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4 commits

Author SHA1 Message Date
teknium1
1c646499b6 fix(skills): sync mlops training/model-infra skills to current APIs
Seven optional mlops training skills had stale APIs, config paths, image locations, and requirement pins. Verified against upstream and corrected:

- torchtitan: removed TOML train_configs paths (replaced upstream by config registry)
- trl-fine-tuning: PPO removed from TRL 1.x -> GRPO/RLOO; SFTTrainer tokenizer= -> processing_class
- flash-attention: torch.backends.cuda.sdp_kernel (deprecated) -> torch.nn.attention.sdpa_kernel; corrected false FA3/FP8-in-pip claim (FA2 only)
- accelerate: DeepSpeedPlugin instance not raw dict; --config_file expects accelerate YAML; auto_wrap_policy -> transformer_based_wrap
- saelens: v6 nested training config (sae=/logger=); from_pretrained tuple -> from_pretrained_with_cfg_and_sparsity
- tensorrt-llm: Docker Hub image 404 -> NGC nvcr.io; rc pin -> GA; CUDA req updated
- nemo-curator: pip extras renamed; repo moved to NVIDIA-NeMo/Curator; 1.x pipeline rewrite noted
2026-07-24 08:18:05 -07:00
Teknium
b0ef72a8a0 docs(skills): bring 69 skill descriptions under the 60-char authoring budget
Every SKILL.md description over 60 chars was silently truncated to
57 chars + '...' in the system-prompt skill index
(extract_skill_description, agent/skill_utils.py), destroying the
routing signal for 69 of 179 skills — some descriptions ran to
1,005 chars.

Rewrites follow the authoring standard: <=60 chars, one sentence,
ends with a period, trigger front-loaded, no marketing words, no
skill-name repetition. Excess detail already lives in each skill's
body.

Includes the touchdesigner-mcp trim from PR #32361 (credit:
@JeliTron) and aligns with the router-precision direction of PR
#48780 (@John-Lussier). Docs catalogs + per-skill pages regenerated
via website/scripts/generate-skill-docs.py.

Co-authored-by: JeliTron <287797501+JeliTron@users.noreply.github.com>
2026-07-23 21:07:16 -07:00
Teknium
b18b17f9c9 feat(skills): gate 7 Linux/macOS-only skills from Windows via platforms frontmatter
Hermes's skill loader (agent/skill_utils.skill_matches_platform) already honors
the 'platforms:' frontmatter field and skip-loads skills whose declared
platform list doesn't include sys.platform. Seven bundled skills are in fact
Linux/macOS-only but never declared it, so they leak into Windows skill
listings and sometimes load with broken instructions.

Audited all 160 SKILL.md files (skills/ + optional-skills/) for Windows-
hostile signals: apt-get/brew/systemd/chmod+x install flows, ptrace/proc
runtime dependencies, bash-only launcher scripts, and package dependencies
with no Windows build. The 7 below fail one or more of those tests in a way
that fundamentally can't be papered over by docs edits:

  minecraft-modpack-server      bash start.sh + chmod +x + apt openjdk
  evaluating-llms-harness       lm-eval-harness bash launcher scripts
  distributed-llm-pretraining-
  torchtitan                    bash multi-node torchrun launcher
  python-debugpy                remote attach relies on /proc ptrace_scope
  pytorch-fsdp                  NCCL backend; Windows path is WSL only
  tensorrt-llm                  NVIDIA TensorRT-LLM has no Windows build
  searxng-search                Docker volume flow assumes POSIX $(pwd)

All seven get 'platforms: [linux, macos]'. On Windows the loader now skips
them silently — no more phantom skill listings, no more mid-task failures
because an Apple-only path was surfaced as a suggestion.

Cross-platform skills that merely CONTAIN signals in examples or
install-instructions (brew install as one of several paths, /tmp/ in a code
snippet, etc.) are NOT touched by this commit. A broader audit that
declares the ~140 cross-platform skills as 'platforms: [linux, macos,
windows]' can follow as a separate change once each has been verified
working on Windows.

The installed user copies under ~/AppData/Local/hermes/skills/ (when they
exist) are also patched so the running session reflects the gating
immediately, but only the in-repo files are committed here.
2026-05-08 14:27:40 -07:00
Teknium
5ceed021dc
feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap (#3934)
* feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap

Map active skills to Telegram's slash command menu so users can
discover and invoke skills directly. Three changes:

1. Telegram menu now includes active skill commands alongside built-in
   commands, capped at 100 entries (Telegram Bot API limit). Overflow
   commands remain callable but hidden from the picker. Logged at
   startup when cap is hit.

2. New /commands [page] gateway command for paginated browsing of all
   commands + skills. /help now shows first 10 skill commands and
   points to /commands for the full list.

3. When a user types a slash command that matches a disabled or
   uninstalled skill, they get actionable guidance:
   - Disabled: 'Enable it with: hermes skills config'
   - Optional (not installed): 'Install with: hermes skills install official/<path>'

Built on ideas from PR #3921 by @kshitijk4poor.

* chore: move 21 niche skills to optional-skills

Move specialized/niche skills from built-in (skills/) to optional
(optional-skills/) to reduce the default skill count. Users can
install them with: hermes skills install official/<category>/<name>

Moved skills (21):
- mlops: accelerate, chroma, faiss, flash-attention,
  hermes-atropos-environments, huggingface-tokenizers, instructor,
  lambda-labs, llava, nemo-curator, pinecone, pytorch-lightning,
  qdrant, saelens, simpo, slime, tensorrt-llm, torchtitan
- research: domain-intel, duckduckgo-search
- devops: inference-sh cli

Built-in skills: 96 → 75
Optional skills: 22 → 43

* fix: only include repo built-in skills in Telegram menu, not user-installed

User-installed skills (from hub or manually added) stay accessible via
/skills and by typing the command directly, but don't get registered
in the Telegram slash command picker. Only skills whose SKILL.md is
under the repo's skills/ directory are included in the menu.

This keeps the Telegram menu focused on the curated built-in set while
user-installed skills remain discoverable through /skills and /commands.
2026-03-30 10:57:30 -07:00