* feat(image_gen): multi-model FAL support with picker in hermes tools
Adds 8 FAL text-to-image models selectable via `hermes tools` →
Image Generation → (FAL.ai | Nous Subscription) → model picker.
Models supported:
- fal-ai/flux-2/klein/9b (new default, <1s, $0.006/MP)
- fal-ai/flux-2-pro (previous default, kept backward-compat upscaling)
- fal-ai/z-image/turbo (Tongyi-MAI, bilingual EN/CN)
- fal-ai/nano-banana (Gemini 2.5 Flash Image)
- fal-ai/gpt-image-1.5 (with quality tier: low/medium/high)
- fal-ai/ideogram/v3 (best typography)
- fal-ai/recraft-v3 (vector, brand styles)
- fal-ai/qwen-image (LLM-based)
Architecture:
- FAL_MODELS catalog declares per-model size family, defaults, supports
whitelist, and upscale flag. Three size families handled uniformly:
image_size_preset (flux family), aspect_ratio (nano-banana), and
gpt_literal (gpt-image-1.5).
- _build_fal_payload() translates unified inputs (prompt + aspect_ratio)
into model-specific payloads, merges defaults, applies caller overrides,
wires GPT quality_setting, then filters to the supports whitelist — so
models never receive rejected keys.
- IMAGEGEN_BACKENDS registry in tools_config prepares for future imagegen
providers (Replicate, Stability, etc.); each provider entry tags itself
with imagegen_backend: 'fal' to select the right catalog.
- Upscaler (Clarity) defaults off for new models (preserves <1s value
prop), on for flux-2-pro (backward-compat). Per-model via FAL_MODELS.
Config:
image_gen.model = fal-ai/flux-2/klein/9b (new)
image_gen.quality_setting = medium (new, GPT only)
image_gen.use_gateway = bool (existing)
Agent-facing schema unchanged (prompt + aspect_ratio only) — model
choice is a user-level config decision, not an agent-level arg.
Picker uses curses_radiolist (arrow keys, auto numbered-fallback on
non-TTY). Column-aligned: Model / Speed / Strengths / Price.
Docs: image-generation.md rewritten with the model table and picker
walkthrough. tools-reference, tool-gateway, overview updated to drop
the stale "FLUX 2 Pro" wording.
Tests: 42 new in tests/tools/test_image_generation.py covering catalog
integrity, all 3 size families, supports filter, default merging, GPT
quality wiring, model resolution fallback. 8 new in
tests/hermes_cli/test_tools_config.py for picker wiring (registry,
config writes, GPT quality follow-up prompt, corrupt-config repair).
* feat(image_gen): translate managed-gateway 4xx to actionable error
When the Nous Subscription managed FAL proxy rejects a model with 4xx
(likely portal-side allowlist miss or billing gate), surface a clear
message explaining:
1. The rejected model ID + HTTP status
2. Two remediation paths: set FAL_KEY for direct access, or
pick a different model via `hermes tools`
5xx, connection errors, and direct-FAL errors pass through unchanged
(those have different root causes and reasonable native messages).
Motivation: new FAL models added to this release (flux-2-klein-9b,
z-image-turbo, nano-banana, gpt-image-1.5, ideogram-v3, recraft-v3,
qwen-image) are untested against the Nous Portal proxy. If the portal
allowlists model IDs, users on Nous Subscription will hit cryptic
4xx errors without guidance on how to work around it.
Tests: 8 new cases covering status extraction across httpx/fal error
shapes and 4xx-vs-5xx-vs-ConnectionError translation policy.
Docs: brief note in image-generation.md for Nous subscribers.
Operator action (Nous Portal side): verify that fal-queue-gateway
passes through these 7 new FAL model IDs. If the proxy has an
allowlist, add them; otherwise Nous Subscription users will see the
new translated error and fall back to direct FAL.
