Cortex Setup Project

Setup Project — Fully Autonomous Bootstrap

Execute all four phases sequentially without asking the user any questions. If a phase fails, attempt automatic recovery before reporting the error. Never ask the user to run commands manually or choose between options.

Phase 1: Infrastructure Verification

1. Call cortex:memory_stats({}) to verify store connectivity. If it succeeds, the store is healthy — this covers both backends (the zero-config SQLite default needs no PostgreSQL, so do NOT run pg_isready or any PostgreSQL setup when this passes). Proceed to Phase 2.
2. Only if memory_stats fails: call cortex:check_setup({}) (backend-aware diagnostics) to identify the failure.

• SQLite backend reported: fix per the check output (usually ~/.claude/methodology permissions or a corrupt memory.db); do NOT install PostgreSQL.
• PostgreSQL backend reported: run pg_isready via bash, then bash "${CLAUDE_PLUGIN_ROOT}/scripts/setup.sh" automatically. Do not ask for permission. After setup.sh completes, call cortex:memory_stats({}) again to verify.
• If it still fails, report the error output and stop. Do not continue to later phases.

Phase 2: Build Methodology Profiles

1. Call cortex:rebuild_profiles({"force": true}) to scan all session history and build cognitive profiles per domain.
2. This creates the domain hubs that memories, entities, and discussions link to. It must run before seeding.
3. Record the domain count for the final summary.

Phase 3: Codebase Seeding

1. Call cortex:seed_project({"directory": ""}) where `` is the current working directory.
2. Record the count of discoveries for the final summary.

Phase 3b: Pipeline Codebase Analysis (Optional)

The ai-automatised-pipeline MCP server provides structured codebase analysis (symbol graph, processes, communities, cross-file impact). It is optional — Cortex core memory/recall works without it. Enable only if the user asks for "deeper code understanding", "symbol-level memory", or the codebase is large (>5k files) where substring-based hooks underperform.

1. Detection: attempt cortex:ingest_codebase({"project_path": ""}). If it succeeds, record the counts (wiki pages, memory entities, KG edges) for the summary and skip to Phase 4.
2. If ingest_codebase fails with McpConnectionError (pipeline not installed/configured):

• Check if the sibling checkout exists at ../anthropic/ai-automatised-pipeline/Cargo.toml (or equivalent). If so, run bash -c 'cd ../anthropic/ai-automatised-pipeline && cargo install --path . 2>&1 | tail -20' (accepts ~1-2 min compile) and re-run the ingest.
• If the source checkout is missing or cargo is unavailable, skip Phase 3b silently and proceed to Phase 4. Do NOT block setup on this.

1. The pipeline's auto-wire happens on every SessionStart via pipeline_discovery, so once the binary exists on PATH (or sibling source is built), future sessions pick it up automatically. No manual mcp-connections.json editing needed.

Phase 4: History Import

1. Call cortex:backfill_memories({"dry_run": true, "max_files": 500}) to preview available session files.
2. If files are available, call cortex:backfill_memories({"max_files": 500, "min_importance": 0.35}) to import.
3. Record the count of imported memories for the final summary.

Phase 5: Consolidation and Verification

1. Call cortex:consolidate({}) to run decay, compression, CLS, and causal discovery on all memories.
2. Call cortex:memory_stats({}) to get the final system state.
3. Call cortex:detect_gaps({}) to identify knowledge gaps.

Final Summary

After all phases complete, print a single summary block:

Cortex Setup Complete
---------------------
Domains:         
Memories stored: 
Entities:        
Relationships:   
Pipeline:        
Gaps found:      

Do not print intermediate status updates between phases beyond what the tool calls themselves return. One summary at the end.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: cdeust
• Source: cdeust/Cortex
• License: MIT
• Homepage: https://ai-architect.tools

Install and usage instructions live in the source repository linked above.