* feat(skills): inject absolute skill dir and expand ${HERMES_SKILL_DIR} templates
When a skill loads, the activation message now exposes the absolute
skill directory and substitutes ${HERMES_SKILL_DIR} /
${HERMES_SESSION_ID} tokens in the SKILL.md body, so skills with
bundled scripts can instruct the agent to run them by absolute path
without an extra skill_view round-trip.
Also adds opt-in inline-shell expansion: !`cmd` snippets in SKILL.md
are pre-executed (with the skill directory as CWD) and their stdout is
inlined into the message before the agent reads it. Off by default —
enable via skills.inline_shell in config.yaml — because any snippet
runs on the host without approval.
Changes:
- agent/skill_commands.py: template substitution, inline-shell
expansion, absolute skill-dir header, supporting-files list now
shows both relative and absolute forms.
- hermes_cli/config.py: new skills.template_vars,
skills.inline_shell, skills.inline_shell_timeout knobs.
- tests/agent/test_skill_commands.py: coverage for header, both
template tokens (present and missing session id), template_vars
disable, inline-shell default-off, enabled, CWD, and timeout.
- website/docs/developer-guide/creating-skills.md: documents the
template tokens, the absolute-path header, and the opt-in inline
shell with its security caveat.
Validation: tests/agent/ 1591 passed (includes 9 new tests).
E2E: loaded a real skill in an isolated HERMES_HOME; confirmed
${HERMES_SKILL_DIR} resolves to the absolute path, ${HERMES_SESSION_ID}
resolves to the passed task_id, !`date` runs when opt-in is set, and
stays literal when it isn't.
* feat(terminal): source ~/.bashrc (and user-listed init files) into session snapshot
bash login shells don't source ~/.bashrc, so tools that install themselves
there — nvm, asdf, pyenv, cargo, custom PATH exports — stay invisible to
the environment snapshot Hermes builds once per session. Under systemd
or any context with a minimal parent env, that surfaces as
'node: command not found' in the terminal tool even though the binary
is reachable from every interactive shell on the machine.
Changes:
- tools/environments/local.py: before the login-shell snapshot bootstrap
runs, prepend guarded 'source <file>' lines for each resolved init
file. Missing files are skipped, each source is wrapped with a
'[ -r ... ] && . ... || true' guard so a broken rc can't abort the
bootstrap.
- hermes_cli/config.py: new terminal.shell_init_files (explicit list,
supports ~ and ${VAR}) and terminal.auto_source_bashrc (default on)
knobs. When shell_init_files is set it takes precedence; when it's
empty and auto_source_bashrc is on, ~/.bashrc gets auto-sourced.
- tests/tools/test_local_shell_init.py: 10 tests covering the resolver
(auto-bashrc, missing file, explicit override, ~/${VAR} expansion,
opt-out) and the prelude builder (quoting, guarded sourcing), plus
a real-LocalEnvironment snapshot test that confirms exports in the
init file land in subsequent commands' environment.
- website/docs/reference/faq.md: documents the fix in Troubleshooting,
including the zsh-user pattern of sourcing ~/.zshrc or nvm.sh
directly via shell_init_files.
Validation: 10/10 new tests pass; tests/tools/test_local_*.py 40/40
pass; tests/agent/ 1591/1591 pass; tests/hermes_cli/test_config.py
50/50 pass. E2E in an isolated HERMES_HOME: confirmed that a fake
~/.bashrc setting a marker var and PATH addition shows up in a real
LocalEnvironment().execute() call, that auto_source_bashrc=false
suppresses it, that an explicit shell_init_files entry wins over the
auto default, and that a missing bashrc is silently skipped.
15 KiB
| sidebar_position | title | description |
|---|---|---|
| 3 | Creating Skills | How to create skills for Hermes Agent — SKILL.md format, guidelines, and publishing |
Creating Skills
Skills are the preferred way to add new capabilities to Hermes Agent. They're easier to create than tools, require no code changes to the agent, and can be shared with the community.
Should it be a Skill or a Tool?
