Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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A relentless interview to sharpen a plan or design, which also builds the project's domain model — glossary and ADRs — as it goes. Use in a working directory whenever an idea needs sharpening.
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See how to installReview the instructions the agent will receive before you install.
Invoke two skills and run them together: grilling and domain-modeling.
Neither is restated here. grilling supplies the interview — design tree, frontier rounds, numbered questions with a recommended answer each. domain-modeling supplies the discipline that runs underneath it: challenging terms against the glossary, sharpening fuzzy language, stress-testing relationships with concrete scenarios, and writing what is settled into CONTEXT.md and docs/adr/ as it crystallises, not batched at the end.
Prefer this over grill-me whenever there is a repo to leave a trail in. The interview is identical; the difference is whether the shared understanding survives the session. Use grill-me when there is no working directory, or when the outcome is a decision rather than a document.
Grilling produces a shared understanding, not an execution plan. When the frontier is empty, pick the pipeline the work actually needs:
/startcycle — a straight run with file hand-offs; the usual choice/startcycle-graph — when the durable state.json, the Reviewer repair loop and human escalation earn their overhead/startcycle-graph-user — a throwaway 2–4 node fan-out, nothing persistent left behind/bdbrainstorm and /bdbmediastorm run this interview as their own first step; do not run it twice.
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Use when manage multiple local CLI agents via tmux sessions (start/stop/monitor/assign) with cron-friendly scheduling.
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Use when a hybrid memory system that provides persistent, searchable knowledge management for AI agents (Architecture, Patterns, Decisions).
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Reference for how BDB structures autonomous software engineering work — the seven-node dispatcher graph (Architect, TechLead, UI/UX, Engineering, Media/EventTech, Reviewer, Shipping) that /startcycle-graph actually runs. Use when you need the high-level lifecycle framing without inventing your own process.
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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling.
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Harness patterns for coding agents — memory, permissions, context engineering, delegation, skills, hooks, bootstrap.
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agenttrail: live map of a multi-agent build in the browser: which plan component is being worked on, by which agent or harness, what is done and what is stuck. Use when a multi-agent pipeline starts (/startcycle, /startcycle-graph, /teamwork-preview) or after a plan-canvas approve, when the user asks to see what the agents are doing ("live map", "build board", "who is running now"), or by yourself whenever a multi-agent run is under way — no user prompt needed.
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