foundation model deployments, drafting GPAI compliance plans, or assessing systemic risk thresholds. DACH: BaFin, BSI, BNetzA. Pairs with the EU AI Act System Classifier, High-Risk Readiness, FRIA, and Serious Incident Reporting skills.
200 skills
BDD-first engineering skills forked from mattpocock/skills (synced 2026-11-04, upstream v1.3.2 + 3 commits)
50 skills
Research-augmented fork of obra/superpowers. Ships 13 workflow skills (brainstorming, planning, code review, debugging, verification, worktrees, parallel agents) standalone, with no dependency on the upstream superpowers plugin.
13 skills
This page updates itself from your repo. Add the badge to your README, or get it Featured to pin it above the organic results with a followed link to your site.