Double-model verification gate before declaring a build/research/refactor "done". Runs a fresh Anthropic (Claude) review AND an independent OpenAI/Azure critic against the stated goal + criteria, then reconciles. Use before announcing completion of medium/major builds, refactors, major fixes, research deliverables, frontend work, or trade-decision rigor — and on demand via /verify. Skip for small Q&A and trivial edits.
Record and retrieve Architecture Decision Records — log a decision's context, options, rationale, and tradeoffs, then list/search them. Use when making a non-trivial design or architecture decision, choosing between tools/approaches, or asked 'why did we do it this way?'
Queue an external action (Telegram message, shell command, GitHub comment, PR merge, file write) for the user's explicit approval before it runs. Use when you want to take an outward-facing or irreversible action that needs sign-off first.
Run a structured multi-position debate over an analytical question, spawning sub-agents to argue each option and counter confirmation bias. Use when comparing options or tradeoffs — 'which is better', 'should we', 'what's the risk', 'evaluate', 'compare options'.
Ingest documents (URLs, local files, PDFs) into a searchable local knowledge base and query stored knowledge. Use when ingesting or storing documents, searching previously stored knowledge, or building research context.
Collect macro market and economic-calendar data (yfinance + FairEconomy API) into a SQLite DB and generate a formatted macro briefing for Telegram. Use when producing a macro/markets briefing or collecting macro market data.
Watch any URL for meaningful changes — price moves, new releases (semver), hiring signals, content diffs, keyword appear/disappear — and alert. Use when tracking competitors, releases, or job postings, or detecting content changes on a web page.
Classify a task and pick the right Claude model tier (haiku/sonnet/opus) before significant work. Use every time before spawning a sub-agent or starting substantial work, to right-size the model to the task.