For 14 of 74 compressed skills, the original description contained
trigger keywords, technique counts, attribution, or use-case phrases
not covered by the existing body content. Prepends a 'When to use' /
'What's inside' block near the top so the agent still has the full
context when the skill is loaded.
Skills salvaged:
- codex, ascii-video, creative-ideation, excalidraw, manim-video, p5js
- gif-search, heartmula, youtube-content
- lm-evaluation-harness, obliteratus, vllm, axolotl
- powerpoint
Remaining 60 skills were verified to already cover the dropped content
in their existing body sections (When to Use, overview, intro prose)
or had short descriptions fully captured by the new compressed form.
Target: every skill's description fits in a one-line gateway menu and
leads with trigger keywords an agent would match on. Drops filler like
'Use this skill to', 'A skill for', 'This skill provides'.
Before: max description length was 791 chars (architecture-diagram),
74 of 81 built-in skills were >60 chars.
After: max 60, mean 54, all 81 built-in skills <=60.
Rewritten with double-quoted YAML scalars to preserve Chinese/arrow
glyphs (baoyu-comic, yuanbao, youtube-content).
Adds a 'Video Guide' section pointing at the walkthrough of a Hermes agent
abliterating Gemma with OBLITERATUS, so the agent can surface it when the
user wants a visual overview before running the workflow.
- Description truncated to 60 chars in system prompt (extract_skill_description),
so the 500-char HF workflow description never reached the agent; shortened to
'llama.cpp local GGUF inference + HF Hub model discovery.' (56 chars).
- Restore llama-cpp-python section (basic, chat+stream, embeddings,
Llama.from_pretrained) and frontmatter dependencies entry.
- Fix broken 'Authorization: Bearer ***' curl line (missing closing quote;
llama-server doesn't require auth by default).
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.
