42 skills · sorted by relevance
Configure Google Cloud logs across multiple projects, either by storing them centrally or querying them together where they already reside. The skill guides routing, access permissions, and log views, and helps diagnose missing logs and permission failures.
Configure and troubleshoot Google Cloud cross-project centralized logging and read-time aggregation. Use when: - Setting up log routing from multiple projects/folders/organizations to a central log bucket. - Creating cross-project log sinks and configuring central log buckets. - Troubleshooting cross-project routing. Don't use for single-project basic configurations.
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Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface: 6 tools with --full (adds check_action); 13 tools with AR_EXTRAS=1 --full. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.
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Persistent compounding memory for AI agents. 5 default MCP tools: session_start, session_end, remember, recall, check. Full surface (18 tools) available with --full flag. Two-verb model: inhale (session_start) and exhale (session_end). Correction-first memory with decision trail tracking, watch_for warnings, palace rooms with salience scoring, cross-project insight matching, same-day journal merging, ambient recall hooks. Local markdown only. Zero cloud, zero telemetry, Obsidian-compatible. Optional Supabase backend: when configured via `ar setup supabase`, recall() uses pgvector cosine similarity on OpenAI/Voyage embeddings instead of keyword search — same API, semantic understanding. Gracefully degrades to local search if not configured.
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Turn Claude Code session patterns into reusable behavior rules with confidence scores. Keep project-specific lessons separate, review and share learned rules, and combine related patterns into skills, commands, or agents.
Review and refine code using shared conventions for clear names, readability, error handling, and updates that preserve original data. Identify duplication, oversized functions, and unnecessary complexity to make code easier to understand and maintain.
Import Claude Code auto-memory into AgentDB and search past notes by meaning across sessions and projects. The skill checks import status, consolidates near-duplicate entries, and returns search results with their memory sources identified.
Audit Google Cloud access permissions to find overly broad roles, unnecessary service account keys, public access, and impersonation risks. Use gcloud CLI, Policy Analyzer, and IAM Recommender to document findings and plan more limited permissions.
Creates Terraform configuration for Google Cloud Monitoring notification channels, including email, Slack, and Pub/Sub, and attaches channels to existing alert policies. It also checks Pub/Sub topic compatibility and publishing permissions when inspecting the cloud environment.
Configure Cloud Logging within one Google Cloud project. Set storage locations, retention periods, routing rules, and viewing permissions; create metrics from logs; and adjust stored volume through exclusions or sampling, which retains only a portion of entries.
Set up a new Obsidian vault, a folder for linked notes, or adopt an existing one. Select the working vault and route requests to the appropriate skills for importing sources, answering questions, saving results, or maintenance.
[omh] Recurring lessons worth promoting: turn repeated project or cross-project lessons into atomic, confidence-scored instinct candidates with scoped promotion and export boundaries. Use when the user says: instinct-ledger, instinct ledger, project instincts, project-scoped instincts, project scoped instincts, global instincts, instinct review, instinct candidate.
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Pattern extraction, confidence-scored evaluation, skill creation, organization, versioning, and cross-project export pipeline.
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Coordinate coding agents through AMQ. Use for agent messages, inboxes, receipts, sessions, wake delivery, cross-project routing, managed launches, or AMQ diagnostics. Use amq-spec for collaborative design; do not use this for general message queues or single-agent work.
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Weekly engineering retrospective. Analyzes commit history, work patterns, and code quality metrics. Per-person breakdowns with praise and growth areas. Modes: default 7d, 24h, 14d, 30d, compare, global cross-project. Shipping streaks and tweetable summary.
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Weekly cross-project error overview from PostHog - enumerates every project the OAuth grant covers, pulls the last 7 days of error-tracking issues per project, ranks them by impact, flags what's new vs ongoing, and sends one digest with per-project totals, the top issues, and a clickable link to a full committed report of every issue.
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Build, maintain, and audit design systems — tokens, component libraries, style guides, and cross-project consistency. Use when asked to create a design system, define tokens, audit component consistency, generate a style guide, or sync design tokens with code.
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Audit, generate, update, and lint AGENTS.md files across all projects. Use when asked to check project context files, scaffold AGENTS.md for new projects, update stale ones, or run a cross-project audit.
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Manage Espen's projects across the Dev folder and Obsidian vault. Use for project status checks, creating new projects, syncing between code repos and vault notes, archiving, and cross-project search.
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Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.
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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.
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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.
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Verify and lock project identity before ANY git push, Cloudflare deploy, or Supabase operation. Essential when working with multiple GitHub accounts (personal + work), multiple Cloudflare accounts, or multiple Supabase/Neon projects. Prevents wrong-account deploys, cross-project secret leaks, and git history contamination.
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Conduct a structured cross-project code review between two Claude Code instances via the cross-review-mcp broker. Each agent reads its own codebase, reviews the peer's code, and engages in evidence-backed dialogue — with QSG scaling laws enforcing review quality through minimum bandwidth constraints and phase-gated progression.
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