lever

name	lever
description	Use when the user asks for Lever, leverage analysis, leverage AI, self-learning leverage reviews, agent-building decisions, bottleneck diagnosis, or whether work should become a reusable agent or system.

Lever

Use the live Lever CLI for leverage framing, durable learning, and agent-build decisions.

Prefer lever on PATH. If unavailable in this local environment, use:

/Users/dshanklin/repos-personal/lever/.venv/bin/lever doctor
/Users/dshanklin/repos-personal/lever/.venv/bin/lever manifesto
/Users/dshanklin/repos-personal/lever/.venv/bin/lever score "turn repeated triage into a bounded agent" --leverage-type automation --constraint "manual routing consumes founder attention" --compounding 5 --reversibility 4 --control 4 --optionality 4
/Users/dshanklin/repos-personal/lever/.venv/bin/lever agent-build "recurring inbox triage" --role "Inbox leverage scout" --repeatability 5 --boundedness 4 --proof-loop 5 --memory-fit 4 --refusal-boundary 4 --approval-risk medium
/Users/dshanklin/repos-personal/lever/.venv/bin/lever review --focus "current bottleneck"
/Users/dshanklin/repos-personal/lever/.venv/bin/lever agent "describe the work" --leverage-type optionality
/Users/dshanklin/repos-personal/lever/.venv/bin/lever learn "durable correction" --source "human correction" --evidence "short evidence" --leverage-type decision --confidence high
/Users/dshanklin/repos-personal/lever/.venv/bin/lever lessons --limit 5
/Users/dshanklin/repos-personal/lever/.venv/bin/lever distill --limit 20
/Users/dshanklin/repos-personal/lever/.venv/bin/lever improve --focus "Lever itself" --limit 20

Lever is not a generic productivity assistant. It identifies the active constraint and decides whether the highest-leverage response is an answer, artifact, reusable system, specialist agent, or durable lesson.

Lever's posture is intentionally sharp: find the constraint, build the reusable thing, kill weak loops, upgrade proven loops, and record the durable lesson.

Use lever score or lever prioritize when there is a real resource-allocation choice. It scores compounding, reversibility, control, and optionality, then returns a kill/test/upgrade decision.

Use lever agent-build when deciding whether repeated work should become a specialist agent. It scores repeatability, boundedness, proof loop, memory fit, and refusal boundary, then returns do-not-build, prototype, or build-specialist.

Treat lever learn as an explicit learning action. Use it when the human corrects the frame or when verified outcomes show a durable leverage principle. Do not silently store secrets, credentials, payment details, private messages, or weak one-off inferences.

Use lever distill after several explicit lessons have accumulated. It summarizes the learning log into operating takeaways; it does not mutate hidden preferences or cross approval gates.

Use lever improve when the user asks to improve Lever or when distilled lessons should become a concrete hardening backlog. Treat its output as a plan: make a code, docs, tests, score-threshold, or task-state change before claiming Lever improved.

Keep this plugin thin. Source-owned behavior and durable learning state belong in the canonical Lever CLI repo.