Make it a Skill when:
- The capability can be expressed as instructions + shell commands + existing tools
- It wraps an external CLI or API that the agent can call via
terminalorweb_extract - It doesn't need custom Python integration or API key management baked into the agent
- Examples: arXiv search, git workflows, Docker management, PDF processing, email via CLI tools
Make it a Tool when:
- It requires end-to-end integration with API keys, auth flows, or multi-component configuration
- It needs custom processing logic that must execute precisely every time
- It handles binary data, streaming, or real-time events
- Examples: browser automation, TTS, vision analysis
Skill Directory Structure
Bundled skills live in skills/ organized by category. Official optional skills use the same structure in optional-skills/:
skills/
├── research/
│ └── arxiv/
│ ├── SKILL.md # Required: main instructions
│ └── scripts/ # Optional: helper scripts
│ └── search_arxiv.py
├── productivity/
│ └── ocr-and-documents/
│ ├── SKILL.md
│ ├── scripts/
│ └── references/
└── ...
SKILL.md Format
---
name: my-skill
description: Brief description (shown in skill search results)
version: 1.0.0
author: Your Name
license: MIT
platforms: [macos, linux] # Optional — restrict to specific OS platforms
# Valid: macos, linux, windows
# Omit to load on all platforms (default)
metadata:
hermes:
tags: [Category, Subcategory, Keywords]
related_skills: [other-skill-name]
requires_toolsets: [web] # Optional — only show when these toolsets are active
requires_tools: [web_search] # Optional — only show when these tools are available
fallback_for_toolsets: [browser] # Optional — hide when these toolsets are active
fallback_for_tools: [browser_navigate] # Optional — hide when these tools exist
config: # Optional — config.yaml settings the skill needs
- key: my.setting
description: "What this setting controls"
default: "sensible-default"
prompt: "Display prompt for setup"
required_environment_variables: # Optional — env vars the skill needs
- name: MY_API_KEY
prompt: "Enter your API key"
help: "Get one at https://example.com"
required_for: "API access"
---
# Skill Title
Brief intro.
## When to Use
Trigger conditions — when should the agent load this skill?
## Quick Reference
Table of common commands or API calls.
## Procedure
Step-by-step instructions the agent follows.
## Pitfalls
Known failure modes and how to handle them.
## Verification
How the agent confirms it worked.
Platform-Specific Skills
Skills can restrict themselves to specific operating systems using the platforms field:
platforms: [macos] # macOS only (e.g., iMessage, Apple Reminders)
platforms: [macos, linux] # macOS and Linux
platforms: [windows] # Windows only
When set, the skill is automatically hidden from the system prompt, skills_list(), and slash commands on incompatible platforms. If omitted or empty, the skill loads on all platforms (backward compatible).
Conditional Skill Activation
Skills can declare dependencies on specific tools or toolsets. This controls whether the skill appears in the system prompt for a given session.
metadata:
hermes:
requires_toolsets: [web] # Hide if the web toolset is NOT active
requires_tools: [web_search] # Hide if web_search tool is NOT available
fallback_for_toolsets: [browser] # Hide if the browser toolset IS active
fallback_for_tools: [browser_navigate] # Hide if browser_navigate IS available
| Field | Behavior |
|---|---|
requires_toolsets |
Skill is hidden when ANY listed toolset is not available |
requires_tools |
Skill is hidden when ANY listed tool is not available |
fallback_for_toolsets |
Skill is hidden when ANY listed toolset is available |
fallback_for_tools |
Skill is hidden when ANY listed tool is available |
Use case for fallback_for_*: Create a skill that serves as a workaround when a primary tool isn't available. For example, a duckduckgo-search skill with fallback_for_tools: [web_search] only shows when the web search tool (which requires an API key) is not configured.
Use case for requires_*: Create a skill that only makes sense when certain tools are present. For example, a web scraping workflow skill with requires_toolsets: [web] won't clutter the prompt when web tools are disabled.
