* 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)
Agents Registry
Agent templates for LibreFang. Each entry is a ready-to-install agent definition with a pre-configured system prompt, model settings, capability declarations, and routing aliases.
These are the reference agents shipped with the registry. You can install them as-is, override individual fields (model, system_prompt, tools) after installation, or use them as base templates inside a Hand.
File Format
Each agent lives in its own subdirectory containing a single agent.toml:
agents/
├── coder/
│ └── agent.toml
├── orchestrator/
│ └── agent.toml
└── ...
agent.toml format
name = "coder" # must match directory name
version = "0.4.3-beta3-20260314"
description = "Expert software engineer. Reads, writes, and analyzes code."
author = "librefang"
module = "builtin:chat" # runtime module — builtin:chat for all current agents
[metadata.routing]
aliases = ["write code", "fix bug", "implement feature"] # exact activation phrases
weak_aliases = ["refactor", "patch", "code change"] # keyword hints
[model]
provider = "default" # default = use LibreFang's configured primary provider
model = "default"
api_key_env = "GEMINI_API_KEY" # optional override: use this key env var
max_tokens = 8192
temperature = 0.3
system_prompt = """You are Coder, an expert software engineer..."""
[[fallback_models]] # optional: try these providers on failure
provider = "default"
model = "default"
api_key_env = "GROQ_API_KEY"
[schedule] # optional: continuous or cron activation
continuous = { check_interval_secs = 120 }
[resources]
max_llm_tokens_per_hour = 200000
max_concurrent_tools = 10
[capabilities]
tools = ["file_read", "file_write", "file_list", "shell_exec", "web_search", "web_fetch",
"memory_store", "memory_recall"]
network = ["*"] # "*" = all, or list specific domains
memory_read = ["*"]
memory_write = ["self.*"] # "self.*" = own namespace only
shell = ["cargo *", "rustc *", "git *", "npm *", "python *"] # shell command allowlist
agent_spawn = false
agent_message = [] # agents this agent may message
[i18n.zh]
name = "编码工程师"
description = "资深软件工程师:阅读、编写与分析代码。"
Installing and Using Agents
# List all available agent templates
librefang catalog agents
# Install an agent from the registry
librefang agent install coder
# Install with a custom name
librefang agent install coder --name my-coder
# List installed agents
librefang agent list
# Send a message to an installed agent
librefang agent message coder "Implement a binary search function in Rust"
# Remove an agent
librefang agent remove my-coder
Agents can also be used as base templates in a Hand by setting base = "coder" in HAND.toml.
All Agents (33 total)
Development
| Name | Description | Key Tools |
|---|---|---|
| architect | System architect. Designs software architectures, evaluates trade-offs, creates technical specifications. | file_read, file_write, web_search, web_fetch |
| code-reviewer | Senior code reviewer. Reviews PRs, identifies issues, suggests improvements with production standards. | file_read, shell_exec, web_search |
| coder | Expert software engineer. Reads, writes, and analyzes code. | file_read, file_write, shell_exec, web_search |
| debugger | Expert debugger. Traces bugs, analyzes stack traces, performs root cause analysis. | file_read, shell_exec, web_search |
| devops-lead | DevOps lead. Manages CI/CD, infrastructure, deployments, monitoring, and incident response. | shell_exec, file_read, web_search |
| ops | DevOps agent. Monitors systems, runs diagnostics, manages deployments. | shell_exec, file_read, web_search |
| test-engineer | Quality assurance engineer. Designs test strategies, writes tests, validates correctness. | file_read, file_write, shell_exec |
Research and Analysis
| Name | Description | Key Tools |
|---|---|---|
| academic-researcher | Academic research agent. Searches scholarly papers, summarizes findings, and generates literature reviews. | web_search, web_fetch, file_write |
| analyst | Data analyst. Processes data, generates insights, creates reports. | file_read, web_search, web_fetch |
| data-scientist | Data scientist. Analyzes datasets, builds models, creates visualizations, performs statistical analysis. | file_read, file_write, shell_exec |
| researcher | Research agent. Fetches web content and synthesizes information. | web_search, web_fetch, memory_store |
Writing and Documentation
| Name | Description | Key Tools |
|---|---|---|