* feat(image_gen): pin GPT-Image quality to medium (no user choice)
Previously the tools picker asked a follow-up question for GPT-Image
quality tier (low / medium / high) and persisted the answer to
`image_gen.quality_setting`. This created two problems:
1. Nous Portal billing complexity — the 22x cost spread between tiers
($0.009 low / $0.20 high) forces the gateway to meter per-tier per
user, which the portal team can't easily support at launch.
2. User footgun — anyone picking `high` by mistake burns through
credit ~6x faster than `medium`.
This commit pins quality at medium by baking it into FAL_MODELS
defaults for gpt-image-1.5 and removes all user-facing override paths:
- Removed `_resolve_gpt_quality()` runtime lookup
- Removed `honors_quality_setting` flag on the model entry
- Removed `_configure_gpt_quality_setting()` picker helper
- Removed `_GPT_QUALITY_CHOICES` constant
- Removed the follow-up prompt call in `_configure_imagegen_model()`
- Even if a user manually edits `image_gen.quality_setting` in
config.yaml, no code path reads it — always sends medium.
Tests:
- Replaced TestGptQualitySetting (6 tests) with TestGptQualityPinnedToMedium
(5 tests) — proves medium is baked in, config is ignored, flag is
removed, helper is removed, non-gpt models never get quality.
- Replaced test_picker_with_gpt_image_also_prompts_quality with
test_picker_with_gpt_image_does_not_prompt_quality — proves only 1
picker call fires when gpt-image is selected (no quality follow-up).
Docs updated: image-generation.md replaces the quality-tier table
with a short note explaining the pinning decision.
* docs(image_gen): drop stale 'wires GPT quality tier' line from internals section
Caught in a cleanup sweep after pinning quality to medium. The
"How It Works Internally" walkthrough still described the removed
quality-wiring step.
llm-wiki was the only shipped skill using metadata.hermes.config, which
caused 'hermes update' and 'hermes config migrate' to prompt for a wiki
directory on every run — even for users who have never touched the skill
— because 'enabled' is opt-out (all shipped skills count as enabled unless
explicitly disabled). Declining the prompt didn't persist anything, so
the nag fired again on every update.
Switch llm-wiki to the env var + runtime default pattern that obsidian and
google-workspace already use: WIKI_PATH env var, default $HOME/wiki. No
prompting infrastructure, no config.yaml touch, no nag loop.
Changes:
- skills/research/llm-wiki/SKILL.md: remove metadata.hermes.config,
document WIKI_PATH env var in the Wiki Location section, update the
orientation snippet and initialization guidance.
- Docs: replace llm-wiki's wiki.path examples with a generic 'myplugin.path'
placeholder across configuration.md, features/skills.md, and
creating-skills.md so users don't try to set skills.config.wiki.path
expecting llm-wiki to use it.
- skills-catalog.md: mention WIKI_PATH instead of skills.config.wiki.path.
E2E verified: discover_all_skill_config_vars() and get_missing_skill_config_vars()
both return 0 entries after this change, so the prompt branch in migrate_config()
no longer fires.
The metadata.hermes.config feature stays in place for third-party skills
that genuinely need structured config, but built-ins now prefer env vars.
- New page: user-guide/features/tool-gateway.md covering eligibility,
setup (hermes model, hermes tools, manual config), how use_gateway
works, precedence, switching back, status checking, self-hosted
gateway env vars, and FAQ
- Added to sidebar under Features (top-level, before Core category)
- Cross-references from: overview.md, tools.md, browser.md,
image-generation.md, tts.md, providers.md, environment-variables.md
- Added Nous Tool Gateway subsection to env vars reference with
TOOL_GATEWAY_DOMAIN, TOOL_GATEWAY_SCHEME, TOOL_GATEWAY_USER_TOKEN,
and FIRECRAWL_GATEWAY_URL
Pass platform_env_var="TELEGRAM_PROXY" to resolve_proxy_url() in both
telegram.py (main connect) and telegram_network.py (fallback transport),
so a Telegram-specific proxy takes priority over the generic HTTPS_PROXY.
