adoption-sprint-designerDesign structured AI adoption sprints (hackathons, pilots, onboarding experiences) with clear objectives, participant selection, buddy pairing, demo format, and activity-based measurement — saved to $HOME/.ai-first-kit/. Produces a complete sprint plan that forces hands-on AI usage and creates socia
agent-builderGenerate role-specific agent system prompts, tool permissions, and self-review checklists from organizational design artifacts — saved to $HOME/.ai-first-kit/ with optional framework-specific configuration for Claude Code, OpenAI Agents SDK, Anthropic Agent SDK, CrewAI, or custom frameworks. Reads t
ai-first-kitNavigate organizational redesign for AI with a structured 13-skill toolkit that produces persistent artifacts in $HOME/.ai-first-kit/. Routes founders and leaders to the right specialist skill — coordination audit, organizational genome, specification writing, quality gates, governance, role design,
coordination-auditProduce a structured organizational diagnostic that quantifies time spent on specification vs coordination vs execution, saved as a persistent audit artifact to $HOME/.ai-first-kit/. Conducts a guided 5-question interview, classifies every workflow structure by actual function, and identifies highes
evolution-auditorRun a structured organizational design health check — operationalizing the governance learning loop and decision ledger by collecting operational evidence, measuring gate effectiveness, detecting genome drift, and producing an evolution audit with routed recommendations saved to $HOME/.ai-first-kit/
governance-architectDesign and save a complete governance ecosystem for agentic operations — 6 structured documents (authority matrix, hard boundaries, escalation protocols, policy generation loop, decision ledger spec, learning loop) written to $HOME/.ai-first-kit/. Builds a four-tier decision authority model through
holdout-evaluatorValidate agent work output against hidden holdout scenarios using LLM-as-Judge evaluation, producing mapped feedback (referencing visible criteria only) and telemetry records saved to $HOME/.ai-first-kit/. Cross-references the agent's self-review evidence table against actual files to detect claims
maturity-ladderBuild a per-role human AI adoption maturity matrix with observable behaviors per level, current state assessment, barrier-informed progression paths, and visibility infrastructure — saved to $HOME/.ai-first-kit/. Measures where HUMANS actually are on the AI adoption journey — by evidence, not self-r
operationalizeDistill organizational design artifacts into an operational agent primer — a concise, agent-consumable AGENT-PRIMER.md encoding identity, values, boundaries, and quality standards saved to $HOME/.ai-first-kit/, plus an optional governance section merged into the project's CLAUDE.md. Also supports a
org-genome-builderBuild and save a structured organizational genome — 7 markdown files across identity, decision architecture, and quality standards directories in $HOME/.ai-first-kit/ — that encodes values as decision rules, quality standards as pass/fail criteria, and communication norms. Conducts an 11-question So
political-navigatorMap organizational power structures, classify resistance archetypes, design reframe strategies, and produce a sequenced change plan — saved as a political-map artifact to $HOME/.ai-first-kit/. The skill most leaders skip, and why 70% of transformations fail. Conducts per-stakeholder power mapping an
quality-gate-designerConvert human approval chains into automated quality gates with explicit pass/fail criteria and holdout-scenario validation, saving gate specifications and an index to $HOME/.ai-first-kit/. Decomposes each approval step by actual function (quality, risk, political, compliance, cultural) and designs
role-value-mapperDesign roles from value flows and specification responsibility — not job titles — producing a structured role definitions artifact saved to $HOME/.ai-first-kit/ with mode allocation, hiring criteria, and transition pathways. Decomposes each role using the Three-Variable Model (specification/coordina
specification-writerWrite and save structured specifications that pass the Stranger Test — precise enough for someone with zero context to evaluate agent output. Produces spec files in $HOME/.ai-first-kit/ at task, workflow, or governance layers, aligned with the organizational genome. Use when the user says 'write a s
usage-policy-writerGenerate a human-facing AI usage policy with approved tools, data classification, risk model explanations, and exception processes — saved to $HOME/.ai-first-kit/. Produces a policy document for HUMANS (not agents) that explains what AI tools are approved, what data can be used with AI, and the reas