Extends the Windows-gating work to the optional-skills/ tree. Every
SKILL.md that previously omitted the platforms: field now carries an
explicit declaration, which Hermes's loader (agent.skill_utils.
skill_matches_platform) honors to skip-load on incompatible OSes.
58 skills declared cross-platform (platforms: [linux, macos, windows]):
autonomous-ai-agents/blackbox, autonomous-ai-agents/honcho
blockchain/base, blockchain/solana
communication/one-three-one-rule
creative/blender-mcp, creative/concept-diagrams, creative/hyperframes,
creative/kanban-video-orchestrator, creative/meme-generation
devops/cli (inference-sh-cli), devops/docker-management
dogfood/adversarial-ux-test
email/agentmail
finance/3-statement-model, finance/comps-analysis, finance/dcf-model,
finance/excel-author, finance/lbo-model, finance/merger-model,
finance/pptx-author
health/fitness-nutrition, health/neuroskill-bci
mcp/fastmcp, mcp/mcporter
migration/openclaw-migration
mlops/accelerate, mlops/chroma, mlops/clip, mlops/guidance,
mlops/hermes-atropos-environments, mlops/huggingface-tokenizers,
mlops/instructor, mlops/lambda-labs, mlops/llava, mlops/modal,
mlops/peft, mlops/pinecone, mlops/pytorch-lightning, mlops/qdrant,
mlops/saelens, mlops/simpo, mlops/stable-diffusion
productivity/canvas, productivity/shop-app, productivity/shopify,
productivity/siyuan, productivity/telephony
research/domain-intel, research/drug-discovery, research/duckduckgo-search,
research/gitnexus-explorer, research/parallel-cli, research/scrapling
security/1password, security/oss-forensics, security/sherlock
web-development/page-agent
5 skills gated from Windows (platforms: [linux, macos]):
mlops/flash-attention - Flash Attention wheels are Linux-first; Windows
install requires building from source with CUDA
mlops/faiss - faiss-gpu has no Windows wheel; gate rather than
leak partial (faiss-cpu) support
mlops/nemo-curator - NVIDIA NeMo ecosystem has no first-class Windows path
mlops/slime - Megatron+SGLang RL stack is Linux-only in practice
mlops/whisper - openai-whisper + ffmpeg setup on Windows is
non-trivial; gate until Windows install stanza lands
Methodology: scanned every SKILL.md for Windows-hostile signals
(apt-get, brew, systemd, osascript, ptrace, X11 binaries, POSIX-only
Python APIs, Docker POSIX $(pwd) bind-mounts, explicit 'linux-only' /
'macos-only' text). 3 skills flagged as having hard signals on review:
docker-management and qdrant only had POSIX $(pwd) docker examples and
the tools themselves (Docker Desktop, Qdrant) run fine on Windows —
declared ALL. whisper had an apt/brew ffmpeg install path and nothing
else but the openai-whisper Windows install story is rough enough to
warrant gating.
Strict-over-lenient policy: when in doubt, gate. Easier to un-gate after
verified Windows support lands than to leak partial support that
manifests as mid-task failures for Windows users.
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.
Three tightly-scoped built-in skill consolidations to reduce redundancy in
the available_skills listing injected into every system prompt:
1. gguf-quantization → llama-cpp (merged)
GGUF is llama.cpp's format; two skills covered the same toolchain. The
merged llama-cpp skill keeps the full K-quant table + imatrix workflow
from gguf and the ROCm/benchmarks/supported-models sections from the
original llama-cpp. All 5 reference files preserved.
2. grpo-rl-training → fine-tuning-with-trl (folded in)
GRPO isn't a framework, it's a trainer inside TRL. Moved the 17KB
deep-dive SKILL.md to references/grpo-training.md and the working
template to templates/basic_grpo_training.py. TRL's GRPO workflow
section now points to both. Atropos skill's related_skills updated.
3. guidance → optional-skills/mlops/
Dropped from built-in. Outlines (still built-in) covers the same
structured-generation ground with wider adoption. Listed in the
optional catalog for users who specifically want Guidance.
Net: 3 fewer built-in skill lines in every system prompt, zero content
loss. Contributor authorship preserved via git rename detection.
* 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.
Remove the optional skill (redundant now that NeuTTS is a built-in TTS
provider). Replace neutts_cli dependency with a standalone synthesis
helper (tools/neutts_synth.py) that calls the neutts Python API directly
in a subprocess.
Add TTS provider selection to hermes setup:
- 'hermes setup' now prompts for TTS provider after model selection
- 'hermes setup tts' available as standalone section
- Selecting NeuTTS checks for deps and offers to install:
espeak-ng (system) + neutts[all] (pip)
- ElevenLabs/OpenAI selections prompt for API keys
- Tool status display shows NeuTTS install state
Changes:
- Remove optional-skills/mlops/models/neutts/ (skill + CLI scaffold)
- Add tools/neutts_synth.py (standalone synthesis subprocess helper)
- Move jo.wav/jo.txt to tools/neutts_samples/ (bundled default voice)
- Refactor _generate_neutts() — uses neutts API via subprocess, no
neutts_cli dependency, config-driven ref_audio/ref_text/model/device
- Add TTS setup to hermes_cli/setup.py (SETUP_SECTIONS, tool status)
- Update config.py defaults (ref_audio, ref_text, model, device)
* feat(skills): add bundled neutts optional skill
Add NeuTTS optional skill with CLI scaffold, bootstrap helper, and
sample voice profile. Also fixes skills_hub.py to handle binary
assets (WAV files) during skill installation.
Changes:
- optional-skills/mlops/models/neutts/ — skill + CLI scaffold
- tools/skills_hub.py — binary asset support (read_bytes, write_bytes)
- tests/tools/test_skills_hub.py — regression tests for binary assets
* feat(tts): add NeuTTS as local TTS provider backend
Add NeuTTS as a fourth TTS provider option alongside Edge, ElevenLabs,
and OpenAI. NeuTTS runs fully on-device via neutts_cli — no API key
needed.
Provider behavior:
- Explicit: set tts.provider to 'neutts' in config.yaml
- Fallback: when Edge TTS is unavailable and neutts_cli is installed,
automatically falls back to NeuTTS instead of failing
- check_tts_requirements() now includes NeuTTS in availability checks
NeuTTS outputs WAV natively. For Telegram voice bubbles, ffmpeg
converts to Opus (same pattern as Edge TTS).
Changes:
- tools/tts_tool.py — _generate_neutts(), _check_neutts_available(),
provider dispatch, fallback logic, Opus conversion
- hermes_cli/config.py — tts.neutts config defaults
---------
Co-authored-by: unmodeled-tyler <unmodeled.tyler@proton.me>
