* fix(providers): remove ~anthropic, skip ~ prefixes in sync script
OpenRouter uses ~ prefixes for internal auto-routing aliases (e.g. ~anthropic).
These are not real providers — they already route through openrouter.toml.
The generated ~anthropic.toml was confusing (looked like a stale backup)
and redundant with the existing openrouter provider.
- Delete providers/~anthropic.toml
- Skip provider IDs starting with ~ in sync-pricing.py --create-missing
* fix(providers): remove morph, aider, kwaipilot
- morph: specialized code-editing/patching tool, not a general LLM provider
- aider: CLI meta-tool wrapper (base_url empty), redundant with claude-code/codex-cli/gemini-cli/qwen-code
- kwaipilot: Kwai internal coding assistant routed via OpenRouter, niche
* fix(sync): add morph/aider/kwaipilot to SKIP_PROVIDERS to prevent re-creation
* feat(sync): merge OpenRouter-only providers into openrouter.toml
Instead of generating standalone .toml files that just wrap the OpenRouter
endpoint, merge their models directly into openrouter.toml with the
standard 'openrouter/{provider}/{model}' ID convention.
- Add _build_model_fields() and _model_lines() helpers to deduplicate
model rendering between standalone and merged paths
- Add merge_into_openrouter() that appends new models idempotently
- generate_provider_toml() now only runs for providers in PROVIDER_API
- --create-missing routes OpenRouter-only providers to merge_into_openrouter
* fix(providers): remove 14 OpenRouter-only standalone files
These providers have no direct public API and all route through
openrouter.ai/api/v1. Per the new sync-pricing.py policy, their models
will be merged into openrouter.toml on the next CI run instead of
living in separate files that just wrap the OpenRouter endpoint.
Removed: allenai, deepcogito, essentialai, inclusionai, inflection,
liquid, meituan, nex-agi, nousresearch, prime-intellect, relace,
switchpoint, tngtech, writer
* fix(providers): remove 7 niche providers with no driver support
No dedicated LLM driver code exists for these providers — they rely
purely on OpenAI-compatible passthrough with no special handling.
Removing them reduces registry noise; users can still reach them via
openrouter.toml if needed.
Removed: microsoft, ibm-granite, xiaomi, upstage, inception, aion-labs, arcee-ai
* fix(providers): remove ai21, chutes, venice
All three use ApiFormat::OpenAI with no special handling — pure passthrough.
No registry entry needed; users can reach them via openrouter.toml or by
adding a custom provider.
* docs(providers): rewrite README with full provider catalog and inclusion criteria
- List all 46 providers grouped by category with descriptions
- Document why each provider exists (direct API, unique endpoint, dedicated driver, local, CLI)
- Add inclusion criteria section explaining when to create standalone files vs merging into openrouter.toml
- Document sync script routing logic
- Update model counts: 49→46 providers, 339→232 models
* docs: add comprehensive READMEs for all registry sections + deepinfra provider
- agents/README.md: 32 agents across 7 categories with capability field reference
- channels/README.md: 44 channels across 5 categories with protocol reference table
- hands/README.md: 18 hands across 5 categories with HAND.toml format guide
- mcp/README.md: 33 MCP servers across 5 categories with transport/auth format
- plugins/README.md: 12 plugins with hook protocol documentation
- skills/README.md: 60 skills across 9 categories with SKILL.md format guide
- providers/deepinfra.toml: add DeepInfra serverless inference (5 models)
Hands Registry
Hands are pre-packaged capability bundles that compose agents, tools, skills, MCP servers, and plugins into a working application. Installing a hand gives you a complete, ready-to-use workflow — not just a single agent.
"You have many hands helping you."
A hand can contain one agent (single-agent) or multiple coordinated agents (multi-agent). Each agent in a multi-agent hand can have its own role-specific skills, model config, and capability restrictions.
File Format
Each hand lives in its own subdirectory:
hands/
├── researcher/
│ ├── HAND.toml # required: hand definition
│ └── SKILL.md # optional: shared reference knowledge for all agents
├── devteam/
│ ├── HAND.toml
│ ├── SKILL-pm.md # optional: role-specific knowledge for PM agent
│ ├── SKILL-engineer.md # optional: role-specific knowledge for Engineer agent
│ └── SKILL-qa.md # optional: role-specific knowledge for QA agent
HAND.toml format
id = "researcher"
version = "1.1.1"
name = "Researcher Hand"
description = "Autonomous deep researcher — exhaustive investigation, cross-referencing, fact-checking, and structured reports"
category = "productivity" # productivity | development | data | content | communication
icon = "lucide:flask-conical"
# Tools available to all agents in this hand
tools = [
"shell_exec", "file_read", "file_write", "web_fetch", "web_search",
"memory_store", "memory_recall", "knowledge_query", "event_publish",
]
# MCP servers all agents can use
mcp_servers = ["github"]
# Skills allowlist (empty = all available)
skills = []
# Plugin allowlist
allowed_plugins = ["todo-tracker", "auto-summarizer"]
# ─── Routing ──────────────────────────────────────────────────────────────────
[routing]
aliases = ["deep research", "investigate", "fact check"] # exact activation phrases
weak_aliases = ["research", "look into"] # keyword hints
# ─── Configurable settings ────────────────────────────────────────────────────
[[settings]]
key = "research_depth"
label = "Research Depth"
description = "How exhaustive each investigation should be"
setting_type = "select" # select | toggle | text
default = "thorough"
[[settings.options]]
value = "quick"
label = "Quick (5-10 sources, 1 pass)"
[[settings.options]]
value = "thorough"
label = "Thorough (20-30 sources, cross-referenced)"
# ─── Single-agent definition ──────────────────────────────────────────────────
[agent]
name = "researcher"
base = "researcher" # inherits from agents/researcher/agent.toml
[agent.model]
system_prompt = """Custom prompt override..."""