Environment Variable Requirements
Skills can declare environment variables they need. When a skill is loaded via skill_view, its required vars are automatically registered for passthrough into sandboxed execution environments (terminal, execute_code).
required_environment_variables:
- name: TENOR_API_KEY
prompt: "Tenor API key" # Shown when prompting user
help: "Get your key at https://tenor.com" # Help text or URL
required_for: "GIF search functionality" # What needs this var
Each entry supports:
name(required) — the environment variable nameprompt(optional) — prompt text when asking the user for the valuehelp(optional) — help text or URL for obtaining the valuerequired_for(optional) — describes which feature needs this variable
Users can also manually configure passthrough variables in config.yaml:
terminal:
env_passthrough:
- MY_CUSTOM_VAR
- ANOTHER_VAR
See skills/apple/ for examples of macOS-only skills.
Secure Setup on Load
Use required_environment_variables when a skill needs an API key or token. Missing values do not hide the skill from discovery. Instead, Hermes prompts for them securely when the skill is loaded in the local CLI.
required_environment_variables:
- name: TENOR_API_KEY
prompt: Tenor API key
help: Get a key from https://developers.google.com/tenor
required_for: full functionality
The user can skip setup and keep loading the skill. Hermes never exposes the raw secret value to the model. Gateway and messaging sessions show local setup guidance instead of collecting secrets in-band.
:::tip Sandbox Passthrough
When your skill is loaded, any declared required_environment_variables that are set are automatically passed through to execute_code and terminal sandboxes — including remote backends like Docker and Modal. Your skill's scripts can access $TENOR_API_KEY (or os.environ["TENOR_API_KEY"] in Python) without the user needing to configure anything extra. See Environment Variable Passthrough for details.
:::
Legacy prerequisites.env_vars remains supported as a backward-compatible alias.
Config Settings (config.yaml)
Skills can declare non-secret settings that are stored in config.yaml under the skills.config namespace. Unlike environment variables (which are secrets stored in .env), config settings are for paths, preferences, and other non-sensitive values.
metadata:
hermes:
config:
- key: myplugin.path
description: Path to the plugin data directory
default: "~/myplugin-data"
prompt: Plugin data directory path
- key: myplugin.domain
description: Domain the plugin operates on
default: ""
prompt: Plugin domain (e.g., AI/ML research)
Each entry supports:
key(required) — dotpath for the setting (e.g.,myplugin.path)description(required) — explains what the setting controlsdefault(optional) — default value if the user doesn't configure itprompt(optional) — prompt text shown duringhermes config migrate; falls back todescription
How it works:
-
Storage: Values are written to
config.yamlunderskills.config.<key>:skills: config: myplugin: path: ~/my-data -
Discovery:
hermes config migratescans all enabled skills, finds unconfigured settings, and prompts the user. Settings also appear inhermes config showunder "Skill Settings." -
Runtime injection: When a skill loads, its config values are resolved and appended to the skill message:
[Skill config (from ~/.hermes/config.yaml): myplugin.path = /home/user/my-data ]The agent sees the configured values without needing to read
config.yamlitself. -
Manual setup: Users can also set values directly:
hermes config set skills.config.myplugin.path ~/my-data
:::tip When to use which
Use required_environment_variables for API keys, tokens, and other secrets (stored in ~/.hermes/.env, never shown to the model). Use config for paths, preferences, and non-sensitive settings (stored in config.yaml, visible in config show).
:::
Credential File Requirements (OAuth tokens, etc.)
Skills that use OAuth or file-based credentials can declare files that need to be mounted into remote sandboxes. This is for credentials stored as files (not env vars) — typically OAuth token files produced by a setup script.
required_credential_files:
- path: google_token.json
description: Google OAuth2 token (created by setup script)
- path: google_client_secret.json
description: Google OAuth2 client credentials
Each entry supports:
path(required) — file path relative to~/.hermes/description(optional) — explains what the file is and how it's created
When loaded, Hermes checks if these files exist. Missing files trigger setup_needed. Existing files are automatically:
- Mounted into Docker containers as read-only bind mounts
- Synced into Modal sandboxes (at creation + before each command, so mid-session OAuth works)
- Available on local backend without any special handling
:::tip When to use which
Use required_environment_variables for simple API keys and tokens (strings stored in ~/.hermes/.env). Use required_credential_files for OAuth token files, client secrets, service account JSON, certificates, or any credential that's a file on disk.
