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By mistakeknot
Agent-native architecture patterns — design, review, and audit for agent-first applications.
npx claudepluginhub mistakeknot/interagency-marketplace --plugin intercraftAgent-native architecture patterns for Claude Code.
The core question intercraft answers: can an agent do everything a user can do? If your application has a button that creates a project but no API endpoint or tool that does the same thing, you've built a human-only feature. Agents are second-class citizens, and that's a design bug.
intercraft provides 8 design principles for agent-native architecture (action parity, tools as primitives, context injection, shared workspace, CRUD completeness, UI integration, capability discovery, prompt-native features), a review agent that evaluates code against those principles, and a scored audit command for comprehensive assessment.
First, add the interagency marketplace (one-time setup):
/plugin marketplace add mistakeknot/interagency-marketplace
Then install the plugin:
/plugin install intercraft
Run an agent-native architecture audit:
/agent-native-audit
Or use the skill for design guidance when building new features:
"review this PR for agent-native parity"
"design this feature so agents can use it too"
skills/agent-native-architecture/ 14 reference docs + SKILL.md
agents/agent-native-reviewer.md Review agent for PRs and code changes
commands/agent-native-audit.md Scored audit command
The full knowledge cluster pattern: one skill with all the reference material, one agent that applies it to code review, one command that runs a comprehensive audit.
Uses power tools
Uses Bash, Write, or Edit tools
Share bugs, ideas, or general feedback.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Battle-tested configuration system for Claude Code agents: 28 architectural principles (incl. P-28 Feature-Layer Architecture for project-knowledge-as-a-navigable-tree), 19 safety hooks, 23 skills (incl. /layer-new + /feature-new for ULTRAPACK-style feature narratives), 16 alternative comparisons, 12 templates (incl. extended kb-skeleton with docs/layers/), diagnostic scripts (incl. build_kb_graph.py + validate_kb_links.py). Pairs with mclaude for multi-session coordination.
Core ACE workflow with TDD-based skills, task enforcement, and quality reviewers
[Beta] 6つの専門エージェントチームでコードベースのアーキテクチャを多角的に分析するスキル
Editorial "Agent Architect" bundle for Claude Code from Antigravity Awesome Skills.
Make a codebase agent-ready by scaffolding AGENTS.md, ARCHITECTURE.md, and docs/ structure following progressive disclosure patterns. Creates CLAUDE.md as a symlink for Claude Code compatibility.
Comprehensive UI/UX design plugin for mobile (iOS, Android, React Native) and web applications with design systems, accessibility, and modern patterns
[DEPRECATED — use intervoice] Analyze your writing style and adapt Claude's output to sound like you. Replaced by intervoice, which reads one global multi-register profile instead of per-project glob-routed files.
Recursive AGENTS.md generator with integrated Oracle critique, CLAUDE.md harmonization, incremental updates, diff previews, and smart monorepo scoping. Cross-AI compatible.
Self-improving agent rig: codifies product and engineering discipline into composable workflows from brainstorm to ship. Compounds knowledge, generates domain agents, monitors its own docs, and surfaces conservative update drift. Orchestrates Claude, Codex, and Oracle through 6 agents, 52 commands, 19 skills, 0 MCP servers. Factory substrate: CXDB turn DAG, scenario bank with satisfaction scoring, evidence pipeline, agent capability policies. Companions: interspect, interphase, interline, interflux, interpath, interwatch, interslack, interform, intercraft, interdev, interpeer, intertest.
Token-efficient code reconnaissance for LLMs. Autonomous skills save 48-85% tokens via diff-context, semantic search, structural patterns, and symbol analysis. Includes MCP server for direct tool integration.
Token efficiency benchmarking, session analytics, and API-equivalent cost analysis for agent workflows
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