Files
librefang-registry/agents
Evan d43077afa9 fix(providers): remove ~anthropic, skip ~ prefixes in sync script (#69)
* 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)
2026-04-24 00:02:33 +09:00
..

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

  1. Create agents/<name>/agent.toml — name must match the directory name.
  2. Set module = "builtin:chat" unless you have a custom runtime module.
  3. Write a focused system_prompt — clear role definition, methodology, and constraints.
  4. Declare only the tools and capabilities the agent actually needs.
  5. Add [metadata.routing] aliases so the router can activate the agent by intent.
  6. Run python scripts/validate.py.
  7. Submit a PR.

See CONTRIBUTING.md for the full guide.