mantle-ai 0.12.0

AI workflow engine with persistent context.

Mantle

AI workflow engine with persistent context. Built for developers who use Claude Code.

The Problem

AI coding agents are stateless. Every session starts from zero — context is lost, decisions are forgotten, and you end up repeating yourself or pasting notes between tools. Worse, agents rubber-stamp bad ideas instead of challenging them.

Mantle fixes this by giving your AI agent a memory, a structured workflow, and the discipline to validate ideas before building them.

What It Does

Mantle manages the full lifecycle of AI-assisted development:

Idea to verified code in one command — /mantle:build runs the full pipeline automatically: shape the issue, plan stories, implement with per-story agents, simplify, and verify against acceptance criteria.

Persistent context — project state, decisions, session logs, and a personal knowledge vault stored as markdown with YAML frontmatter. Everything is human-readable and lives in .mantle/.

Auto-briefing — every Claude Code session starts with a compiled briefing: project state, last session log, open blockers, next actions. You never start from zero.

Compiled knowledge — vault state is pre-compiled into Claude Code commands so your AI gets instant context, not expensive runtime file queries.

Cross-project learning — a personal vault links skills, patterns, and lessons learned across projects via Obsidian wikilinks. Learnings from past issues auto-surface in future planning.

Global storage — store .mantle/ context at ~/.mantle/ instead of in-repo for workplace environments where modifying .gitignore isn't desirable. Project identity is derived from git remote URL, so context survives re-clones.

Quick Start

Requires Python 3.14+.

# Install
uv tool install mantle-ai

# Mount commands into Claude Code
mantle install --global

# Initialize a project
cd your-project
mantle init

# Set up a personal vault (optional)
mantle init-vault ~/vault

Once initialized, .mantle/ is created in your project. Start a Claude Code session and use /mantle:help to see available commands.

Already have an existing project? Run mantle init then /mantle:adopt — AI agents analyze your codebase and domain, then interactively generate product and system design documents from what already exists.

Using this at work? Store context outside the repo so it never shows up in git diffs:

mantle storage --mode global
mantle migrate-storage --direction global

Context moves to ~/.mantle/projects/<repo-identity>/. All commands work identically — the path resolution is transparent.

Workflow

Every phase is a /mantle:* slash command inside Claude Code. Run them individually for control, or use /mantle:build to automate the full pipeline from shaped issue to verified code.

Project Setup (once)

Phase	Command	What It Does
Idea	/mantle:idea	Capture your idea with structured metadata — hypothesis, target user, success criteria. Saved as .mantle/idea.md.
Challenge	/mantle:challenge	Optional. AI stress-tests your idea from multiple angles (devil's advocate, pre-mortem, competitive analysis). Produces a verdict with confidence level.
Research	/mantle:research	Optional. Web research to validate technical feasibility and explore existing solutions. Reports saved to .mantle/research/.
Product Design	/mantle:design-product	Interactive session defining the what and why — features, target users, user stories, release milestones. Creates .mantle/product-design.md.
System Design	/mantle:design-system	Interactive session defining the how — architecture, tech choices, data model. Every decision logged with rationale and alternatives. Creates .mantle/system-design.md.

Already have an existing project? Run /mantle:adopt instead — AI agents analyze your codebase and domain, then interactively generate product and system design documents from what already exists.

Per-Issue Cycle (repeat for each issue)

Phase	Command	What It Does
Plan Issues	/mantle:plan-issues	Break work into vertical slices. AI proposes one issue at a time — you approve or adjust each before the next.
Shape Issue	/mantle:shape-issue	Evaluate 2-3 approaches with tradeoffs before committing to a direction. Past learnings are loaded automatically.
Plan Stories	/mantle:plan-stories	Decompose the issue into implementable stories sized for a single AI context window. Each story includes test expectations (TDD).
Implement	/mantle:implement	Automated build loop — spawns an Agent per story with dependency-aware wave execution, runs tests, retries once on failure, post-implementation code review, atomic git commits.
Simplify	/mantle:simplify	Post-implementation quality gate. Per-file agents identify and remove AI-generated code bloat. Test-gated — changes only committed if tests pass.
Verify	/mantle:verify	Project-specific verification against acceptance criteria. Auto-detects test/lint/check commands on first use. Per-issue overrides supported.
Review	/mantle:review	Human review with acceptance criteria checklist. AI presents pass/fail status from verification. You approve or request changes per criterion.
Retrospective	/mantle:retrospective	Capture what went well, what was harder than expected, and wrong assumptions. Learnings auto-surface in future shaping sessions.

