gem-hunt

Gem-Hunt — extensive multi-lens workspace self-improvement sweep

The repeatable form of the process that produced the agentic-perfection gems (open-loops, contraindication-registry, iatrogenics-gate, the closed self-improvement loop, ACE, …). Re-run it whenever the landscape moves (new papers, new tools, new domains) — the lenses and discipline below are the winning formula; only the findings change.

Core philosophy (the user's standing intent): fan out LARGE and wide — "there's no reason to limit the search; a gold gem unfound is a waste." Breadth-first across diverse, independent lenses beats one deep pass, because the best finds come from angles you wouldn't have prompted for. Be adversarially honest, cite, grade confidence, and converge to a decision the user steers — never silently adopt.

The method (7 steps)

1. GROUND — build the dedup-set first. Read the live workspace state (hooks in ~/.claude/hooks + settings.json, skills, ~/.mcp.json, MEMORY.md, the AGENTIC-PERFECTION-PLAN.md / OPEN-THREADS.md / CONSOLIDATED-GEM-DECISIONS.md docs) and recall memory. Assemble the explicit lists: BUILT · PLANNED-unbuilt · ABSORBED · ALREADY-FOUND-this-hunt. Every lens agent gets this set so it dedups instead of re-proposing what exists. Without it, 80% of finds are duplicates.

2. FAN OUT — one agent per DISTINCT lens (the menu that works; pick/scale to the ask, default 6-9, go to 15-20+ for "be exhaustive"):

   • cross-domain borrows — mechanisms from unmined fields (clinical medicine, intel

The anti-overfit meta-anchor (gate every adopt decision)

Hard-won lessons (do these, they cost real reruns to learn)

Deliverable