By mistakeknot
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.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Collaborative brainstorm — assess clarity, research repo, explore approaches, capture design. Auto-handoff to /write-plan.
Orchestrate epic execution — read children, topo-sort by dependencies, dispatch phases sequentially with parallel features
Create engaging changelogs for recent merges to main branch
Toggle interserve execution mode
Bootstrap or check Clavain Codex installation health (install + wrapper sync + doctor)
Validates data migrations, backfills, and production data transformations against reality. Use when PRs involve ID mappings, column renames, enum conversions, or schema changes.
Use this agent when a major project step has been completed and needs to be reviewed against the original plan and coding standards. Examples: <example>Context: The user is creating a code-review agent that should be called after a logical chunk of code is written. user: "I've finished implementing the user authentication system as outlined in step 3 of our plan" assistant: "Great work! Now let me use the plan-reviewer agent to review the implementation against our plan and coding standards" <commentary>Since a major project step has been completed, use the plan-reviewer agent to validate the work against the plan and identify any issues.</commentary></example> <example>Context: User has completed a significant feature implementation. user: "The API endpoints for the task management system are now complete - that covers step 2 from our architecture document" assistant: "Excellent! Let me have the plan-reviewer agent examine this implementation to ensure it aligns with our plan and follows best practices" <commentary>A numbered step from the planning document has been completed, so the plan-reviewer agent should review the work.</commentary></example>
Systematically reproduces and validates bug reports to confirm whether reported behavior is an actual bug. Use when you receive a bug report or issue that needs verification.
Delegates well-scoped tasks to Codex CLI for cost-efficient execution. Use proactively for implementation, exploration, search, test generation, and code review when the task has clear scope and success criteria. Keep architecture, brainstorming, and interactive work in Claude.
Addresses PR review comments by implementing requested changes and reporting resolutions. Use when code review feedback needs to be resolved with code changes.
Use when requesting or receiving code review — dispatch reviewers, handle feedback rigorously, avoid performative agreement.
Use for 2+ independent tasks with no shared state or sequential dependency.
Use when capturing a solved problem as categorized documentation with YAML frontmatter for fast lookup
Execute a written implementation plan in a separate session with review checkpoints.
This skill should be used when managing the file-based todo tracking system in the todos/ directory. It provides workflows for creating todos, managing status and dependencies, conducting triage, and integrating with slash commands and code review processes.
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
Uses power tools
Uses Bash, Write, or Edit tools
Runs pre-commands
Contains inline bash commands via ! syntax
Clavain is the reference Claude Code rig for Sylveste, the platform that orchestrates agents by human/machine comparative advantage. It codifies product and engineering discipline into composable workflows for building software from brainstorm to ship, using Claude, Codex, and Oracle-style second opinions where their different failure modes help. Through knowledge compounding, doc freshness monitoring, domain-aware agent generation, and session evidence capture, Clavain gets better at building your project the more you use it.
Before installing, point Claude Code at this directory and ask it to review the plugin against how you like to work. It's especially helpful to run /insights first so Claude Code can evaluate Clavain against your actual historical usage patterns.
Want the full platform? Clavain is part of Sylveste, which installs the companion ecosystem, Go services, and TUI tools in one command. See the Sylveste Quick Start.
# Full rig install (recommended): installs Clavain + companions, MCP servers, env vars, and conflict resolution
npx @gensysven/agent-rig install mistakeknot/Clavain
# Plugin only (no companions or environment setup)
claude plugin install clavain@interagency-marketplace
# Local development
claude --plugin-dir /path/to/Clavain
# Remove Clavain + companions from Claude Code
bash scripts/uninstall.sh
# Remove Clavain only, keep companions
bash scripts/uninstall.sh --keep-companions
# Full platform uninstall (from Sylveste repo)
bash install.sh --uninstall
Go 1.22+ is required — clavain-cli is a Go binary built from source. Install from go.dev/dl.
Clavain can also run in Codex via native skill discovery and generated prompt wrappers.
Quick path:
curl -fsSL https://raw.githubusercontent.com/mistakeknot/Clavain/main/.codex/agent-install.sh | bash -s -- --update --json
Then restart Codex.
The default Codex bootstrap now installs the recommended Interverse companion set as well, not just Clavain itself.
Migrating from superpowers or compound-engineering? The ecosystem installer (
install-codex-interverse.sh install) automatically removes known legacy prompt wrappers, legacy~/.codex/skills/*artifacts (symlink or directory), and legacy superpowers clone artifacts with backup-first safety (~/.codex/.clavain-backups/<timestamp>/).
From a local clone:
make codex-refresh
make codex-doctor
make codex-doctor-json
Detailed guide: docs/README.codex.md
Single-file bootstrap target: .codex/INSTALL.md
Clavain serves three concentric circles, inner circle first:
Clavain is not the best workflow for everyone, but it can, at the very least, provide some inspiration for your own approach to Claude Code.
Most agent tools skip the product phases: brainstorm, strategy, specification: and jump straight to code generation. Clavain makes them first-class. The brainstorm and strategy phases are real product capabilities, not engineering context-setting.
A few operating principles that shape every design decision:
Refinement > production. The review phases matter more than the building phases. Resolving ambiguity during planning is far cheaper than dealing with it during execution.
Composition > integration. Small, focused tools composed together beat large integrated platforms. The inter-* constellation, Unix philosophy, modpack metaphor: it's turtles all the way down.
Human attention is the bottleneck. Optimize for the human's time, not the agent's. Multi-agent output must be presented so humans can review quickly and confidently, not just cheaply.
Multi-AI > single-vendor. No one model is best at everything. Clavain is built on Claude Code and uses Codex and Oracle-style review as complements: architecturally multi-model while remaining platform-native.
Discipline before automation. Encode judgment into checks before removing the human. Agents without discipline ship slop.
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Sign in to claimnpx claudepluginhub mistakeknot/interagency-marketplace --plugin clavain[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.
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
Multi-agent review and research with scored triage, domain detection, content slicing, intermediate finding sharing, and knowledge injection. 17 agents (12 review + 5 research), 7 commands, 1 skill (unified flux-drive with review/research modes), 2 MCP servers (exa, openrouter-dispatch). Companion plugin for Clavain.
Agentic engineering done right — 57 structured workflows, 17 specialist agent personas, persistent memory across sessions, integrated learning partner, and impeccable UI design system. Works with Claude Code, Windsurf, Cursor, Gemini CLI, OpenCode, and Codex.
Multi-agent collaboration plugin for Claude Code. Spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any problem that benefits from diverse solutions. Evaluate by metric or LLM judge, merge the winner. 7 slash commands, agent templates, git DAG orchestration, message board coordination.
11 agents, 35 skills, 18 commands, 9 hooks — spec-driven multi-agent orchestration for Claude Code, with optional cross-device semantic memory.
Harness for Claude Code — skills, /harness:* slash commands, persona subagents, lifecycle hooks, and MCP tools without per-repo `harness setup`. Sibling plugins exist for Cursor, Gemini CLI, and Codex.
Research-backed orchestration for Claude Code. Structured workflow from idea to production with parallel execution, session memory, 70-point validation, autonomous mode, and adversarial review. 51 commands, 15 agents across 7 departments.
This skill should be used when the model's ROLE_TYPE is orchestrator and needs to delegate tasks to specialist sub-agents. Provides scientific delegation framework ensuring world-building context (WHERE, WHAT, WHY) while preserving agent autonomy in implementation decisions (HOW). Use when planning task delegation, structuring sub-agent prompts, or coordinating multi-agent workflows.