| doc-writer | Technical writer. Creates documentation, README files, API docs, tutorials, and architecture guides. | file_read, file_write, web_fetch |
| writer | Content writer. Creates documentation, articles, and technical writing. | file_read, file_write, web_search |
Orchestration
| Name | Description | Key Capabilities |
|---|---|---|
| orchestrator | Meta-agent that decomposes complex tasks, delegates to specialist agents, and synthesizes results. | agent_spawn, agent_send, agent_list, agent_kill |
| planner | Project planner. Creates project plans, breaks down epics, estimates effort, identifies risks and dependencies. | file_read, file_write, web_search |
Business and Operations
| Name | Description | Key Tools |
|---|---|---|
| customer-support | Customer support agent for ticket handling, issue resolution, and customer communication. | memory_store, memory_recall, web_search |
| email-assistant | Email triage, drafting, scheduling, and inbox management agent. | memory_store, memory_recall, file_write |
| legal-assistant | Legal assistant agent for contract review, legal research, compliance checking, and document drafting. | file_read, file_write, web_search |
| meeting-assistant | Meeting notes, action items, agenda preparation, and follow-up tracking agent. | memory_store, memory_recall, file_write |
| recruiter | Recruiting agent for resume screening, candidate outreach, job description writing, and hiring pipeline management. | web_search, file_read, memory_store |
| sales-assistant | Sales assistant agent for CRM updates, outreach drafting, pipeline management, and deal tracking. | memory_store, memory_recall, web_search |
| security-auditor | Security specialist. Reviews code for vulnerabilities, checks configurations, performs threat modeling. | file_read, shell_exec, web_search |
Personal Productivity
| Name | Description | Key Tools |
|---|---|---|
| assistant | General-purpose assistant agent. The default agent for everyday tasks, questions, and conversations. | file_read, file_write, web_search, memory_store |
| health-tracker | Wellness tracking agent for health metrics, medication reminders, fitness goals, and lifestyle habits. | memory_store, memory_recall, file_write |
| hello-world | A friendly greeting agent that can read files, search the web, and answer everyday questions. | file_read, web_search, web_fetch |
| home-automation | Smart home control agent for IoT device management, automation rules, and home monitoring. | shell_exec, memory_store, web_fetch |
| personal-finance | Personal finance agent for budget tracking, expense analysis, savings goals, and financial planning. | file_read, memory_store, web_search |
| recipe-assistant | Cooking assistant that helps with recipes, meal plans, ingredient substitutions, and portion adjustments. | web_search, memory_recall, file_write |
| social-media | Social media content creation, scheduling, and engagement strategy agent. | web_fetch, web_search, file_write |
| translator | Multi-language translation agent for document translation, localization, and cross-cultural communication. | file_read, file_write, web_fetch |
| travel-planner | Trip planning agent for itinerary creation, booking research, budget estimation, and travel logistics. | web_search, web_fetch, memory_store |
| tutor | Teaching and explanation agent for learning, tutoring, and educational content creation. | web_search, memory_recall, file_write |
Capability Reference
| Capability field | Values | Effect |
|---|---|---|
tools |
list of tool names | Which built-in tools the agent may invoke |
network |
["*"] or domain list |
Outbound HTTP domain allowlist |
memory_read |
["*"] or namespace list |
Which memory namespaces the agent can read |
memory_write |
["self.*"] or ["*"] |
Which memory namespaces the agent can write |
shell |
glob patterns | Shell command allowlist (e.g. "cargo *") |
agent_spawn |
true / false |
Whether the agent can spawn child agents |
agent_message |
["*"] or agent name list |
Which agents this agent may send messages to |
Adding a New Agent
- Create
agents/<name>/agent.toml—namemust match the directory name. - Set
module = "builtin:chat"unless you have a custom runtime module. - Write a focused
system_prompt— clear role definition, methodology, and constraints. - Declare only the tools and capabilities the agent actually needs.
- Add
[metadata.routing]aliases so the router can activate the agent by intent. - Run
python scripts/validate.py. - Submit a PR.
See CONTRIBUTING.md for the full guide.