# ─── Multi-agent definition (alternative to [agent]) ─────────────────────────
[agents.pm]
coordinator = true
base = "planner" # inherits from agents/planner/agent.toml
invoke_hint = "Task coordination and issue triage"
[agents.engineer]
base = "coder"
invoke_hint = "Implementation"
[agents.qa]
base = "test-engineer"
invoke_hint = "Quality assurance and validation"
# ─── Dashboard metrics ────────────────────────────────────────────────────────
[dashboard]
[[dashboard.metrics]]
label = "Reports Written"
memory_key = "metric_reports_written"
format = "number"
# ─── i18n ─────────────────────────────────────────────────────────────────────
[i18n.zh]
name = "研究员"
description = "自主深度研究员 — 详尽调查、交叉核实、事实核查与结构化报告"
Installing and Using Hands
# List all available hands
librefang catalog hands
# Install a hand
librefang hand install researcher
# Install with a specific agent name
librefang hand install researcher --name my-researcher
# List installed hands
librefang hand list
# Remove a hand
librefang hand remove my-researcher
All Hands (18 total)
Productivity
| ID | Name | Category | Description |
|---|---|---|---|
| researcher | Researcher Hand | productivity | Autonomous deep researcher — exhaustive investigation, cross-referencing, fact-checking, and structured reports |
| strategist | Strategist Hand | productivity | Autonomous strategy analyst — market research, competitive analysis, business planning, and strategic recommendations |
| wiki | Wiki Hand | productivity | LLM-maintained personal knowledge base — builds an Obsidian-compatible wiki from raw sources with provenance tracking |
| browser | Browser Hand | productivity | Autonomous web browser — navigates sites, fills forms, clicks buttons, and completes multi-step web tasks |
Development
| ID | Name | Category | Description |
|---|---|---|---|
| devteam | Dev Team | development | Autonomous software development team — PM triages issues, Engineer implements, QA validates |
| devops | DevOps Hand | development | Autonomous DevOps engineer — CI/CD management, infrastructure monitoring, deployment automation, and incident response |
| apitester | API Tester Hand | development | Autonomous API testing agent — endpoint discovery, request validation, load testing, and regression detection |
Data
| ID | Name | Category | Description |
|---|---|---|---|
| analytics | Analytics Hand | data | Autonomous data analytics agent — data collection, analysis, visualization, dashboards, and automated reporting |
| collector | Collector Hand | data | Autonomous intelligence collector — monitors any target continuously with change detection and knowledge graphs |
| lead | Lead Hand | data | Autonomous lead generation — discovers, enriches, and delivers qualified leads on a schedule |
| predictor | Predictor Hand | data | Autonomous future predictor — collects signals, builds reasoning chains, makes calibrated predictions, and tracks accuracy |
| trader | Trading Hand | data | Autonomous market intelligence and trading engine — multi-signal analysis, adversarial bull/bear reasoning, and strict risk management |
Content
| ID | Name | Category | Description |
|---|---|---|---|
| clip | Clip Hand | content | Turns long-form video into viral short clips with captions and thumbnails |
| creator | Creator Hand | content | AI media studio — generates images, videos, music, and speech from text prompts |
Communication
| ID | Name | Category | Description |
|---|---|---|---|
| LinkedIn Hand | communication | Autonomous LinkedIn manager — profile optimization, content creation, networking, and professional engagement | |
| Reddit Hand | communication | Autonomous Reddit manager — monitors subreddits, posts content, replies to threads, and tracks engagement | |
| Twitter Hand | communication | Autonomous Twitter/X manager — content creation, scheduled posting, engagement, and performance tracking |
Data (additional)
| ID | Name | Category | Description |
|---|---|---|---|
| clip | Clip Hand | content | Turns long-form video into viral short clips with captions and thumbnails |
Resource Composition Summary
| Resource | How to compose | Notes |
|---|---|---|
| Agent templates | base = "coder" on [agents.*] |
Inherits prompt, model config, fallbacks from agents/coder/agent.toml |
| Tools | tools = [...] at hand level |
All agents in the hand share these built-in tools |
| Skills | skills = [...] at hand level |
Empty list means all available skills are allowed |
| MCP servers | mcp_servers = [...] at hand level |
Agent interacts via MCP tools, not hardcoded API calls |
| Plugins | allowed_plugins = [...] at hand level |
Empty list means all installed plugins are allowed |
| Per-agent knowledge | SKILL-{role}.md files |
Different reference prompts per agent role |
| Per-agent capabilities | [agents.*.capabilities] |
Fine-grained shell / network / memory per agent |
Adding a New Hand
- Create
hands/<name>/HAND.tomlwith at leastid,name,description, andcategory. - Add
SKILL.md(shared) orSKILL-{role}.md(per-agent) files for reference knowledge. - Use
base = "agent-name"in each[agents.*]block to inherit from existing agent templates. - Specify
mcp_servers,skills, andallowed_pluginsfor resource composition. - Ensure
idmatches the directory name. - Run
python scripts/validate.py. - Submit a PR.
See CONTRIBUTING.md for the full guide.