Model Profiler

Impartially PROFILE the cross-provider sub-agent fleet against the FIXED canonical 10 work-categories whenever a new model ships (or on demand). Discover every model published in the recent window by the in-scope provider families, gather ALL public benchmark scores + statistics, map them onto the fixed 10 categories, then JUDGE each model+effort pairing into per-category tier rankings (best→worst) SOLELY from the discovered research, with a recorded rationale per tier placement. Emits exactly 3 artifacts: routing-table.json (lean), routing-table-audit.json (full provenance), research-seed-sites.json (accumulating learned source list). Single-family and multi-family are both fully-supported, first-class paths; provider mix is optional. The 10 categories are immutable inputs — this skill never derives, chooses, renames, reorders, or reshuffles them. Use when a new model is released, when asked to profile new model, re-profile models, re-profile the fleet, rebalance routing, update routing table, refresh model profiles, re-run model research, regenerate routing-table.json, refresh tier rankings, or to answer "which model for X now" after a model launch. Orchestrator-only pipeline: model discovery + maximalist benchmark research, pivotal-question interview, flagship judging + merge, 3-artifact emission, 3-pass adversarial validation, and provider/seed validators + scenario routing tests. Sub-agents dispatched via `mcp__subagent-mcp__launch_agent`; cross-family critics are available when ≥2 families are reachable.

mkdir -p ~/.claude/skills/model-profiler
curl -L https://claudskills.com/skills/model-profiler/SKILL.md \
  -o ~/.claude/skills/model-profiler/SKILL.md

@misc{model-profiler-2026,
  author    = {Lexi Blackburn (https://github.com/Heretyc/)},
  title     = {Model Profiler [Claude Code skill]},
  year      = {2026},
  publisher = {ClaudSkills},
  url       = {https://claudskills.com/skills/model-profiler/}
}