Also bridge telegram.proxy_url from config.yaml to the TELEGRAM_PROXY
env var (env var takes precedence if both are set), add OPTIONAL_ENV_VARS
entry, docs, and tests.
Composite salvage of four community PRs:
- Core approach (both call sites): #9414 by @leeyang1990
- config.yaml bridging + docs: #6530 by @WhiteWorld
- Naming convention: #9074 by @brantzh6
- Earlier proxy work: #7786 by @ten-ltw
Closes#9414, closes#9074, closes#7786, closes#6530
Co-authored-by: WhiteWorld <WhiteWorld@users.noreply.github.com>
Co-authored-by: brantzh6 <brantzh6@users.noreply.github.com>
Co-authored-by: ten-ltw <ten-ltw@users.noreply.github.com>
Users are confused about the difference between `hermes model` (terminal
command for full provider setup) and `/model` (session command for switching
between already-configured providers). This distinction was not documented
anywhere.
Changes across 4 doc pages:
- cli-commands.md: Added warning callout explaining the difference, added
--global flag docs, added 'only see OpenRouter models?' info box
- slash-commands.md: Added notes on both TUI and messaging /model entries
that /model only switches between configured providers
- providers.md: Added 'Two Commands for Model Management' comparison table
near top of page, added warning callout in switching section
- faq.md: Added new FAQ entry '/model only shows one provider' with quick
reference table
Prompted by user feedback in Discord — new users consistently hit this
confusion when trying to add providers from inside a session.
- Matrix docs: full Proxy Mode section with architecture diagram,
step-by-step setup (host + Docker), docker-compose.yml/Dockerfile
examples, configuration reference, and limitations notes
- API Server docs: add Proxy Mode section explaining the api_server
serves as the backend for gateway proxy mode
- Environment variables reference: add GATEWAY_PROXY_URL and
GATEWAY_PROXY_KEY entries
- Rename platform from 'qq' to 'qqbot' across all integration points
(Platform enum, toolset, config keys, import paths, file rename qq.py → qqbot.py)
- Add PLATFORM_HINTS for QQBot in prompt_builder (QQ supports markdown)
- Set SUPPORTS_MESSAGE_EDITING = False to skip streaming on QQ
(prevents duplicate messages from non-editable partial + final sends)
- Add _send_qqbot() standalone send function for cron/send_message tool
- Add interactive _setup_qq() wizard in hermes_cli/setup.py
- Restore missing _setup_signal/email/sms/dingtalk/feishu/wecom/wecom_callback
functions that were lost during the original merge
Adds Arcee AI as a standard direct provider (ARCEEAI_API_KEY) with
Trinity models: trinity-large-thinking, trinity-large-preview, trinity-mini.
Standard OpenAI-compatible provider checklist: auth.py, config.py,
models.py, main.py, providers.py, doctor.py, model_normalize.py,
model_metadata.py, setup.py, trajectory_compressor.py.
Based on PR #9274 by arthurbr11, simplified to a standard direct
provider without dual-endpoint OpenRouter routing.
Cherry-picked from PR #7637 by hcshen0111.
Adds kimi-coding-cn provider with dedicated KIMI_CN_API_KEY env var
and api.moonshot.cn/v1 endpoint for China-region Moonshot users.
