- refs/ -> references/, the folder name the Agent Skills spec uses and the one
Hermes skips when it walks for nested skills.
- rl and pinn declared name: rl and name: pinn, which are global names in a flat
skill namespace. Now ml-debug-rl and ml-debug-pinn. They also called themselves
sub-skills of 'ml-debugging', which is not this skill's name.
- Drop the dead link to SKILL_old.md. It moved into gitignored slop/, so the link
was broken for anyone who cloned.
- Route references/llm_judge_litreview.md, the one reference SKILL.md never named.
- Description leads with the trigger situations. Hermes truncates it to 57 chars.
Co-Authored-By: Claudypoo <288921227+claudypoo@users.noreply.github.com>
An /abs/ link is a stub: it costs a second lookup before anyone can check the
quote, and it is what let abstract-only caches look sourced. 77 links across
the skill files and 4 cache headers. Verbatim source bodies untouched, their
reference lists are the authors' text.
Checked every 2001.04536 / 2402.01868 citation against the full texts now in
docs/evidence. Two quotation-marked sentences were not in the papers; the
Helmholtz 49x figure does not exist and the 64x Klein-Gordon one belongs to
architecture+annealing, not architecture alone; the Wang 1e5 Hessian number is
a max eigenvalue, not a max/min ratio. Section, table and figure pointers fixed.
Add 3 new evidence files from modern open-source sources:
- karpathy_recipe_training_nn_2019.md: Karpathy's training recipe blog post
- nanochat_deepwiki_llm_pretraining_2026.md: 320+ HP sweeps for GPT-2-scale pretraining
- sanh_simple_considerations_hf_2021.md: HuggingFace NLP debugging notes
Add update-to-data ratio diagnostic to refs/diagnostics.md (target ~1e-3).
Add LLM pretraining gap note to SKILL.md intro linking the new sources.
Add tanh saturation % to logging checklist.
Moved heat-exchanger-specific content from pinn/SKILL.md to
pinn/refs/heat_exchanger.md: complexity ladder table, known failure
modes (U->0, counterflow signs), property mappings (REFPROP/PCHIP),
multi-episode training. PINN skill is now domain-agnostic.
pinn/SKILL.md reduced from 4961w to 4274w (~14%).
