A Claude Code configuration that gives your AI assistant a structured productivity layer. Goals, tasks, projects, pipeline evaluation, and compounding knowledge — all in plain markdown. Runs in Claude Code, Codex CLI, Cursor, and Antigravity via the open Agent Skills standard.
Built on Andrej Karpathy's insight that large language models are best understood not as chatbots, but as the kernel of a new kind of operating system.
"Think about it more like an operating system."
— Andrej Karpathy, Intro to Large Language Models (2023)
Three architectural views — system flow, project pipeline, and the compounding loop that makes each session smarter than the last.
From raw ideas to daily execution — everything flows through a single inbox, gets classified, and ties back to your goals.
/morning picks Top 5 daily/launch runs 7-stage pipelineEach project passes through seven stages — five evaluation stages with a Go/No-Go gate, a non-blocking technical-spec stage, and a final decomposition stage that promotes to active. Skip ahead with --from.
Three nested feedback loops. Each layer feeds the next — the system gets smarter over time.
/morning saves plans to journals. Next morning reads yesterday's actuals. Memories persist across sessions.
/weekly compiles shipping summaries, reads journals for plan-vs-actual patterns, proposes workflow improvements.
/quarterly scores OKRs, archives stale projects, refreshes GOALS.md, cleans stale memories, audits AGENTS.md.
A complete productivity system — from ideation to execution to compounding knowledge.
Authored for Claude Code, generated to the open Agent Skills standard — so the same skills, agents, and MCP tools work in OpenAI Codex CLI, Cursor, Google Antigravity, and other conformant hosts.
.agents/skills/ tree that Codex, Cursor, Antigravity, Windsurf, and Copilot read natively.CLAUDE.md stays the thin Claude-specific overlay on top..cursor/agents/) and Codex (.codex/agents/) subagents — separate context, background execution.install_for.py splices the manager-ai MCP server into each tool's config — dry-run by default, backs up first, never clobbers other servers.Adapters are generated by build_adapters.py, which writes a manifest (.agents/skills.lock.json) and refuses to overwrite any file it cannot prove it generated; the validator (check 38) keeps them in sync. Full setup: docs/portability.md.
Clone the repo and run setup. Two paths — guided or manual.
setup.sh installs MCP server dependencies, creates workspace directories, and walks you through an interactive goals setup. Then run /refresh-goals in Claude Code to populate your goals.
| Tool | Version | Required | Install |
|---|---|---|---|
| Python | 3.11+ | Yes | brew install python@3.13 |
| uv | latest | Yes | curl -LsSf https://astral.sh/uv/install.sh | sh |
| git | any | Yes | brew install git |
| Claude Code | latest | Yes | claude.ai/download |
Each skill teaches your AI assistant a focused capability — from market validation to sprint planning. 26 specialized skills below, plus 6 daily-workflow skills that appear as commands in the next section (the 7th command, /analyze, is standalone).
Workflow automation at your fingertips — from daily standups to quarterly reviews.
--from.Each runs in its own context window, autonomously performing focused tasks in the background.
The manager-ai MCP server provides programmatic access to tasks, projects, and system state — with fuzzy deduplication built in.
| Tool | Description |
|---|---|
| list_tasks | Query tasks with filters (priority, status, category) — flags clipped bodies, lists files it could not parse |
| get_task_summary | Priority/category/status counts with time estimates |
| check_priority_limits | Alerts if P0 > 3 or P1 > 7 |
| prune_completed_tasks | Preview the done tasks older than 30 days that would move to tasks/archive/; moves them only on an explicit confirm |
| list_projects | Query projects with filters (status, priority, category) — flags clipped bodies, lists files it could not parse |
| get_pipeline_status | Count of projects at each pipeline stage |
| get_project_artifacts | Check which evaluation artifacts exist for a project |
| get_project_summary | Aggregate project stats and artifact coverage |
| get_system_status | Full dashboard — tasks + projects + backlog + time insights |
| get_watcher_status | Currency watcher status — last report, days since, undecided candidates |
| process_backlog_with_dedup | Deduplicate backlog items against existing work |
The workflow is simple — brain dump, process, evaluate, execute, compound.
Connect external services to supercharge your workflows. All are optional — the core system works standalone.
