Team Constitution
Interactively create or amend the team constitution in team-ai-directives. Use when bootstrapping a new team AI directives, establishing team-wide principles for the first time, or amending existing ones.
Team Setup
Interactive setup of team AI directives. Use when bootstrapping a team directives repository from scratch, cloning an existing one, pointing to a local path, or checking an existing configuration. Auto-invoked by team-boot when a project has no configured team AI directives (self-install), and available on demand via /team-setup.
Team Skills
Browse and install team skills from the team AI directives. Use when listing, adding, or onboarding team skills to the current agent's skills directory. Supports --all to install every default and external skill at once.
Architect Implement
Generate a full Architecture Description (AD.md) from accepted ADRs using multi-agent DAG orchestration. Use when accepted ADRs exist and you need to produce or update unified architecture documentation.
Team Discover
Manually re-scan team context modules and produce a structured discovery table with relevance assessments. The CDR index is already in the system prompt; use this for explicit re-discovery.
Product Clarify
Refine and validate Product Decision Records through targeted clarification questions. Review PDR completeness, detect conflicts, approve decisions, and update status to Accepted. Use before /product-implement.
Evals Validate
Run evaluations and validate evaluator quality (SLA compliance, TPR/TNR, statistical accuracy). Executes PromptFoo or pytest DeepEval.
Workspace
Multi-repo workspace coordinator for shared team context. Initialize .adlc/ structure, configure .gitignore, discover child repos, link them as Git submodules, and audit workspace health. Use --init for first-time setup, default mode for ongoing auditing.
Levelup Clarify
Review, accept, reject, or defer Context Directive Records (CDRs) discovered by levelup-init or proposed by levelup-specify. Interactive one-CDR-at-a-time workflow.
Evals Implement
Generate executable graders and configs from goldset. Generates Python graders / metrics and auto-runs unit tests to verify grader correctness.
Levelup Init
Reverse-engineer Context Directive Records (CDRs) from an existing codebase for contribution to team-ai-directives. Use when bootstrapping team knowledge from brownfield projects.
Mission Brief
>-
Levelup Publish
Compile accepted Context Directive Records (CDRs) into team-ai-directives artifacts and create a draft PR. Builds context modules, evals goldensets, and/or skills based on CDR context types.
Evals Specify
Extract eval criteria from product specs and production failure traces (bottom-up error analysis). Writes proposed criteria to .adlc/drafts/evals/.
Evals Analyze
Analyze evaluation results and close the loop. Specification failures create local CDRs to fix agent rules; generalization failures go to evaluator backlog.
Levelup Specify
Extract Context Directive Records (CDRs) from the current session after completing work. Identifies reusable patterns (rules, personas, examples, evals) and captures directive compliance cases for team-ai-directives.
Product Analyze
Read-only analysis of PDR↔PRD consistency, PDR quality, cross-PDR conflicts, and staleness. Outputs a structured markdown report with severity-assigned findings. Use after /product-implement or periodically to detect drift.
Team Boot
Bootstrap the session with team AI directives context (constitution, CDR index, PDR/ADR indexes, skill registry). Runs automatically at session start via the event hook.
Architect Analyze
Analyze architecture for consistency between ADRs and AD, completeness, and quality issues. Use when validating generated or refined architecture artifacts, before feature development, during architecture review, or periodically to detect drift.
Product Specify
Interactive PRD exploration and Product Decision Record (PDR) creation for greenfield products. Facilitates product discovery discussions, surfaces trade-offs, and documents decisions as individual PDR files. Use when starting a new product or major pivot.
Product Implement
Generate a full Product Requirements Document (PRD.md) from accepted PDRs using multi-agent DAG orchestration. Reads individual PDR files, generates PRD sections from templates, validates output, and promotes accepted PDRs to memory. Use after /product-clarify.
Evals Clarify
Refine, cluster, and accept draft criteria into the published goldset. Isolates 20% holdout split and publishes goldset.md + goldset.json.
Evals Init
Initialize evals/{system}/ directory structure for evaluation system following EDD principles (Standalone). Choose PromptFoo or DeepEval based on tech stack, generate security baseline.
Architect Clarify
Refine and validate system-level ADRs through targeted clarification questions. Use when ADRs need review, gaps need filling, or ADR status must be approved before architecture generation.
Product Init
Reverse-engineer Product Decision Records (PDRs) from an existing codebase and documentation using multi-agent feature-area analysis (brownfield). Use when documenting product decisions inferred from an already-built product.
Product Roadmap
Track milestone progress across four layers of truth — decision state (PDR status), execution state (live issue tracker via MCP), evidence state (code-vs-PDR verification), and gate state (milestone gates). Shows honest completion, done-means warnings, and updates status only when all layers are green. Use for weekly progress checks and milestone validation.
Architect Specify
Interactive PRD exploration and system-level ADR creation for greenfield projects. Use when transforming a PRD or high-level system description into Architecture Decision Records.
Architect Init
Reverse-engineer architecture from an existing codebase to create ADRs documenting discovered decisions. Use when bootstrapping architecture documentation for brownfield projects.
Team Repair
Re-index CDR.md, .skills.json, and AGENTS.md in team-ai-directives, scan for rule conflicts, and verify directive freshness. Use when indexes are inconsistent, orphans are detected, after bulk changes, or for periodic team AI directives health validation.
Tech Radar Context
Discover and inject Tikal Israeli Tech Radar context — adoption ring, quadrant, and Tikal's opinion — for any technology, framework, database, library, or cloud tool implied by the current prompt. Model-invoked whenever a tech stack choice is being made or evaluated, similar to team-discover but scoped to the Tikal Tech Radar.