- New docs page: user-guide/features/web-dashboard.md covering
quick start, prerequisites, all three pages (Status, Config, API Keys),
the /reload slash command, REST API endpoints, CORS config, and
development workflow
- Added 'Management' category in sidebar for web-dashboard
- Added 'hermes web' to CLI commands reference with options table
- Added '/reload' to slash commands reference (both CLI and gateway tables)
Follow-up for cherry-picked PR #8272:
- Add MATRIX_RECOVERY_KEY to module docstring header in matrix.py
- Register in OPTIONAL_ENV_VARS (config.py) with password=True, advanced=True
- Add to _NON_SETUP_ENV_VARS set
- Document cross-signing verification in matrix.md E2EE section
- Update migration guide with recovery key step (step 3)
- Add to environment-variables.md reference
- Add rebrand_text() that replaces OpenClaw, Open Claw, Open-Claw,
ClawdBot, and MoltBot with Hermes (case-insensitive, word-boundary)
- Apply rebranding to memory entries (MEMORY.md, USER.md, daily memory)
- Apply rebranding to SOUL.md and workspace instructions via new
transform parameter on copy_file()
- Fix moldbot -> moltbot typo across codebase (claw.py, migration
script, docs, tests)
- Add unit tests for rebrand_text and integration tests for memory
and soul migration rebranding
Add the missing 'Adding a Platform Adapter' developer guide — a
comprehensive step-by-step checklist covering all 20+ integration
points (enum, adapter, config, runner, CLI, tools, toolsets, cron,
webhooks, tests, and docs). Includes common patterns for long-poll,
callback/webhook, and token-lock adapters with reference implementations.
Also adds full docs coverage for the WeCom Callback platform:
- New docs page: user-guide/messaging/wecom-callback.md
- Environment variables reference (9 WECOM_CALLBACK_* vars)
- Toolsets reference (hermes-wecom-callback)
- Messaging index (comparison table, architecture diagram, toolsets,
security, next-steps links)
- Integrations index listing
- Sidebar entries for both new pages
- Add shared is_wsl() to hermes_constants (like is_termux)
- Update supports_systemd_services() to verify systemd is actually
running on WSL before returning True
- Add WSL-specific guidance in gateway install/start/setup/status
for both cases: WSL+systemd and WSL without systemd
- Improve help strings: 'run' now says recommended for WSL/Docker,
'start'/'install' now mention systemd/launchd explicitly
- Add WSL gateway FAQ section with tmux/nohup/Task Scheduler tips
- Update CLI commands docs with WSL tip
- Deduplicate _is_wsl() from clipboard.py to shared hermes_constants
- Fix clipboard tests to reset hermes_constants cache
- 20 new WSL-specific tests covering detection, systemd check,
supports_systemd_services integration, and command output
Motivated by user feedback: took 1 hour to figure out run vs start
on WSL, Telegram bot kept disconnecting due to flaky WSL systemd.
Add is_network_accessible() helper using Python's ipaddress module to
robustly classify bind addresses (IPv4/IPv6 loopback, wildcards,
mapped addresses, hostname resolution with DNS-failure-fails-closed).
The API server connect() now refuses to start when the bind address is
network-accessible and no API_SERVER_KEY is set, preventing RCE from
other machines on the network.
Co-authored-by: entropidelic <entropidelic@users.noreply.github.com>
When enabled, @mentioning the bot in a DM creates a thread (default:
false). Supports both env var and YAML config (matrix.dm_mention_threads).
6 new tests, docs updated.
From #6957
- Remove sys.path.insert hack (leftover from standalone dev)
- Add token lock (acquire_scoped_lock/release_scoped_lock) in
connect()/disconnect() to prevent duplicate pollers across profiles
- Fix get_connected_platforms: WEIXIN check must precede generic
token/api_key check (requires both token AND account_id)
- Add WEIXIN_HOME_CHANNEL_NAME to _EXTRA_ENV_KEYS
- Add gateway setup wizard with QR login flow
- Add platform status check for partially configured state
- Add weixin.md docs page with full adapter documentation
- Update environment-variables.md reference with all 11 env vars
- Update sidebars.ts to include weixin docs page
- Wire all gateway integration points onto current main
Salvaged from PR #6747 by Zihan Huang.
- Add HERMES_CRON_TIMEOUT and HERMES_CRON_SCRIPT_TIMEOUT to env vars reference
- Add script timeout and provider recovery sections to cron features page
- Add timeout resolution chain and credential pool details to cron internals
Add streaming timeout documentation to three pages:
- guides/local-llm-on-mac.md: New 'Timeouts' section with table of all
three timeouts, their defaults, local auto-adjustments, and env var
overrides
- reference/faq.md: Tip box in the local models FAQ section
- user-guide/configuration.md: 'Streaming Timeouts' subsection under
the agent config section
Follow-up to #6967.