Or run it all at once: /mantle:build executes the full pipeline — shape, plan stories, implement, simplify, and verify — without requiring confirmation at each step.

Available Any Time

Command	What It Does
/mantle:bug	Quick structured bug capture. Open bugs surface during planning.
/mantle:inbox	Ultra-low-friction idea capture for feature ideas.
/mantle:add-issue	Add a single new issue to the backlog.
/mantle:brainstorm	Explore and validate a feature idea against your product vision.
/mantle:scout	Analyze an external repo through your project's design lens.
/mantle:refactor	Structured refactoring for architectural debt and design problems.
/mantle:fix	Read saved review feedback and fix flagged criteria.
/mantle:revise-product	Update the product design. Creates a decision log entry.
/mantle:revise-system	Update the system design. Creates a decision log entry.
/mantle:status	Show current project state compiled from vault data.
/mantle:resume	Re-display the project briefing mid-session.
/mantle:add-skill	Add a skill node to your personal vault for cross-project knowledge.
/mantle:query	Search your vault knowledge and synthesize a grounded answer.
/mantle:distill	Synthesize accumulated vault knowledge on a topic into a persistent note.
/mantle:help	List all commands grouped by phase.

Knowledge Engine

Every AI context window is expensive. Mantle makes each one smarter by injecting the right knowledge at the right time — domain expertise, past learnings, and project decisions that would otherwise be lost between sessions.

How it works

Your personal vault (~/vault/) is a knowledge graph of interconnected skill nodes, each containing domain-specific patterns, conventions, anti-patterns, and lessons learned. When you start working on an issue, Mantle auto-detects which skills are relevant, compiles them into .claude/skills/, and Claude Code natively loads them. Every agent — whether it's shaping an approach, implementing a story, or reviewing code — gets pre-loaded domain knowledge without burning context on file searches.

The compounding effect: learnings from Issue 5 improve how Issue 12 is shaped. A skill you built while working on Project A informs implementation on Project B. The knowledge graph grows with you, not per-project.

Knowledge commands

Command	What It Does
/mantle:add-skill	Create a skill node in your personal vault — proficiency level, patterns, anti-patterns, related skills. Builds the graph.
/mantle:query	Search your accumulated vault knowledge and synthesize a grounded answer. Like asking your past self for advice.
/mantle:distill	Synthesize scattered vault knowledge on a topic into a single, dense reference note. Turns experience into reusable context.
/mantle:retrospective	After completing an issue, capture what went well and what was harder than expected. These learnings auto-surface in future /mantle:shape-issue sessions.
/mantle:scout	Analyze an external repo through your project's design lens. Extract patterns and ideas grounded in your existing architecture.

What gets injected into each context window

• Session briefing — project state, last session log, blockers, next actions (auto-loaded on session start)
• Compiled skills — domain-specific patterns matched to the current issue's technologies
• Past learnings — gotchas, recommendations, and wrong assumptions from previous issues
• Decision log — architectural choices with rationale, so agents honour past decisions instead of re-debating them

The result: agents that know your project's conventions, remember past mistakes, and make informed tradeoff decisions — every session, automatically.

How It Works

Mantle is a Python CLI (mantle) that also installs slash commands into Claude Code (/mantle:*). The core library handles all state and vault operations. The CLI is a thin wrapper. Claude Code commands compile context from your vault and orchestrate AI-assisted workflows.

Architecture: core/ (all business logic) → cli/ (thin routing layer) → Claude Code commands (prompt-based orchestration). Core never imports from CLI. Each implementation story gets a fresh 200k context window via native Agent subagents.

Storage: All state lives in plain markdown files with YAML frontmatter — human-readable and editable by hand. By default, .mantle/ lives in your project root (git-tracked for collaboration). For workplace environments, switch to global storage at ~/.mantle/ with mantle storage --mode global.

Session continuity: A SessionStart hook auto-compiles context and displays a project briefing. Session logs are written automatically at the end of every session, so you never lose context between conversations.

Status

v0.12.0 — Global-mode projects now leave zero .mantle/ footprint in work repos. Detection uses ~/.mantle/projects/<identity>/ directory existence instead of an in-repo config stub, so git worktrees inherit global context automatically.

License

MIT