# Curator run — 2026-06-20T23:35:13.715363+00:00

Model: `stepfun/step-3.7-flash:free` via `nous`  ·  Duration: 3m 46s  ·  Agent-created skills: 73 → 73 (+0)

## Auto-transitions (pure, no LLM)

- checked: 73
- marked stale: 0
- archived (no LLM, pure time-based staleness): 0
- reactivated: 0

## LLM consolidation pass

- tool calls: **36** (by name: search_files=1, skill_manage=1, skill_view=28, terminal=6)
- consolidated into umbrellas: **0**
- pruned (archived for staleness): **0**
- new skills this run: **0**
- state transitions (active ↔ stale ↔ archived): **0**

## LLM final summary

I've now read enough to map all clusters. Here's my analysis:

**Confirmed clusters:**
1. **github siblings** (6 skills: github-auth, github-repo-management, github-issues, github-pr-workflow, github-code-review, github-trending-reporting) → umbrella is `github` (already has all sections, just needs siblings archived)
2. **Claude Code / Codex / OpenCode** — duplicated across `autonomous-ai-agents/` and `kanban-suite/autonomous-ai-agents/` (3 pairs × 2 = 6 total, 3 identical copies in kanban-suite)
3. **QRS vs software-development duplicates** (4 pairs: systematic-debugging, simplify-code, spike, test-driven-development) — all byte-identical, keep the QRS home

That gives 13 archives total. Let me execute. First, create the reference file for github-trending-reporting's unique session-specific details, then archive all 13.

## Recovery

- Restore an archived skill: `hermes curator restore <name>`
- All archives live under `~/.hermes/skills/.archive/` and are recoverable by `mv`
- See `run.json` in this directory for the full machine-readable record.