Raise the default httpx stream read timeout from 60s to 120s for all
providers. Additionally, auto-detect local LLM endpoints (Ollama,
llama.cpp, vLLM) and raise the read timeout to HERMES_API_TIMEOUT
(1800s) since local models can take minutes for prefill on large
contexts before producing the first token.
The stale stream timeout already had this local auto-detection pattern;
the httpx read timeout was missing it — causing a hard 60s wall that
users couldn't find (HERMES_STREAM_READ_TIMEOUT was undocumented).
Changes:
- Default HERMES_STREAM_READ_TIMEOUT: 60s -> 120s
- Auto-detect local endpoints -> raise to 1800s (user override respected)
- Document HERMES_STREAM_READ_TIMEOUT and HERMES_STREAM_STALE_TIMEOUT
- Add 10 parametrized tests
Reported-by: Pavan Srinivas (@pavanandums)
* feat: API server model name derived from profile name
For multi-user setups (e.g. OpenWebUI), each profile's API server now
advertises a distinct model name on /v1/models:
- Profile 'lucas' -> model ID 'lucas'
- Profile 'admin' -> model ID 'admin'
- Default profile -> 'hermes-agent' (unchanged)
Explicit override via API_SERVER_MODEL_NAME env var or
platforms.api_server.model_name config for custom names.
Resolves friction where OpenWebUI couldn't distinguish multiple
hermes-agent connections all advertising the same model name.
* docs: multi-user setup with profiles for API server + Open WebUI
- api-server.md: added Multi-User Setup section, API_SERVER_MODEL_NAME
to config table, updated /v1/models description
- open-webui.md: added Multi-User Setup with Profiles section with
step-by-step guide, updated model name references
- environment-variables.md: added API_SERVER_MODEL_NAME entry
/pr <anything> silently resolved to /prompt via the shortest-match
tiebreaker in prefix expansion, permanently overwriting the system
prompt and persisting to config. The command's functionality (setting
agent.system_prompt) is available via config.yaml and /personality
covers the common use case.
Removes: CommandDef, dispatch branch, _handle_prompt_command handler,
docs references, and updates subcommand extraction test.
Documents both debugging commands with full option tables,
examples, and usage guidance. Adds both to the top-level
commands table and as detailed sections with subsections for
log files, filtering behavior, and log rotation.
The old setup wizard (pre-March 2026) wrote LLM_MODEL to ~/.hermes/.env
across 12 provider flows. Commit 9302690e removed the writes but never
cleaned up existing .env files, leaving a dead variable that:
- Nothing in the codebase reads (zero os.getenv calls)
- The docs incorrectly claimed the gateway still used as fallback
- Caused user confusion when debugging model resolution issues
Changes:
- config.py: Bump _config_version 12 → 13, add migration to clear
LLM_MODEL and OPENAI_MODEL from .env (both dead since March 2026)
- environment-variables.md: Remove LLM_MODEL row, fix HERMES_MODEL
description to stop referencing it
- providers.md: Update deprecation notice from 'deprecated' to 'removed'
Add configurable reply-reference behavior for Discord, matching the
existing Telegram (TELEGRAM_REPLY_TO_MODE) and Mattermost
(MATTERMOST_REPLY_MODE) implementations.
Modes:
- 'off': never reply-reference the original message
- 'first': reply-reference on first chunk only (default, current behavior)
- 'all': reply-reference on every chunk
Set DISCORD_REPLY_TO_MODE=off in .env to disable reply-to messages.
Changes:
- gateway/config.py: parse DISCORD_REPLY_TO_MODE env var
- gateway/platforms/discord.py: read reply_to_mode from config, respect
it in send() — skip fetch_message entirely when 'off'
- hermes_cli/config.py: add to OPTIONAL_ENV_VARS for hermes setup
- 23 tests covering config, send behavior, env var override
- docs: discord.md env var table + environment-variables.md reference
Closes community request from Stuart on Discord.