:::
See the skills/productivity/google-workspace/SKILL.md for a complete example using both.
Skill Guidelines
No External Dependencies
Prefer stdlib Python, curl, and existing Hermes tools (web_extract, terminal, read_file). If a dependency is needed, document installation steps in the skill.
Progressive Disclosure
Put the most common workflow first. Edge cases and advanced usage go at the bottom. This keeps token usage low for common tasks.
Include Helper Scripts
For XML/JSON parsing or complex logic, include helper scripts in scripts/ — don't expect the LLM to write parsers inline every time.
Referencing bundled scripts from SKILL.md
When a skill is loaded, the activation message exposes the absolute skill directory as [Skill directory: /abs/path] and also substitutes two template tokens anywhere in the SKILL.md body:
| Token | Replaced with |
|---|---|
${HERMES_SKILL_DIR} |
Absolute path to the skill's directory |
${HERMES_SESSION_ID} |
The active session id (left in place if there is no session) |
So a SKILL.md can tell the agent to run a bundled script directly with:
To analyse the input, run:
node ${HERMES_SKILL_DIR}/scripts/analyse.js <input>
The agent sees the substituted absolute path and invokes the terminal tool with a ready-to-run command — no path math, no extra skill_view round-trip. Disable substitution globally with skills.template_vars: false in config.yaml.
Inline shell snippets (opt-in)
Skills can also embed inline shell snippets written as !`cmd` in the SKILL.md body. When enabled, each snippet's stdout is inlined into the message before the agent reads it, so skills can inject dynamic context:
Current date: !`date -u +%Y-%m-%d`
Git branch: !`git -C ${HERMES_SKILL_DIR} rev-parse --abbrev-ref HEAD`
This is off by default — any snippet in a SKILL.md runs on the host without approval, so only enable it for skill sources you trust:
# config.yaml
skills:
inline_shell: true
inline_shell_timeout: 10 # seconds per snippet
Snippets run with the skill directory as their working directory, and output is capped at 4000 characters. Failures (timeouts, non-zero exits) show up as a short [inline-shell error: ...] marker instead of breaking the whole skill.
Test It
Run the skill and verify the agent follows the instructions correctly:
hermes chat --toolsets skills -q "Use the X skill to do Y"
Where Should the Skill Live?
Bundled skills (in skills/) ship with every Hermes install. They should be broadly useful to most users:
- Document handling, web research, common dev workflows, system administration
- Used regularly by a wide range of people
If your skill is official and useful but not universally needed (e.g., a paid service integration, a heavyweight dependency), put it in optional-skills/ — it ships with the repo, is discoverable via hermes skills browse (labeled "official"), and installs with builtin trust.
If your skill is specialized, community-contributed, or niche, it's better suited for a Skills Hub — upload it to a registry and share it via hermes skills install.
Publishing Skills
To the Skills Hub
hermes skills publish skills/my-skill --to github --repo owner/repo
To a Custom Repository
Add your repo as a tap:
hermes skills tap add owner/repo
Users can then search and install from your repository.
Security Scanning
All hub-installed skills go through a security scanner that checks for:
- Data exfiltration patterns
- Prompt injection attempts
- Destructive commands
- Shell injection
Trust levels:
builtin— ships with Hermes (always trusted)official— fromoptional-skills/in the repo (builtin trust, no third-party warning)trusted— from openai/skills, anthropics/skillscommunity— non-dangerous findings can be overridden with--force;dangerousverdicts remain blocked
Hermes can now consume third-party skills from multiple external discovery models:
- direct GitHub identifiers (for example
openai/skills/k8s) skills.shidentifiers (for exampleskills-sh/vercel-labs/json-render/json-render-react)- well-known endpoints served from
/.well-known/skills/index.json
If you want your skills to be discoverable without a GitHub-specific installer, consider serving them from a well-known endpoint in addition to publishing them in a repo or marketplace.