/validate-project, /research-topic, and /discover-ideas. Uses the official Perplexity MCP server (@perplexity-ai/mcp-server).claude mcp add perplexity --env PERPLEXITY_API_KEY="your_key_here" -- npx -y @perplexity-ai/mcp-server
-s user before --env to register at user scope so every Claude Code project picks it up./morning and /weekly./plugin install slack
/meeting-sync. Requires paid plan..mcp.json. Authenticates via OAuth on first use. Setup guide/meeting-prep with email history and checking your schedule.brew install googleworkspace-cli
gws auth setup once to configure Google Cloud OAuth (requires gcloud). See README for full auth steps.Run one command after any change to skills, agents, hooks, or MCP tools — 52 deterministic checks catch drift before it ships.
Inline # /// script metadata auto-installs pyyaml. No venv setup.
CLAUDE.md, and every entry in CLAUDE.md exists on disk.server.py registrations, each tool has a wired dispatch branch.AGENTS.md tree matches reality; init-workspace.sh scaffolds the documented paths.evaluating/ready/active flagged when expected artifacts (validation, pre-mortem, PRD, stories) are missing.npm, gh, or gws warn if the CLI is not on PATH..DS_Store, stray TODO/FIXME markers, stale lock files, a UTF-8 BOM that would make Claude Code skip the file, hardcoded user paths in the validator itself — plus files the ignore rules cover but git still tracks, tracked symlinks, and paths that collide under case folding.model: assignment..agents/skills/ tree stays free of Claude-only tokens.Exit 0 clean, 1 on findings. Warnings (non-blocking) — pipeline drift, a missing CLI, an unpushed main — are reported separately. Run it before every PR, alongside the pytest suite and build_adapters.py --check.
Two currency watchers track the Anthropic platform and the wider agent ecosystem, write dated decision reports, and leave every adoption decision to you — so the framework never drifts a generation behind between manual catch-ups.
Watchers fetch only the delta since the last baseline. Adopting anything is a separate, owner-gated step — the baseline advances only after adopted work is committed.
model: assignment — mechanical work runs cheap, judgment work pins higher. Adapters map tiers per host./cli-watch tracks Claude Code / Anthropic releases; /repo-watch tracks a registry of external agent frameworks. Both write dated decision reports with self-attested egress receipts — one row per fetch.get_watcher_status MCP tool plus a step in /morning and /weekly surface days since the last run and undecided candidates.docs/capabilities.md records the verified Claude Code capability surface — models, effort, workflows, scheduling, hooks — re-verified every wave as the watcher's baseline.Scheduled watcher runs are report-only behind five independent layers — restricted tool profile, write fence, egress pin, fail-closed guard, and defang on ingestion — adversarially reviewed through nine rounds of bypass attempts. The guard runs every external step under a stall budget, so a hung guard denies instead of being skipped.
The fail-closed guard denies on any parse doubt or stall and writes only the run lock and today's report, fetched web content is defanged before it can reach a report, and validator checks 39–52 keep the whole path enforced.
./setup.sh. It installs MCP server dependencies, creates the workspace (tasks/, projects/, knowledge/) plus a blank BACKLOG.md and a GOALS.md template, then walks you through an interactive goals setup. Then run /refresh-goals in Claude Code for a guided walkthrough that fills in your goals, and /morning to start your first standup..claude/skills/<name>/SKILL.md and agents in .claude/agents/<name>.md. Each uses YAML frontmatter for configuration. Everything that you invoke as a slash command is also a skill — there's one consistent pattern. You can modify existing ones or create new ones by following the same shape. Regenerate the cross-tool adapters afterwards with build_adapters.py; it writes a manifest so it never clobbers a file it didn't generate.uv run core/scripts/validate.py. The validator runs 52 deterministic checks covering frontmatter, cross-references, registry parity, MCP tool wiring, workspace shape, pipeline conformance, external CLI deps, hygiene, tracked-tree hygiene, model currency, degradation coverage, secret hygiene, the automation guard, adapter parity, and backup coverage. Exit 0 means clean. Warnings (non-blocking) are reported separately. It is one of three gates — the pytest suite and build_adapters.py --check are the others; CONTRIBUTING.md lists all three. Run them before every PR, or any time something feels off.knowledge/currency/ — and, under the guard, to just the run lock and today's report — fetches are pinned to allowlisted hosts, and a fail-closed PreToolUse guard denies anything it can't parse cleanly or that stalls past its budget. Fetched web content is defanged before it lands in a report, every report lists its own fetches as egress receipts, and the whole path went through nine rounds of adversarial review. Nothing runs unattended unless you explicitly choose it during setup; a non-interactive setup selects skip.