* refactor: remove browser_close tool — auto-cleanup handles it
The browser_close tool was called in only 9% of browser sessions (13/144
navigations across 66 sessions), always redundantly — cleanup_browser()
already runs via _cleanup_task_resources() at conversation end, and the
background inactivity reaper catches anything else.
Removing it saves one tool schema slot in every browser-enabled API call.
Also fixes a latent bug: cleanup_browser() now handles Camofox sessions
too (previously only Browserbase). Camofox sessions were never auto-cleaned
per-task because they live in a separate dict from _active_sessions.
Files changed (13):
- tools/browser_tool.py: remove function, schema, registry entry; add
camofox cleanup to cleanup_browser()
- toolsets.py, model_tools.py, prompt_builder.py, display.py,
acp_adapter/tools.py: remove browser_close from all tool lists
- tests/: remove browser_close test, update toolset assertion
- docs/skills: remove all browser_close references
* fix: repeat browser_scroll 5x per call for meaningful page movement
Most backends scroll ~100px per call — barely visible on a typical
viewport. Repeating 5x gives ~500px (~half a viewport), making each
scroll tool call actually useful.
Backend-agnostic approach: works across all 7+ browser backends without
needing to configure each one's scroll amount individually. Breaks
early on error for the agent-browser path.
* feat: auto-return compact snapshot from browser_navigate
Every browser session starts with navigate → snapshot. Now navigate
returns the compact accessibility tree snapshot inline, saving one
tool call per browser task.
The snapshot captures the full page DOM (not viewport-limited), so
scroll position doesn't affect it. browser_snapshot remains available
for refreshing after interactions or getting full=true content.
Both Browserbase and Camofox paths auto-snapshot. If the snapshot
fails for any reason, navigation still succeeds — the snapshot is
a bonus, not a requirement.
Schema descriptions updated to guide models: navigate mentions it
returns a snapshot, snapshot mentions it's for refresh/full content.
* refactor: slim cronjob tool schema — consolidate model/provider, drop unused params
Session data (151 calls across 67 sessions) showed several schema
properties were never used by models. Consolidated and cleaned up:
Removed from schema (still work via backend/CLI):
- skill (singular): use skills array instead
- reason: pause-only, unnecessary
- include_disabled: now defaults to true
- base_url: extreme edge case, zero usage
- provider (standalone): merged into model object
Consolidated:
- model + provider → single 'model' object with {model, provider} fields.
If provider is omitted, the current main provider is pinned at creation
time so the job stays stable even if the user changes their default.
Kept:
- script: useful data collection feature
- skills array: standard interface for skill loading
Schema shrinks from 14 to 10 properties. All backend functionality
preserved — the Python function signature and handler lambda still
accept every parameter.
* fix: remove mixture_of_agents from core toolsets — opt-in only via hermes tools
MoA was in _HERMES_CORE_TOOLS and composite toolsets (hermes-cli,
hermes-messaging, safe), which meant it appeared in every session
for anyone with OPENROUTER_API_KEY set. The _DEFAULT_OFF_TOOLSETS
gate only works after running 'hermes tools' explicitly.
Now MoA only appears when a user explicitly enables it via
'hermes tools'. The moa toolset definition and check_fn remain
unchanged — it just needs to be opted into.
- Add full Supermemory section to memory-providers.md with config table,
tools, setup instructions, and key features
- Update provider count from 7 to 8 across memory.md and memory-providers.md
- Add SUPERMEMORY_API_KEY to environment-variables.md
- Add Supermemory to integrations/providers.md optional API keys table
- Add supermemory to cli-commands.md provider list
- Add Supermemory to profile isolation section (config file providers)
Two fixes:
1. Replace all stale 'hermes login' references with 'hermes auth' across
auth.py, auxiliary_client.py, delegate_tool.py, config.py, run_agent.py,
and documentation. The 'hermes login' command was deprecated; 'hermes auth'
now handles OAuth credential management.
2. Fix credential removal not persisting for singleton-sourced credentials
(device_code for openai-codex/nous, hermes_pkce for anthropic).
auth_remove_command already cleared env vars for env-sourced credentials,
but singleton credentials stored in the auth store were re-seeded by
_seed_from_singletons() on the next load_pool() call. Now clears the
underlying auth store entry when removing singleton-sourced credentials.
* feat(tools): add Firecrawl cloud browser provider
Adds Firecrawl (https://firecrawl.dev) as a cloud browser provider
alongside Browserbase and Browser Use. All browser tools route through
Firecrawl's cloud browser via CDP when selected.
- tools/browser_providers/firecrawl.py — FirecrawlProvider
- tools/browser_tool.py — register in _PROVIDER_REGISTRY
- hermes_cli/tools_config.py — add to onboarding provider picker
- hermes_cli/setup.py — add to setup summary
- hermes_cli/config.py — add FIRECRAWL_BROWSER_TTL config
- website/docs/ — browser docs and env var reference
Based on #4490 by @developersdigest.
Co-Authored-By: Developers Digest <124798203+developersdigest@users.noreply.github.com>
* refactor: simplify FirecrawlProvider.emergency_cleanup
Use self._headers() and self._api_url() instead of duplicating
env-var reads and header construction.
* fix: recognize Firecrawl in subscription browser detection
_resolve_browser_feature_state() now handles "firecrawl" as a direct
browser provider (same pattern as "browser-use"), so hermes setup
summary correctly shows "Browser Automation (Firecrawl)" instead of
misreporting as "Local browser".
Also fixes test_config_version_unchanged assertion (11 → 12).
---------
Co-authored-by: Developers Digest <124798203+developersdigest@users.noreply.github.com>
Skills can now declare config.yaml settings via metadata.hermes.config
in their SKILL.md frontmatter. Values are stored under skills.config.*
namespace, prompted during hermes config migrate, shown in hermes config
show, and injected into the skill context at load time.
Also adds the llm-wiki skill (Karpathy's LLM Wiki pattern) as the first
skill to use the new config interface, declaring wiki.path.
Skill config interface (new):
- agent/skill_utils.py: extract_skill_config_vars(), discover_all_skill_config_vars(),
resolve_skill_config_values(), SKILL_CONFIG_PREFIX
- agent/skill_commands.py: _inject_skill_config() injects resolved values
into skill messages as [Skill config: ...] block
- hermes_cli/config.py: get_missing_skill_config_vars(), skill config
prompting in migrate_config(), Skill Settings in show_config()
LLM Wiki skill (skills/research/llm-wiki/SKILL.md):
- Three-layer architecture (raw sources, wiki pages, schema)
- Three operations (ingest, query, lint)
- Session orientation, page thresholds, tag taxonomy, update policy,
scaling guidance, log rotation, archiving workflow
Docs: creating-skills.md, configuration.md, skills.md, skills-catalog.md
Closes#5100
Bring Matrix feature parity with Discord by adding mention gating and
auto-threading. Both default to true, matching Discord behavior.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Audit found 24+ discrepancies between docs and code. Fixed:
HIGH severity:
- Remove honcho toolset from tools-reference, toolsets-reference, and tools.md
(converted to memory provider plugin, not a built-in toolset)
- Add note that Honcho is available via plugin
MEDIUM severity:
- Add hermes memory command family to cli-commands.md (setup/status/off)
- Add --clone-all, --clone-from to profile create in cli-commands.md
- Add --max-turns option to hermes chat in cli-commands.md
- Add /btw slash command to slash-commands.md
- Fix profile show example output (remove nonexistent disk usage,
add .env and SOUL.md status lines)
- Add missing hermes-webhook toolset to toolsets-reference.md
- Add 5 missing providers to fallback-providers.md table
- Add 7 missing providers to providers.md fallback list
- Fix outdated model examples: glm-4-plus→glm-5, moonshot-v1-auto→kimi-for-coding
